fix: prevent LLM observation hallucination by properly attributing tool results

Fixes #4181

The issue was that tool observations were being appended to the assistant
message in the conversation history, which caused the LLM to learn to
hallucinate fake observations during tool calls.

Changes:
- Add llm_response field to AgentAction to store the original LLM response
  before observation is appended
- Modify handle_agent_action_core to store llm_response before appending
  observation to text (text still contains observation for logging)
- Update CrewAgentExecutor._invoke_loop and _ainvoke_loop to:
  - Append LLM response as assistant message
  - Append observation as user message (not assistant)
- Apply same fix to LiteAgent._invoke_loop
- Apply same fix to CrewAgentExecutorFlow.execute_tool_action
- Fix add_image_tool special case in both executors to use same pattern
- Add comprehensive tests for proper message attribution

Co-Authored-By: João <joao@crewai.com>

README.md

@@ -57,14 +57,14 @@
 > It empowers developers with both high-level simplicity and precise low-level control, ideal for creating autonomous AI agents tailored to any scenario.
 
 - **CrewAI Crews**: Optimize for autonomy and collaborative intelligence.
-- **CrewAI Flows**: Enable granular, event-driven control, single LLM calls for precise task orchestration and supports Crews natively
+- **CrewAI Flows**: The **enterprise and production architecture** for building and deploying multi-agent systems. Enable granular, event-driven control, single LLM calls for precise task orchestration and supports Crews natively
 
 With over 100,000 developers certified through our community courses at [learn.crewai.com](https://learn.crewai.com), CrewAI is rapidly becoming the
 standard for enterprise-ready AI automation.
 
-# CrewAI AOP Suite
+# CrewAI AMP Suite
 
-CrewAI AOP Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
+CrewAI AMP Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
 
 You can try one part of the suite the [Crew Control Plane for free](https://app.crewai.com)
 
@@ -76,9 +76,9 @@ You can try one part of the suite the [Crew Control Plane for free](https://app.
 - **Advanced Security**: Built-in robust security and compliance measures ensuring safe deployment and management.
 - **Actionable Insights**: Real-time analytics and reporting to optimize performance and decision-making.
 - **24/7 Support**: Dedicated enterprise support to ensure uninterrupted operation and quick resolution of issues.
-- **On-premise and Cloud Deployment Options**: Deploy CrewAI AOP on-premise or in the cloud, depending on your security and compliance requirements.
+- **On-premise and Cloud Deployment Options**: Deploy CrewAI AMP on-premise or in the cloud, depending on your security and compliance requirements.
 
-CrewAI AOP is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient,
+CrewAI AMP is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient,
 intelligent automations.
 
 ## Table of contents
@@ -124,7 +124,8 @@ Setup and run your first CrewAI agents by following this tutorial.
 [![CrewAI Getting Started Tutorial](https://img.youtube.com/vi/-kSOTtYzgEw/hqdefault.jpg)](https://www.youtube.com/watch?v=-kSOTtYzgEw "CrewAI Getting Started Tutorial")
 
 ###
- Learning Resources
+
+Learning Resources
 
 Learn CrewAI through our comprehensive courses:
 
@@ -141,6 +142,7 @@ CrewAI offers two powerful, complementary approaches that work seamlessly togeth
    - Dynamic task delegation and collaboration
    - Specialized roles with defined goals and expertise
    - Flexible problem-solving approaches
+
 2. **Flows**: Production-ready, event-driven workflows that deliver precise control over complex automations. Flows provide:
 
    - Fine-grained control over execution paths for real-world scenarios
@@ -166,13 +168,13 @@ Ensure you have Python >=3.10 <3.14 installed on your system. CrewAI uses [UV](h
 First, install CrewAI:
 
 ```shell
-pip install crewai
+uv pip install crewai
 ```
 
 If you want to install the 'crewai' package along with its optional features that include additional tools for agents, you can do so by using the following command:
 
 ```shell
-pip install 'crewai[tools]'
+uv pip install 'crewai[tools]'
 ```
 
 The command above installs the basic package and also adds extra components which require more dependencies to function.
@@ -185,14 +187,15 @@ If you encounter issues during installation or usage, here are some common solut
 
 1. **ModuleNotFoundError: No module named 'tiktoken'**
 
-   - Install tiktoken explicitly: `pip install 'crewai[embeddings]'`
-   - If using embedchain or other tools: `pip install 'crewai[tools]'`
+   - Install tiktoken explicitly: `uv pip install 'crewai[embeddings]'`
+   - If using embedchain or other tools: `uv pip install 'crewai[tools]'`
+
 2. **Failed building wheel for tiktoken**
 
    - Ensure Rust compiler is installed (see installation steps above)
    - For Windows: Verify Visual C++ Build Tools are installed
-   - Try upgrading pip: `pip install --upgrade pip`
-   - If issues persist, use a pre-built wheel: `pip install tiktoken --prefer-binary`
+   - Try upgrading pip: `uv pip install --upgrade pip`
+   - If issues persist, use a pre-built wheel: `uv pip install tiktoken --prefer-binary`
 
 ### 2. Setting Up Your Crew with the YAML Configuration
 
@@ -270,7 +273,7 @@ reporting_analyst:
 
 **tasks.yaml**
 
-```yaml
+````yaml
 # src/my_project/config/tasks.yaml
 research_task:
   description: >
@@ -290,7 +293,7 @@ reporting_task:
     Formatted as markdown without '```'
   agent: reporting_analyst
   output_file: report.md
-```
+````
 
 **crew.py**
 
@@ -556,7 +559,7 @@ Please refer to the [Connect CrewAI to LLMs](https://docs.crewai.com/how-to/LLM-
 
 - **LangGraph**: While LangGraph provides a foundation for building agent workflows, its approach requires significant boilerplate code and complex state management patterns. The framework's tight coupling with LangChain can limit flexibility when implementing custom agent behaviors or integrating with external systems.
 
-*P.S. CrewAI demonstrates significant performance advantages over LangGraph, executing 5.76x faster in certain cases like this QA task example ([see comparison](https://github.com/crewAIInc/crewAI-examples/tree/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/QA%20Agent)) while achieving higher evaluation scores with faster completion times in certain coding tasks, like in this example ([detailed analysis](https://github.com/crewAIInc/crewAI-examples/blob/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/Coding%20Assistant/coding_assistant_eval.ipynb)).*
+_P.S. CrewAI demonstrates significant performance advantages over LangGraph, executing 5.76x faster in certain cases like this QA task example ([see comparison](https://github.com/crewAIInc/crewAI-examples/tree/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/QA%20Agent)) while achieving higher evaluation scores with faster completion times in certain coding tasks, like in this example ([detailed analysis](https://github.com/crewAIInc/crewAI-examples/blob/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/Coding%20Assistant/coding_assistant_eval.ipynb))._
 
 - **Autogen**: While Autogen excels at creating conversational agents capable of working together, it lacks an inherent concept of process. In Autogen, orchestrating agents' interactions requires additional programming, which can become complex and cumbersome as the scale of tasks grows.
 - **ChatDev**: ChatDev introduced the idea of processes into the realm of AI agents, but its implementation is quite rigid. Customizations in ChatDev are limited and not geared towards production environments, which can hinder scalability and flexibility in real-world applications.
@@ -611,7 +614,7 @@ uv build
 ### Installing Locally
 
 ```bash
-pip install dist/*.tar.gz
+uv pip install dist/*.tar.gz
 ```
 
 ## Telemetry
@@ -674,9 +677,9 @@ CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/b
 
 ### Enterprise Features
 
-- [What additional features does CrewAI AOP offer?](#q-what-additional-features-does-crewai-amp-offer)
-- [Is CrewAI AOP available for cloud and on-premise deployments?](#q-is-crewai-amp-available-for-cloud-and-on-premise-deployments)
-- [Can I try CrewAI AOP for free?](#q-can-i-try-crewai-amp-for-free)
+- [What additional features does CrewAI AMP offer?](#q-what-additional-features-does-crewai-amp-offer)
+- [Is CrewAI AMP available for cloud and on-premise deployments?](#q-is-crewai-amp-available-for-cloud-and-on-premise-deployments)
+- [Can I try CrewAI AMP for free?](#q-can-i-try-crewai-amp-for-free)
 
 ### Q: What exactly is CrewAI?
 
@@ -687,13 +690,13 @@ A: CrewAI is a standalone, lean, and fast Python framework built specifically fo
 A: Install CrewAI using pip:
 
 ```shell
-pip install crewai
+uv pip install crewai
 ```
 
 For additional tools, use:
 
 ```shell
-pip install 'crewai[tools]'
+uv pip install 'crewai[tools]'
 ```
 
 ### Q: Does CrewAI depend on LangChain?
@@ -732,17 +735,17 @@ A: Check out practical examples in the [CrewAI-examples repository](https://gith
 
 A: Contributions are warmly welcomed! Fork the repository, create your branch, implement your changes, and submit a pull request. See the Contribution section of the README for detailed guidelines.
 
-### Q: What additional features does CrewAI AOP offer?
+### Q: What additional features does CrewAI AMP offer?
 
-A: CrewAI AOP provides advanced features such as a unified control plane, real-time observability, secure integrations, advanced security, actionable insights, and dedicated 24/7 enterprise support.
+A: CrewAI AMP provides advanced features such as a unified control plane, real-time observability, secure integrations, advanced security, actionable insights, and dedicated 24/7 enterprise support.
 
-### Q: Is CrewAI AOP available for cloud and on-premise deployments?
+### Q: Is CrewAI AMP available for cloud and on-premise deployments?
 
-A: Yes, CrewAI AOP supports both cloud-based and on-premise deployment options, allowing enterprises to meet their specific security and compliance requirements.
+A: Yes, CrewAI AMP supports both cloud-based and on-premise deployment options, allowing enterprises to meet their specific security and compliance requirements.
 
-### Q: Can I try CrewAI AOP for free?
+### Q: Can I try CrewAI AMP for free?
 
-A: Yes, you can explore part of the CrewAI AOP Suite by accessing the [Crew Control Plane](https://app.crewai.com) for free.
+A: Yes, you can explore part of the CrewAI AMP Suite by accessing the [Crew Control Plane](https://app.crewai.com) for free.
 
 ### Q: Does CrewAI support fine-tuning or training custom models?
 
@@ -762,7 +765,7 @@ A: CrewAI is highly scalable, supporting simple automations and large-scale ente
 
 ### Q: Does CrewAI offer debugging and monitoring tools?
 
-A: Yes, CrewAI AOP includes advanced debugging, tracing, and real-time observability features, simplifying the management and troubleshooting of your automations.
+A: Yes, CrewAI AMP includes advanced debugging, tracing, and real-time observability features, simplifying the management and troubleshooting of your automations.
 
 ### Q: What programming languages does CrewAI support?
 

docs/docs.json

@@ -116,6 +116,7 @@
                   "en/concepts/tasks",
                   "en/concepts/crews",
                   "en/concepts/flows",
+                  "en/concepts/production-architecture",
                   "en/concepts/knowledge",
                   "en/concepts/llms",
                   "en/concepts/processes",
@@ -308,6 +309,7 @@
                   "en/learn/hierarchical-process",
                   "en/learn/human-input-on-execution",
                   "en/learn/human-in-the-loop",
+                  "en/learn/human-feedback-in-flows",
                   "en/learn/kickoff-async",
                   "en/learn/kickoff-for-each",
                   "en/learn/llm-connections",
@@ -327,7 +329,7 @@
             ]
           },
           {
-            "tab": "AOP",
+            "tab": "AMP",
             "icon": "briefcase",
             "groups": [
               {
@@ -558,6 +560,7 @@
                   "pt-BR/concepts/tasks",
                   "pt-BR/concepts/crews",
                   "pt-BR/concepts/flows",
+                  "pt-BR/concepts/production-architecture",
                   "pt-BR/concepts/knowledge",
                   "pt-BR/concepts/llms",
                   "pt-BR/concepts/processes",
@@ -702,6 +705,7 @@
               {
                 "group": "Observabilidade",
                 "pages": [
+                  "pt-BR/observability/tracing",
                   "pt-BR/observability/overview",
                   "pt-BR/observability/arize-phoenix",
                   "pt-BR/observability/braintrust",
@@ -735,6 +739,7 @@
                   "pt-BR/learn/hierarchical-process",
                   "pt-BR/learn/human-input-on-execution",
                   "pt-BR/learn/human-in-the-loop",
+                  "pt-BR/learn/human-feedback-in-flows",
                   "pt-BR/learn/kickoff-async",
                   "pt-BR/learn/kickoff-for-each",
                   "pt-BR/learn/llm-connections",
@@ -754,7 +759,7 @@
             ]
           },
           {
-            "tab": "AOP",
+            "tab": "AMP",
             "icon": "briefcase",
             "groups": [
               {
@@ -982,6 +987,7 @@
                   "ko/concepts/tasks",
                   "ko/concepts/crews",
                   "ko/concepts/flows",
+                  "ko/concepts/production-architecture",
                   "ko/concepts/knowledge",
                   "ko/concepts/llms",
                   "ko/concepts/processes",
@@ -1138,6 +1144,7 @@
               {
                 "group": "Observability",
                 "pages": [
+                  "ko/observability/tracing",
                   "ko/observability/overview",
                   "ko/observability/arize-phoenix",
                   "ko/observability/braintrust",
@@ -1171,6 +1178,7 @@
                   "ko/learn/hierarchical-process",
                   "ko/learn/human-input-on-execution",
                   "ko/learn/human-in-the-loop",
+                  "ko/learn/human-feedback-in-flows",
                   "ko/learn/kickoff-async",
                   "ko/learn/kickoff-for-each",
                   "ko/learn/llm-connections",

docs/en/api-reference/introduction.mdx

@@ -1,19 +1,19 @@
 ---
 title: "Introduction"
-description: "Complete reference for the CrewAI AOP REST API"
+description: "Complete reference for the CrewAI AMP REST API"
 icon: "code"
 mode: "wide"
 ---
 
-# CrewAI AOP API
+# CrewAI AMP API
 
-Welcome to the CrewAI AOP API reference. This API allows you to programmatically interact with your deployed crews, enabling integration with your applications, workflows, and services.
+Welcome to the CrewAI AMP API reference. This API allows you to programmatically interact with your deployed crews, enabling integration with your applications, workflows, and services.
 
 ## Quick Start
 
 <Steps>
   <Step title="Get Your API Credentials">
-    Navigate to your crew's detail page in the CrewAI AOP dashboard and copy your Bearer Token from the Status tab.
+    Navigate to your crew's detail page in the CrewAI AMP dashboard and copy your Bearer Token from the Status tab.
   </Step>
 
 <Step title="Discover Required Inputs">
@@ -48,7 +48,7 @@ curl -H "Authorization: Bearer YOUR_CREW_TOKEN" \
 
 <Tip>
   You can find both token types in the Status tab of your crew's detail page in
-  the CrewAI AOP dashboard.
+  the CrewAI AMP dashboard.
 </Tip>
 
 ## Base URL
@@ -84,7 +84,7 @@ The API uses standard HTTP status codes:
 ## Interactive Testing
 
 <Info>
-  **Why no "Send" button?** Since each CrewAI AOP user has their own unique crew
+  **Why no "Send" button?** Since each CrewAI AMP user has their own unique crew
   URL, we use **reference mode** instead of an interactive playground to avoid
   confusion. This shows you exactly what the requests should look like without
   non-functional send buttons.

docs/en/concepts/agents.mdx

@@ -8,6 +8,7 @@ mode: "wide"
 ## Overview of an Agent
 
 In the CrewAI framework, an `Agent` is an autonomous unit that can:
+
 - Perform specific tasks
 - Make decisions based on its role and goal
 - Use tools to accomplish objectives
@@ -16,15 +17,19 @@ In the CrewAI framework, an `Agent` is an autonomous unit that can:
 - Delegate tasks when allowed
 
 <Tip>
-Think of an agent as a specialized team member with specific skills, expertise, and responsibilities. For example, a `Researcher` agent might excel at gathering and analyzing information, while a `Writer` agent might be better at creating content.
+  Think of an agent as a specialized team member with specific skills,
+  expertise, and responsibilities. For example, a `Researcher` agent might excel
+  at gathering and analyzing information, while a `Writer` agent might be better
+  at creating content.
 </Tip>
 
 <Note type="info" title="Enterprise Enhancement: Visual Agent Builder">
-CrewAI AOP includes a Visual Agent Builder that simplifies agent creation and configuration without writing code. Design your agents visually and test them in real-time.
+CrewAI AMP includes a Visual Agent Builder that simplifies agent creation and configuration without writing code. Design your agents visually and test them in real-time.
 
 ![Visual Agent Builder Screenshot](/images/enterprise/crew-studio-interface.png)
 
 The Visual Agent Builder enables:
+
 - Intuitive agent configuration with form-based interfaces
 - Real-time testing and validation
 - Template library with pre-configured agent types
@@ -33,36 +38,36 @@ The Visual Agent Builder enables:
 
 ## Agent Attributes
 
-| Attribute                               | Parameter                | Type                          | Description                                                                                                          |
-| :-------------------------------------- | :----------------------- | :---------------------------- | :------------------------------------------------------------------------------------------------------------------- |
-| **Role**                                | `role`                   | `str`                         | Defines the agent's function and expertise within the crew.                                                           |
-| **Goal**                                | `goal`                   | `str`                         | The individual objective that guides the agent's decision-making.                                                     |
-| **Backstory**                           | `backstory`              | `str`                         | Provides context and personality to the agent, enriching interactions.                                                |
-| **LLM** _(optional)_                    | `llm`                    | `Union[str, LLM, Any]`        | Language model that powers the agent. Defaults to the model specified in `OPENAI_MODEL_NAME` or "gpt-4".              |
-| **Tools** _(optional)_                  | `tools`                  | `List[BaseTool]`              | Capabilities or functions available to the agent. Defaults to an empty list.                                          |
-| **Function Calling LLM** _(optional)_   | `function_calling_llm`   | `Optional[Any]`               | Language model for tool calling, overrides crew's LLM if specified.                                                   |
-| **Max Iterations** _(optional)_         | `max_iter`               | `int`                         | Maximum iterations before the agent must provide its best answer. Default is 20.                                      |
-| **Max RPM** _(optional)_                | `max_rpm`                | `Optional[int]`               | Maximum requests per minute to avoid rate limits.                                                                     |
-| **Max Execution Time** _(optional)_     | `max_execution_time`     | `Optional[int]`               | Maximum time (in seconds) for task execution.                                                                         |
-| **Verbose** _(optional)_                | `verbose`                | `bool`                        | Enable detailed execution logs for debugging. Default is False.                                                       |
-| **Allow Delegation** _(optional)_       | `allow_delegation`       | `bool`                        | Allow the agent to delegate tasks to other agents. Default is False.                                                  |
-| **Step Callback** _(optional)_          | `step_callback`          | `Optional[Any]`               | Function called after each agent step, overrides crew callback.                                                       |
-| **Cache** _(optional)_                  | `cache`                  | `bool`                        | Enable caching for tool usage. Default is True.                                                                       |
-| **System Template** _(optional)_        | `system_template`        | `Optional[str]`               | Custom system prompt template for the agent.                                                                          |
-| **Prompt Template** _(optional)_        | `prompt_template`        | `Optional[str]`               | Custom prompt template for the agent.                                                                                 |
-| **Response Template** _(optional)_      | `response_template`      | `Optional[str]`               | Custom response template for the agent.                                                                               |
-| **Allow Code Execution** _(optional)_   | `allow_code_execution`   | `Optional[bool]`              | Enable code execution for the agent. Default is False.                                                                |
-| **Max Retry Limit** _(optional)_        | `max_retry_limit`        | `int`                         | Maximum number of retries when an error occurs. Default is 2.                                                         |
-| **Respect Context Window** _(optional)_ | `respect_context_window` | `bool`                        | Keep messages under context window size by summarizing. Default is True.                                              |
-| **Code Execution Mode** _(optional)_    | `code_execution_mode`    | `Literal["safe", "unsafe"]`   | Mode for code execution: 'safe' (using Docker) or 'unsafe' (direct). Default is 'safe'.                               |
-| **Multimodal** _(optional)_             | `multimodal`             | `bool`                        | Whether the agent supports multimodal capabilities. Default is False.                                                  |
-| **Inject Date** _(optional)_            | `inject_date`            | `bool`                        | Whether to automatically inject the current date into tasks. Default is False.                                         |
-| **Date Format** _(optional)_            | `date_format`            | `str`                         | Format string for date when inject_date is enabled. Default is "%Y-%m-%d" (ISO format).                               |
-| **Reasoning** _(optional)_              | `reasoning`              | `bool`                        | Whether the agent should reflect and create a plan before executing a task. Default is False.                         |
-| **Max Reasoning Attempts** _(optional)_ | `max_reasoning_attempts` | `Optional[int]`               | Maximum number of reasoning attempts before executing the task. If None, will try until ready.                         |
-| **Embedder** _(optional)_               | `embedder`               | `Optional[Dict[str, Any]]`    | Configuration for the embedder used by the agent.                                                                     |
-| **Knowledge Sources** _(optional)_      | `knowledge_sources`      | `Optional[List[BaseKnowledgeSource]]` | Knowledge sources available to the agent.                                                                     |
-| **Use System Prompt** _(optional)_      | `use_system_prompt`      | `Optional[bool]`              | Whether to use system prompt (for o1 model support). Default is True.                                                 |
+| Attribute                               | Parameter                | Type                                  | Description                                                                                              |
+| :-------------------------------------- | :----------------------- | :------------------------------------ | :------------------------------------------------------------------------------------------------------- |
+| **Role**                                | `role`                   | `str`                                 | Defines the agent's function and expertise within the crew.                                              |
+| **Goal**                                | `goal`                   | `str`                                 | The individual objective that guides the agent's decision-making.                                        |
+| **Backstory**                           | `backstory`              | `str`                                 | Provides context and personality to the agent, enriching interactions.                                   |
+| **LLM** _(optional)_                    | `llm`                    | `Union[str, LLM, Any]`                | Language model that powers the agent. Defaults to the model specified in `OPENAI_MODEL_NAME` or "gpt-4". |
+| **Tools** _(optional)_                  | `tools`                  | `List[BaseTool]`                      | Capabilities or functions available to the agent. Defaults to an empty list.                             |
+| **Function Calling LLM** _(optional)_   | `function_calling_llm`   | `Optional[Any]`                       | Language model for tool calling, overrides crew's LLM if specified.                                      |
+| **Max Iterations** _(optional)_         | `max_iter`               | `int`                                 | Maximum iterations before the agent must provide its best answer. Default is 20.                         |
+| **Max RPM** _(optional)_                | `max_rpm`                | `Optional[int]`                       | Maximum requests per minute to avoid rate limits.                                                        |
+| **Max Execution Time** _(optional)_     | `max_execution_time`     | `Optional[int]`                       | Maximum time (in seconds) for task execution.                                                            |
+| **Verbose** _(optional)_                | `verbose`                | `bool`                                | Enable detailed execution logs for debugging. Default is False.                                          |
+| **Allow Delegation** _(optional)_       | `allow_delegation`       | `bool`                                | Allow the agent to delegate tasks to other agents. Default is False.                                     |
+| **Step Callback** _(optional)_          | `step_callback`          | `Optional[Any]`                       | Function called after each agent step, overrides crew callback.                                          |
+| **Cache** _(optional)_                  | `cache`                  | `bool`                                | Enable caching for tool usage. Default is True.                                                          |
+| **System Template** _(optional)_        | `system_template`        | `Optional[str]`                       | Custom system prompt template for the agent.                                                             |
+| **Prompt Template** _(optional)_        | `prompt_template`        | `Optional[str]`                       | Custom prompt template for the agent.                                                                    |
+| **Response Template** _(optional)_      | `response_template`      | `Optional[str]`                       | Custom response template for the agent.                                                                  |
+| **Allow Code Execution** _(optional)_   | `allow_code_execution`   | `Optional[bool]`                      | Enable code execution for the agent. Default is False.                                                   |
+| **Max Retry Limit** _(optional)_        | `max_retry_limit`        | `int`                                 | Maximum number of retries when an error occurs. Default is 2.                                            |
+| **Respect Context Window** _(optional)_ | `respect_context_window` | `bool`                                | Keep messages under context window size by summarizing. Default is True.                                 |
+| **Code Execution Mode** _(optional)_    | `code_execution_mode`    | `Literal["safe", "unsafe"]`           | Mode for code execution: 'safe' (using Docker) or 'unsafe' (direct). Default is 'safe'.                  |
+| **Multimodal** _(optional)_             | `multimodal`             | `bool`                                | Whether the agent supports multimodal capabilities. Default is False.                                    |
+| **Inject Date** _(optional)_            | `inject_date`            | `bool`                                | Whether to automatically inject the current date into tasks. Default is False.                           |
+| **Date Format** _(optional)_            | `date_format`            | `str`                                 | Format string for date when inject_date is enabled. Default is "%Y-%m-%d" (ISO format).                  |
+| **Reasoning** _(optional)_              | `reasoning`              | `bool`                                | Whether the agent should reflect and create a plan before executing a task. Default is False.            |
+| **Max Reasoning Attempts** _(optional)_ | `max_reasoning_attempts` | `Optional[int]`                       | Maximum number of reasoning attempts before executing the task. If None, will try until ready.           |
+| **Embedder** _(optional)_               | `embedder`               | `Optional[Dict[str, Any]]`            | Configuration for the embedder used by the agent.                                                        |
+| **Knowledge Sources** _(optional)_      | `knowledge_sources`      | `Optional[List[BaseKnowledgeSource]]` | Knowledge sources available to the agent.                                                                |
+| **Use System Prompt** _(optional)_      | `use_system_prompt`      | `Optional[bool]`                      | Whether to use system prompt (for o1 model support). Default is True.                                    |
 
 ## Creating Agents
 
@@ -137,7 +142,8 @@ class LatestAiDevelopmentCrew():
 ```
 
 <Note>
-The names you use in your YAML files (`agents.yaml`) should match the method names in your Python code.
+  The names you use in your YAML files (`agents.yaml`) should match the method
+  names in your Python code.
 </Note>
 
 ### Direct Code Definition
@@ -184,6 +190,7 @@ agent = Agent(
 Let's break down some key parameter combinations for common use cases:
 
 #### Basic Research Agent
+
 ```python Code
 research_agent = Agent(
     role="Research Analyst",
@@ -195,6 +202,7 @@ research_agent = Agent(
 ```
 
 #### Code Development Agent
+
 ```python Code
 dev_agent = Agent(
     role="Senior Python Developer",
@@ -208,6 +216,7 @@ dev_agent = Agent(
 ```
 
 #### Long-Running Analysis Agent
+
 ```python Code
 analysis_agent = Agent(
     role="Data Analyst",
@@ -221,6 +230,7 @@ analysis_agent = Agent(
 ```
 
 #### Custom Template Agent
+
 ```python Code
 custom_agent = Agent(
     role="Customer Service Representative",
@@ -236,6 +246,7 @@ custom_agent = Agent(
 ```
 
 #### Date-Aware Agent with Reasoning
+
 ```python Code
 strategic_agent = Agent(
     role="Market Analyst",
@@ -250,6 +261,7 @@ strategic_agent = Agent(
 ```
 
 #### Reasoning Agent
+
 ```python Code
 reasoning_agent = Agent(
     role="Strategic Planner",
@@ -263,6 +275,7 @@ reasoning_agent = Agent(
 ```
 
 #### Multimodal Agent
+
 ```python Code
 multimodal_agent = Agent(
     role="Visual Content Analyst",
@@ -276,52 +289,64 @@ multimodal_agent = Agent(
 ### Parameter Details
 
 #### Critical Parameters
+
 - `role`, `goal`, and `backstory` are required and shape the agent's behavior
 - `llm` determines the language model used (default: OpenAI's GPT-4)
 
 #### Memory and Context
+
 - `memory`: Enable to maintain conversation history
 - `respect_context_window`: Prevents token limit issues
 - `knowledge_sources`: Add domain-specific knowledge bases
 
 #### Execution Control
+
 - `max_iter`: Maximum attempts before giving best answer
 - `max_execution_time`: Timeout in seconds
 - `max_rpm`: Rate limiting for API calls
 - `max_retry_limit`: Retries on error
 
 #### Code Execution
+
 - `allow_code_execution`: Must be True to run code
 - `code_execution_mode`:
   - `"safe"`: Uses Docker (recommended for production)
   - `"unsafe"`: Direct execution (use only in trusted environments)
 
 <Note>
-  This runs a default Docker image. If you want to configure the docker image, the checkout the Code Interpreter Tool in the tools section.
-  Add the code interpreter tool as a tool in the agent as a tool parameter.
-  </Note>
+  This runs a default Docker image. If you want to configure the docker image,
+  the checkout the Code Interpreter Tool in the tools section. Add the code
+  interpreter tool as a tool in the agent as a tool parameter.
+</Note>
 
 #### Advanced Features
+
 - `multimodal`: Enable multimodal capabilities for processing text and visual content
 - `reasoning`: Enable agent to reflect and create plans before executing tasks
 - `inject_date`: Automatically inject current date into task descriptions
 
 #### Templates
+
 - `system_template`: Defines agent's core behavior
 - `prompt_template`: Structures input format
 - `response_template`: Formats agent responses
 
 <Note>
-When using custom templates, ensure that both `system_template` and `prompt_template` are defined. The `response_template` is optional but recommended for consistent output formatting.
+  When using custom templates, ensure that both `system_template` and
+  `prompt_template` are defined. The `response_template` is optional but
+  recommended for consistent output formatting.
 </Note>
 
 <Note>
-When using custom templates, you can use variables like `{role}`, `{goal}`, and `{backstory}` in your templates. These will be automatically populated during execution.
+  When using custom templates, you can use variables like `{role}`, `{goal}`,
+  and `{backstory}` in your templates. These will be automatically populated
+  during execution.
 </Note>
 
 ## Agent Tools
 
 Agents can be equipped with various tools to enhance their capabilities. CrewAI supports tools from:
+
 - [CrewAI Toolkit](https://github.com/joaomdmoura/crewai-tools)
 - [LangChain Tools](https://python.langchain.com/docs/integrations/tools)
 
@@ -360,7 +385,8 @@ analyst = Agent(
 ```
 
 <Note>
-When `memory` is enabled, the agent will maintain context across multiple interactions, improving its ability to handle complex, multi-step tasks.
+  When `memory` is enabled, the agent will maintain context across multiple
+  interactions, improving its ability to handle complex, multi-step tasks.
 </Note>
 
 ## Context Window Management
@@ -390,6 +416,7 @@ smart_agent = Agent(
 ```
 
 **What happens when context limits are exceeded:**
+
 - ⚠️ **Warning message**: `"Context length exceeded. Summarizing content to fit the model context window."`
 - 🔄 **Automatic summarization**: CrewAI intelligently summarizes the conversation history
 - ✅ **Continued execution**: Task execution continues seamlessly with the summarized context
@@ -411,6 +438,7 @@ strict_agent = Agent(
 ```
 
 **What happens when context limits are exceeded:**
+
 - ❌ **Error message**: `"Context length exceeded. Consider using smaller text or RAG tools from crewai_tools."`
 - 🛑 **Execution stops**: Task execution halts immediately
 - 🔧 **Manual intervention required**: You need to modify your approach
@@ -418,6 +446,7 @@ strict_agent = Agent(
 ### Choosing the Right Setting
 
 #### Use `respect_context_window=True` (Default) when:
+
 - **Processing large documents** that might exceed context limits
 - **Long-running conversations** where some summarization is acceptable
 - **Research tasks** where general context is more important than exact details
@@ -436,6 +465,7 @@ document_processor = Agent(
 ```
 
 #### Use `respect_context_window=False` when:
+
 - **Precision is critical** and information loss is unacceptable
 - **Legal or medical tasks** requiring complete context
 - **Code review** where missing details could introduce bugs
@@ -458,6 +488,7 @@ precision_agent = Agent(
 When dealing with very large datasets, consider these strategies:
 
 #### 1. Use RAG Tools
+
 ```python Code
 from crewai_tools import RagTool
 
@@ -475,6 +506,7 @@ rag_agent = Agent(
 ```
 
 #### 2. Use Knowledge Sources
+
 ```python Code
 # Use knowledge sources instead of large prompts
 knowledge_agent = Agent(
@@ -498,6 +530,7 @@ knowledge_agent = Agent(
 ### Troubleshooting Context Issues
 
 **If you're getting context limit errors:**
+
 ```python Code
 # Quick fix: Enable automatic handling
 agent.respect_context_window = True
@@ -511,6 +544,7 @@ agent.tools = [RagTool()]
 ```
 
 **If automatic summarization loses important information:**
+
 ```python Code
 # Disable auto-summarization and use RAG instead
 agent = Agent(
@@ -524,7 +558,10 @@ agent = Agent(
 ```
 
 <Note>
-The context window management feature works automatically in the background. You don't need to call any special functions - just set `respect_context_window` to your preferred behavior and CrewAI handles the rest!
+  The context window management feature works automatically in the background.
+  You don't need to call any special functions - just set
+  `respect_context_window` to your preferred behavior and CrewAI handles the
+  rest!
 </Note>
 
 ## Direct Agent Interaction with `kickoff()`
@@ -556,10 +593,10 @@ print(result.raw)
 
 ### Parameters and Return Values
 
-| Parameter         | Type                                | Description                                                               |
-| :---------------- | :---------------------------------- | :------------------------------------------------------------------------ |
-| `messages`        | `Union[str, List[Dict[str, str]]]`  | Either a string query or a list of message dictionaries with role/content |
-| `response_format` | `Optional[Type[Any]]`               | Optional Pydantic model for structured output                             |
+| Parameter         | Type                               | Description                                                               |
+| :---------------- | :--------------------------------- | :------------------------------------------------------------------------ |
+| `messages`        | `Union[str, List[Dict[str, str]]]` | Either a string query or a list of message dictionaries with role/content |
+| `response_format` | `Optional[Type[Any]]`              | Optional Pydantic model for structured output                             |
 
 The method returns a `LiteAgentOutput` object with the following properties:
 
@@ -621,28 +658,34 @@ asyncio.run(main())
 ```
 
 <Note>
-The `kickoff()` method uses a `LiteAgent` internally, which provides a simpler execution flow while preserving all of the agent's configuration (role, goal, backstory, tools, etc.).
+  The `kickoff()` method uses a `LiteAgent` internally, which provides a simpler
+  execution flow while preserving all of the agent's configuration (role, goal,
+  backstory, tools, etc.).
 </Note>
 
 ## Important Considerations and Best Practices
 
 ### Security and Code Execution
+
 - When using `allow_code_execution`, be cautious with user input and always validate it
 - Use `code_execution_mode: "safe"` (Docker) in production environments
 - Consider setting appropriate `max_execution_time` limits to prevent infinite loops
 
 ### Performance Optimization
+
 - Use `respect_context_window: true` to prevent token limit issues
 - Set appropriate `max_rpm` to avoid rate limiting
 - Enable `cache: true` to improve performance for repetitive tasks
 - Adjust `max_iter` and `max_retry_limit` based on task complexity
 
 ### Memory and Context Management
+
 - Leverage `knowledge_sources` for domain-specific information
 - Configure `embedder` when using custom embedding models
 - Use custom templates (`system_template`, `prompt_template`, `response_template`) for fine-grained control over agent behavior
 
 ### Advanced Features
+
 - Enable `reasoning: true` for agents that need to plan and reflect before executing complex tasks
 - Set appropriate `max_reasoning_attempts` to control planning iterations (None for unlimited attempts)
 - Use `inject_date: true` to provide agents with current date awareness for time-sensitive tasks
@@ -650,6 +693,7 @@ The `kickoff()` method uses a `LiteAgent` internally, which provides a simpler e
 - Enable `multimodal: true` for agents that need to process both text and visual content
 
 ### Agent Collaboration
+
 - Enable `allow_delegation: true` when agents need to work together
 - Use `step_callback` to monitor and log agent interactions
 - Consider using different LLMs for different purposes:
@@ -657,6 +701,7 @@ The `kickoff()` method uses a `LiteAgent` internally, which provides a simpler e
   - `function_calling_llm` for efficient tool usage
 
 ### Date Awareness and Reasoning
+
 - Use `inject_date: true` to provide agents with current date awareness for time-sensitive tasks
 - Customize the date format with `date_format` using standard Python datetime format codes
 - Valid format codes include: %Y (year), %m (month), %d (day), %B (full month name), etc.
@@ -664,22 +709,26 @@ The `kickoff()` method uses a `LiteAgent` internally, which provides a simpler e
 - Enable `reasoning: true` for complex tasks that benefit from upfront planning and reflection
 
 ### Model Compatibility
+
 - Set `use_system_prompt: false` for older models that don't support system messages
 - Ensure your chosen `llm` supports the features you need (like function calling)
 
 ## Troubleshooting Common Issues
 
 1. **Rate Limiting**: If you're hitting API rate limits:
+
    - Implement appropriate `max_rpm`
    - Use caching for repetitive operations
    - Consider batching requests
 
 2. **Context Window Errors**: If you're exceeding context limits:
+
    - Enable `respect_context_window`
    - Use more efficient prompts
    - Clear agent memory periodically
 
 3. **Code Execution Issues**: If code execution fails:
+
    - Verify Docker is installed for safe mode
    - Check execution permissions
    - Review code sandbox settings

docs/en/concepts/cli.mdx

@@ -5,7 +5,12 @@ icon: terminal
 mode: "wide"
 ---
 
-<Warning>Since release 0.140.0, CrewAI AOP started a process of migrating their login provider. As such, the authentication flow via CLI was updated. Users that use Google to login, or that created their account after July 3rd, 2025 will be unable to log in with older versions of the `crewai` library.</Warning>
+<Warning>
+  Since release 0.140.0, CrewAI AMP started a process of migrating their login
+  provider. As such, the authentication flow via CLI was updated. Users that use
+  Google to login, or that created their account after July 3rd, 2025 will be
+  unable to log in with older versions of the `crewai` library.
+</Warning>
 
 ## Overview
 
@@ -41,6 +46,7 @@ crewai create [OPTIONS] TYPE NAME
 - `NAME`: Name of the crew or flow
 
 Example:
+
 ```shell Terminal
 crewai create crew my_new_crew
 crewai create flow my_new_flow
@@ -57,6 +63,7 @@ crewai version [OPTIONS]
 - `--tools`: (Optional) Show the installed version of CrewAI tools
 
 Example:
+
 ```shell Terminal
 crewai version
 crewai version --tools
@@ -74,6 +81,7 @@ crewai train [OPTIONS]
 - `-f, --filename TEXT`: Path to a custom file for training (default: "trained_agents_data.pkl")
 
 Example:
+
 ```shell Terminal
 crewai train -n 10 -f my_training_data.pkl
 ```
@@ -89,6 +97,7 @@ crewai replay [OPTIONS]
 - `-t, --task_id TEXT`: Replay the crew from this task ID, including all subsequent tasks
 
 Example:
+
 ```shell Terminal
 crewai replay -t task_123456
 ```
@@ -118,6 +127,7 @@ crewai reset-memories [OPTIONS]
 - `-a, --all`: Reset ALL memories
 
 Example:
+
 ```shell Terminal
 crewai reset-memories --long --short
 crewai reset-memories --all
@@ -135,6 +145,7 @@ crewai test [OPTIONS]
 - `-m, --model TEXT`: LLM Model to run the tests on the Crew (default: "gpt-4o-mini")
 
 Example:
+
 ```shell Terminal
 crewai test -n 5 -m gpt-3.5-turbo
 ```
@@ -148,12 +159,16 @@ crewai run
 ```
 
 <Note>
-Starting from version 0.103.0, the `crewai run` command can be used to run both standard crews and flows. For flows, it automatically detects the type from pyproject.toml and runs the appropriate command. This is now the recommended way to run both crews and flows.
+  Starting from version 0.103.0, the `crewai run` command can be used to run
+  both standard crews and flows. For flows, it automatically detects the type
+  from pyproject.toml and runs the appropriate command. This is now the
+  recommended way to run both crews and flows.
 </Note>
 
 <Note>
-Make sure to run these commands from the directory where your CrewAI project is set up.
-Some commands may require additional configuration or setup within your project structure.
+  Make sure to run these commands from the directory where your CrewAI project
+  is set up. Some commands may require additional configuration or setup within
+  your project structure.
 </Note>
 
 ### 9. Chat
@@ -165,6 +180,7 @@ After receiving the results, you can continue interacting with the assistant for
 ```shell Terminal
 crewai chat
 ```
+
 <Note>
 Ensure you execute these commands from your CrewAI project's root directory.
 </Note>
@@ -182,28 +198,30 @@ def crew(self) -> Crew:
         chat_llm="gpt-4o",  # LLM for chat orchestration
     )
 ```
+
 </Note>
 
 ### 10. Deploy
 
-Deploy the crew or flow to [CrewAI AOP](https://app.crewai.com).
+Deploy the crew or flow to [CrewAI AMP](https://app.crewai.com).
 
-- **Authentication**: You need to be authenticated to deploy to CrewAI AOP.
-    You can login or create an account with:
-    ```shell Terminal
-    crewai login
-    ```
+- **Authentication**: You need to be authenticated to deploy to CrewAI AMP.
+  You can login or create an account with:
+
+  ```shell Terminal
+  crewai login
+  ```
 
 - **Create a deployment**: Once you are authenticated, you can create a deployment for your crew or flow from the root of your localproject.
-    ```shell Terminal
-    crewai deploy create
-    ```
-    - Reads your local project configuration.
-    - Prompts you to confirm the environment variables (like `OPENAI_API_KEY`, `SERPER_API_KEY`) found locally. These will be securely stored with the deployment on the Enterprise platform. Ensure your sensitive keys are correctly configured locally (e.g., in a `.env` file) before running this.
+  ```shell Terminal
+  crewai deploy create
+  ```
+  - Reads your local project configuration.
+  - Prompts you to confirm the environment variables (like `OPENAI_API_KEY`, `SERPER_API_KEY`) found locally. These will be securely stored with the deployment on the Enterprise platform. Ensure your sensitive keys are correctly configured locally (e.g., in a `.env` file) before running this.
 
 ### 11. Organization Management
 
-Manage your CrewAI AOP organizations.
+Manage your CrewAI AMP organizations.
 
 ```shell Terminal
 crewai org [COMMAND] [OPTIONS]
@@ -212,65 +230,80 @@ crewai org [COMMAND] [OPTIONS]
 #### Commands:
 
 - `list`: List all organizations you belong to
+
 ```shell Terminal
 crewai org list
 ```
 
 - `current`: Display your currently active organization
+
 ```shell Terminal
 crewai org current
 ```
 
 - `switch`: Switch to a specific organization
+
 ```shell Terminal
 crewai org switch <organization_id>
 ```
 
 <Note>
-You must be authenticated to CrewAI AOP to use these organization management commands.
+  You must be authenticated to CrewAI AMP to use these organization management
+  commands.
 </Note>
 
 - **Create a deployment** (continued):
-    - Links the deployment to the corresponding remote GitHub repository (it usually detects this automatically).
 
-- **Deploy the Crew**: Once you are authenticated, you can deploy your crew or flow to CrewAI AOP.
-    ```shell Terminal
-    crewai deploy push
-    ```
-    - Initiates the deployment process on the CrewAI AOP platform.
-    - Upon successful initiation, it will output the Deployment created successfully! message along with the Deployment Name and a unique Deployment ID (UUID).
+  - Links the deployment to the corresponding remote GitHub repository (it usually detects this automatically).
+
+- **Deploy the Crew**: Once you are authenticated, you can deploy your crew or flow to CrewAI AMP.
+
+  ```shell Terminal
+  crewai deploy push
+  ```
+
+  - Initiates the deployment process on the CrewAI AMP platform.
+  - Upon successful initiation, it will output the Deployment created successfully! message along with the Deployment Name and a unique Deployment ID (UUID).
 
 - **Deployment Status**: You can check the status of your deployment with:
-    ```shell Terminal
-    crewai deploy status
-    ```
-    This fetches the latest deployment status of your most recent deployment attempt (e.g., `Building Images for Crew`, `Deploy Enqueued`, `Online`).
+
+  ```shell Terminal
+  crewai deploy status
+  ```
+
+  This fetches the latest deployment status of your most recent deployment attempt (e.g., `Building Images for Crew`, `Deploy Enqueued`, `Online`).
 
 - **Deployment Logs**: You can check the logs of your deployment with:
-    ```shell Terminal
-    crewai deploy logs
-    ```
-    This streams the deployment logs to your terminal.
+
+  ```shell Terminal
+  crewai deploy logs
+  ```
+
+  This streams the deployment logs to your terminal.
 
 - **List deployments**: You can list all your deployments with:
-    ```shell Terminal
-    crewai deploy list
-    ```
-    This lists all your deployments.
+
+  ```shell Terminal
+  crewai deploy list
+  ```
+
+  This lists all your deployments.
 
 - **Delete a deployment**: You can delete a deployment with:
-    ```shell Terminal
-    crewai deploy remove
-    ```
-    This deletes the deployment from the CrewAI AOP platform.
+
+  ```shell Terminal
+  crewai deploy remove
+  ```
+
+  This deletes the deployment from the CrewAI AMP platform.
 
 - **Help Command**: You can get help with the CLI with:
-    ```shell Terminal
-    crewai deploy --help
-    ```
-    This shows the help message for the CrewAI Deploy CLI.
+  ```shell Terminal
+  crewai deploy --help
+  ```
+  This shows the help message for the CrewAI Deploy CLI.
 
-Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI AOP](http://app.crewai.com) using the CLI.
+Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI AMP](http://app.crewai.com) using the CLI.
 
 <iframe
   className="w-full aspect-video rounded-xl"
@@ -283,25 +316,27 @@ Watch this video tutorial for a step-by-step demonstration of deploying your cre
 
 ### 11. Login
 
-Authenticate with CrewAI AOP using a secure device code flow (no email entry required).
+Authenticate with CrewAI AMP using a secure device code flow (no email entry required).
 
 ```shell Terminal
 crewai login
 ```
 
 What happens:
+
 - A verification URL and short code are displayed in your terminal
 - Your browser opens to the verification URL
 - Enter/confirm the code to complete authentication
 
 Notes:
+
 - The OAuth2 provider and domain are configured via `crewai config` (defaults use `login.crewai.com`)
 - After successful login, the CLI also attempts to authenticate to the Tool Repository automatically
 - If you reset your configuration, run `crewai login` again to re-authenticate
 
 ### 12. API Keys
 
-When running ```crewai create crew``` command, the CLI will show you a list of available LLM providers to choose from, followed by model selection for your chosen provider.
+When running `crewai create crew` command, the CLI will show you a list of available LLM providers to choose from, followed by model selection for your chosen provider.
 
 Once you've selected an LLM provider and model, you will be prompted for API keys.
 
@@ -309,11 +344,11 @@ Once you've selected an LLM provider and model, you will be prompted for API key
 
 Here's a list of the most popular LLM providers suggested by the CLI:
 
-* OpenAI
-* Groq
-* Anthropic
-* Google Gemini
-* SambaNova
+- OpenAI
+- Groq
+- Anthropic
+- Google Gemini
+- SambaNova
 
 When you select a provider, the CLI will then show you available models for that provider and prompt you to enter your API key.
 
@@ -325,7 +360,7 @@ When you select a provider, the CLI will prompt you to enter the Key name and th
 
 See the following link for each provider's key name:
 
-* [LiteLLM Providers](https://docs.litellm.ai/docs/providers)
+- [LiteLLM Providers](https://docs.litellm.ai/docs/providers)
 
 ### 13. Configuration Management
 
@@ -338,23 +373,26 @@ crewai config [COMMAND] [OPTIONS]
 #### Commands:
 
 - `list`: Display all CLI configuration parameters
+
 ```shell Terminal
 crewai config list
 ```
 
 - `set`: Set a CLI configuration parameter
+
 ```shell Terminal
 crewai config set <key> <value>
 ```
 
 - `reset`: Reset all CLI configuration parameters to default values
+
 ```shell Terminal
 crewai config reset
 ```
 
 #### Available Configuration Parameters
 
-- `enterprise_base_url`: Base URL of the CrewAI AOP instance
+- `enterprise_base_url`: Base URL of the CrewAI AMP instance
 - `oauth2_provider`: OAuth2 provider used for authentication (e.g., workos, okta, auth0)
 - `oauth2_audience`: OAuth2 audience value, typically used to identify the target API or resource
 - `oauth2_client_id`: OAuth2 client ID issued by the provider, used during authentication requests
@@ -363,43 +401,48 @@ crewai config reset
 #### Examples
 
 Display current configuration:
+
 ```shell Terminal
 crewai config list
 ```
 
 Example output:
-| Setting             | Value                    | Description                                                 |
+| Setting | Value | Description |
 | :------------------ | :----------------------- | :---------------------------------------------------------- |
-| enterprise_base_url | https://app.crewai.com   | Base URL of the CrewAI AOP instance                  |
-| org_name            | Not set                  | Name of the currently active organization                   |
-| org_uuid            | Not set                  | UUID of the currently active organization                   |
-| oauth2_provider     | workos                   | OAuth2 provider (e.g., workos, okta, auth0)                 |
-| oauth2_audience     | client_01YYY             | Audience identifying the target API/resource                |
-| oauth2_client_id    | client_01XXX             | OAuth2 client ID issued by the provider                     |
-| oauth2_domain       | login.crewai.com         | Provider domain (e.g., your-org.auth0.com)                  |
+| enterprise_base_url | https://app.crewai.com | Base URL of the CrewAI AMP instance |
+| org_name | Not set | Name of the currently active organization |
+| org_uuid | Not set | UUID of the currently active organization |
+| oauth2_provider | workos | OAuth2 provider (e.g., workos, okta, auth0) |
+| oauth2_audience | client_01YYY | Audience identifying the target API/resource |
+| oauth2_client_id | client_01XXX | OAuth2 client ID issued by the provider |
+| oauth2_domain | login.crewai.com | Provider domain (e.g., your-org.auth0.com) |
 
 Set the enterprise base URL:
+
 ```shell Terminal
 crewai config set enterprise_base_url https://my-enterprise.crewai.com
 ```
 
 Set OAuth2 provider:
+
 ```shell Terminal
 crewai config set oauth2_provider auth0
 ```
 
 Set OAuth2 domain:
+
 ```shell Terminal
 crewai config set oauth2_domain my-company.auth0.com
 ```
 
 Reset all configuration to defaults:
+
 ```shell Terminal
 crewai config reset
 ```
 
 <Tip>
-After resetting configuration, re-run `crewai login` to authenticate again.
+  After resetting configuration, re-run `crewai login` to authenticate again.
 </Tip>
 
 ### 14. Trace Management
@@ -413,16 +456,19 @@ crewai traces [COMMAND]
 #### Commands:
 
 - `enable`: Enable trace collection for crew/flow executions
+
 ```shell Terminal
 crewai traces enable
 ```
 
 - `disable`: Disable trace collection for crew/flow executions
+
 ```shell Terminal
 crewai traces disable
 ```
 
 - `status`: Show current trace collection status
+
 ```shell Terminal
 crewai traces status
 ```
@@ -432,19 +478,23 @@ crewai traces status
 Trace collection is controlled by checking three settings in priority order:
 
 1. **Explicit flag in code** (highest priority - can enable OR disable):
+
    ```python
    crew = Crew(agents=[...], tasks=[...], tracing=True)   # Always enable
    crew = Crew(agents=[...], tasks=[...], tracing=False)  # Always disable
    crew = Crew(agents=[...], tasks=[...])                 # Check lower priorities (default)
    ```
+
    - `tracing=True` will **always enable** tracing (overrides everything)
    - `tracing=False` will **always disable** tracing (overrides everything)
    - `tracing=None` or omitted will check lower priority settings
 
 2. **Environment variable** (second priority):
+
    ```env
    CREWAI_TRACING_ENABLED=true
    ```
+
    - Checked only if `tracing` is not explicitly set to `True` or `False` in code
    - Set to `true` or `1` to enable tracing
 
@@ -462,21 +512,30 @@ Trace collection is controlled by checking three settings in priority order:
 - Run `crewai traces enable`
 
 **To disable tracing**, use any ONE of these methods:
+
 - Set `tracing=False` in your Crew/Flow code (overrides everything), OR
 - Remove or set to `false` the `CREWAI_TRACING_ENABLED` env var, OR
 - Run `crewai traces disable`
 
 Higher priority settings override lower ones.
+
 </Note>
 
 <Tip>
-For more information about tracing, see the [Tracing documentation](/observability/tracing).
+  For more information about tracing, see the [Tracing
+  documentation](/observability/tracing).
 </Tip>
 
 <Tip>
-CrewAI CLI handles authentication to the Tool Repository automatically when adding packages to your project. Just append `crewai` before any `uv` command to use it. E.g. `crewai uv add requests`. For more information, see [Tool Repository](https://docs.crewai.com/enterprise/features/tool-repository) docs.
+  CrewAI CLI handles authentication to the Tool Repository automatically when
+  adding packages to your project. Just append `crewai` before any `uv` command
+  to use it. E.g. `crewai uv add requests`. For more information, see [Tool
+  Repository](https://docs.crewai.com/enterprise/features/tool-repository) docs.
 </Tip>
 
 <Note>
-Configuration settings are stored in `~/.config/crewai/settings.json`. Some settings like organization name and UUID are read-only and managed through authentication and organization commands. Tool repository related settings are hidden and cannot be set directly by users.
+  Configuration settings are stored in `~/.config/crewai/settings.json`. Some
+  settings like organization name and UUID are read-only and managed through
+  authentication and organization commands. Tool repository related settings are
+  hidden and cannot be set directly by users.
 </Note>

docs/en/concepts/event-listener.mdx

@@ -1,6 +1,6 @@
 ---
-title: 'Event Listeners'
-description: 'Tap into CrewAI events to build custom integrations and monitoring'
+title: "Event Listeners"
+description: "Tap into CrewAI events to build custom integrations and monitoring"
 icon: spinner
 mode: "wide"
 ---
@@ -20,11 +20,12 @@ CrewAI uses an event bus architecture to emit events throughout the execution li
 When specific actions occur in CrewAI (like a Crew starting execution, an Agent completing a task, or a tool being used), the system emits corresponding events. You can register handlers for these events to execute custom code when they occur.
 
 <Note type="info" title="Enterprise Enhancement: Prompt Tracing">
-CrewAI AOP provides a built-in Prompt Tracing feature that leverages the event system to track, store, and visualize all prompts, completions, and associated metadata. This provides powerful debugging capabilities and transparency into your agent operations.
+CrewAI AMP provides a built-in Prompt Tracing feature that leverages the event system to track, store, and visualize all prompts, completions, and associated metadata. This provides powerful debugging capabilities and transparency into your agent operations.
 
 ![Prompt Tracing Dashboard](/images/enterprise/traces-overview.png)
 
 With Prompt Tracing you can:
+
 - View the complete history of all prompts sent to your LLM
 - Track token usage and costs
 - Debug agent reasoning failures
@@ -274,7 +275,6 @@ The structure of the event object depends on the event type, but all events inhe
 
 Additional fields vary by event type. For example, `CrewKickoffCompletedEvent` includes `crew_name` and `output` fields.
 
-
 ## Advanced Usage: Scoped Handlers
 
 For temporary event handling (useful for testing or specific operations), you can use the `scoped_handlers` context manager:

docs/en/concepts/flows.mdx

@@ -572,6 +572,55 @@ The `third_method` and `fourth_method` listen to the output of the `second_metho
 
 When you run this Flow, the output will change based on the random boolean value generated by the `start_method`.
 
+### Human in the Loop (human feedback)
+
+The `@human_feedback` decorator enables human-in-the-loop workflows by pausing flow execution to collect feedback from a human. This is useful for approval gates, quality review, and decision points that require human judgment.
+
+```python Code
+from crewai.flow.flow import Flow, start, listen
+from crewai.flow.human_feedback import human_feedback, HumanFeedbackResult
+
+class ReviewFlow(Flow):
+    @start()
+    @human_feedback(
+        message="Do you approve this content?",
+        emit=["approved", "rejected", "needs_revision"],
+        llm="gpt-4o-mini",
+        default_outcome="needs_revision",
+    )
+    def generate_content(self):
+        return "Content to be reviewed..."
+
+    @listen("approved")
+    def on_approval(self, result: HumanFeedbackResult):
+        print(f"Approved! Feedback: {result.feedback}")
+
+    @listen("rejected")
+    def on_rejection(self, result: HumanFeedbackResult):
+        print(f"Rejected. Reason: {result.feedback}")
+```
+
+When `emit` is specified, the human's free-form feedback is interpreted by an LLM and collapsed into one of the specified outcomes, which then triggers the corresponding `@listen` decorator.
+
+You can also use `@human_feedback` without routing to simply collect feedback:
+
+```python Code
+@start()
+@human_feedback(message="Any comments on this output?")
+def my_method(self):
+    return "Output for review"
+
+@listen(my_method)
+def next_step(self, result: HumanFeedbackResult):
+    # Access feedback via result.feedback
+    # Access original output via result.output
+    pass
+```
+
+Access all feedback collected during a flow via `self.last_human_feedback` (most recent) or `self.human_feedback_history` (all feedback as a list).
+
+For a complete guide on human feedback in flows, including **async/non-blocking feedback** with custom providers (Slack, webhooks, etc.), see [Human Feedback in Flows](/en/learn/human-feedback-in-flows).
+
 ## Adding Agents to Flows
 
 Agents can be seamlessly integrated into your flows, providing a lightweight alternative to full Crews when you need simpler, focused task execution. Here's an example of how to use an Agent within a flow to perform market research:

docs/en/concepts/production-architecture.mdx

@@ -0,0 +1,154 @@
+---
+title: Production Architecture
+description: Best practices for building production-ready AI applications with CrewAI
+icon: server
+mode: "wide"
+---
+
+# The Flow-First Mindset
+
+When building production AI applications with CrewAI, **we recommend starting with a Flow**.
+
+While it's possible to run individual Crews or Agents, wrapping them in a Flow provides the necessary structure for a robust, scalable application.
+
+## Why Flows?
+
+1.  **State Management**: Flows provide a built-in way to manage state across different steps of your application. This is crucial for passing data between Crews, maintaining context, and handling user inputs.
+2.  **Control**: Flows allow you to define precise execution paths, including loops, conditionals, and branching logic. This is essential for handling edge cases and ensuring your application behaves predictably.
+3.  **Observability**: Flows provide a clear structure that makes it easier to trace execution, debug issues, and monitor performance. We recommend using [CrewAI Tracing](/en/observability/tracing) for detailed insights. Simply run `crewai login` to enable free observability features.
+
+## The Architecture
+
+A typical production CrewAI application looks like this:
+
+```mermaid
+graph TD
+    Start((Start)) --> Flow[Flow Orchestrator]
+    Flow --> State{State Management}
+    State --> Step1[Step 1: Data Gathering]
+    Step1 --> Crew1[Research Crew]
+    Crew1 --> State
+    State --> Step2{Condition Check}
+    Step2 -- "Valid" --> Step3[Step 3: Execution]
+    Step3 --> Crew2[Action Crew]
+    Step2 -- "Invalid" --> End((End))
+    Crew2 --> End
+```
+
+### 1. The Flow Class
+Your `Flow` class is the entry point. It defines the state schema and the methods that execute your logic.
+
+```python
+from crewai.flow.flow import Flow, listen, start
+from pydantic import BaseModel
+
+class AppState(BaseModel):
+    user_input: str = ""
+    research_results: str = ""
+    final_report: str = ""
+
+class ProductionFlow(Flow[AppState]):
+    @start()
+    def gather_input(self):
+        # ... logic to get input ...
+        pass
+
+    @listen(gather_input)
+    def run_research_crew(self):
+        # ... trigger a Crew ...
+        pass
+```
+
+### 2. State Management
+Use Pydantic models to define your state. This ensures type safety and makes it clear what data is available at each step.
+
+- **Keep it minimal**: Store only what you need to persist between steps.
+- **Use structured data**: Avoid unstructured dictionaries when possible.
+
+### 3. Crews as Units of Work
+Delegate complex tasks to Crews. A Crew should be focused on a specific goal (e.g., "Research a topic", "Write a blog post").
+
+- **Don't over-engineer Crews**: Keep them focused.
+- **Pass state explicitly**: Pass the necessary data from the Flow state to the Crew inputs.
+
+```python
+    @listen(gather_input)
+    def run_research_crew(self):
+        crew = ResearchCrew()
+        result = crew.kickoff(inputs={"topic": self.state.user_input})
+        self.state.research_results = result.raw
+```
+
+## Control Primitives
+
+Leverage CrewAI's control primitives to add robustness and control to your Crews.
+
+### 1. Task Guardrails
+Use [Task Guardrails](/en/concepts/tasks#task-guardrails) to validate task outputs before they are accepted. This ensures that your agents produce high-quality results.
+
+```python
+def validate_content(result: TaskOutput) -> Tuple[bool, Any]:
+    if len(result.raw) < 100:
+        return (False, "Content is too short. Please expand.")
+    return (True, result.raw)
+
+task = Task(
+    ...,
+    guardrail=validate_content
+)
+```
+
+### 2. Structured Outputs
+Always use structured outputs (`output_pydantic` or `output_json`) when passing data between tasks or to your application. This prevents parsing errors and ensures type safety.
+
+```python
+class ResearchResult(BaseModel):
+    summary: str
+    sources: List[str]
+
+task = Task(
+    ...,
+    output_pydantic=ResearchResult
+)
+```
+
+### 3. LLM Hooks
+Use [LLM Hooks](/en/learn/llm-hooks) to inspect or modify messages before they are sent to the LLM, or to sanitize responses.
+
+```python
+@before_llm_call
+def log_request(context):
+    print(f"Agent {context.agent.role} is calling the LLM...")
+```
+
+## Deployment Patterns
+
+When deploying your Flow, consider the following:
+
+### CrewAI Enterprise
+The easiest way to deploy your Flow is using CrewAI Enterprise. It handles the infrastructure, authentication, and monitoring for you.
+
+Check out the [Deployment Guide](/en/enterprise/guides/deploy-crew) to get started.
+
+```bash
+crewai deploy create
+```
+
+### Async Execution
+For long-running tasks, use `kickoff_async` to avoid blocking your API.
+
+### Persistence
+Use the `@persist` decorator to save the state of your Flow to a database. This allows you to resume execution if the process crashes or if you need to wait for human input.
+
+```python
+@persist
+class ProductionFlow(Flow[AppState]):
+    # ...
+```
+
+## Summary
+
+- **Start with a Flow.**
+- **Define a clear State.**
+- **Use Crews for complex tasks.**
+- **Deploy with an API and persistence.**

docs/en/concepts/tasks.mdx

@@ -14,11 +14,12 @@ Tasks provide all necessary details for execution, such as a description, the ag
 Tasks within CrewAI can be collaborative, requiring multiple agents to work together. This is managed through the task properties and orchestrated by the Crew's process, enhancing teamwork and efficiency.
 
 <Note type="info" title="Enterprise Enhancement: Visual Task Builder">
-CrewAI AOP includes a Visual Task Builder in Crew Studio that simplifies complex task creation and chaining. Design your task flows visually and test them in real-time without writing code.
+CrewAI AMP includes a Visual Task Builder in Crew Studio that simplifies complex task creation and chaining. Design your task flows visually and test them in real-time without writing code.
 
 ![Task Builder Screenshot](/images/enterprise/crew-studio-interface.png)
 
 The Visual Task Builder enables:
+
 - Drag-and-drop task creation
 - Visual task dependencies and flow
 - Real-time testing and validation
@@ -28,10 +29,12 @@ The Visual Task Builder enables:
 ### Task Execution Flow
 
 Tasks can be executed in two ways:
+
 - **Sequential**: Tasks are executed in the order they are defined
 - **Hierarchical**: Tasks are assigned to agents based on their roles and expertise
 
 The execution flow is defined when creating the crew:
+
 ```python Code
 crew = Crew(
     agents=[agent1, agent2],
@@ -42,30 +45,31 @@ crew = Crew(
 
 ## Task Attributes
 
-| Attribute                        | Parameters        | Type                          | Description                                                                                                          |
-| :------------------------------- | :---------------- | :---------------------------- | :------------------------------------------------------------------------------------------------------------------- |
-| **Description**                  | `description`     | `str`                         | A clear, concise statement of what the task entails.                                                                 |
-| **Expected Output**              | `expected_output` | `str`                         | A detailed description of what the task's completion looks like.                                                     |
-| **Name** _(optional)_            | `name`            | `Optional[str]`               | A name identifier for the task.                                                                                      |
-| **Agent** _(optional)_           | `agent`           | `Optional[BaseAgent]`         | The agent responsible for executing the task.                                                                        |
-| **Tools** _(optional)_           | `tools`           | `List[BaseTool]`              | The tools/resources the agent is limited to use for this task.                                                       |
-| **Context** _(optional)_         | `context`         | `Optional[List["Task"]]`      | Other tasks whose outputs will be used as context for this task.                                                     |
-| **Async Execution** _(optional)_ | `async_execution` | `Optional[bool]`              | Whether the task should be executed asynchronously. Defaults to False.                                               |
-| **Human Input** _(optional)_     | `human_input`     | `Optional[bool]`              | Whether the task should have a human review the final answer of the agent. Defaults to False.                        |
-| **Markdown** _(optional)_        | `markdown`        | `Optional[bool]`              | Whether the task should instruct the agent to return the final answer formatted in Markdown. Defaults to False.      |
-| **Config** _(optional)_          | `config`          | `Optional[Dict[str, Any]]`    | Task-specific configuration parameters.                                                                              |
-| **Output File** _(optional)_     | `output_file`     | `Optional[str]`               | File path for storing the task output.                                                                               |
-| **Create Directory** _(optional)_ | `create_directory` | `Optional[bool]`             | Whether to create the directory for output_file if it doesn't exist. Defaults to True.                               |
-| **Output JSON** _(optional)_     | `output_json`     | `Optional[Type[BaseModel]]`   | A Pydantic model to structure the JSON output.                                                                       |
-| **Output Pydantic** _(optional)_ | `output_pydantic` | `Optional[Type[BaseModel]]`   | A Pydantic model for task output.                                                                                    |
-| **Callback** _(optional)_        | `callback`        | `Optional[Any]`               | Function/object to be executed after task completion.                                                                |
-| **Guardrail** _(optional)_       | `guardrail`       | `Optional[Callable]`             | Function to validate task output before proceeding to next task.                                                  |
-| **Guardrails** _(optional)_       | `guardrails`       | `Optional[List[Callable] | List[str]]` | List of guardrails to validate task output before proceeding to next task.                                      |
-| **Guardrail Max Retries** _(optional)_ | `guardrail_max_retries` | `Optional[int]`     | Maximum number of retries when guardrail validation fails. Defaults to 3.                                         |
+| Attribute                              | Parameters              | Type                        | Description                                                                                                     |
+| :------------------------------------- | :---------------------- | :-------------------------- | :-------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------- |
+| **Description**                        | `description`           | `str`                       | A clear, concise statement of what the task entails.                                                            |
+| **Expected Output**                    | `expected_output`       | `str`                       | A detailed description of what the task's completion looks like.                                                |
+| **Name** _(optional)_                  | `name`                  | `Optional[str]`             | A name identifier for the task.                                                                                 |
+| **Agent** _(optional)_                 | `agent`                 | `Optional[BaseAgent]`       | The agent responsible for executing the task.                                                                   |
+| **Tools** _(optional)_                 | `tools`                 | `List[BaseTool]`            | The tools/resources the agent is limited to use for this task.                                                  |
+| **Context** _(optional)_               | `context`               | `Optional[List["Task"]]`    | Other tasks whose outputs will be used as context for this task.                                                |
+| **Async Execution** _(optional)_       | `async_execution`       | `Optional[bool]`            | Whether the task should be executed asynchronously. Defaults to False.                                          |
+| **Human Input** _(optional)_           | `human_input`           | `Optional[bool]`            | Whether the task should have a human review the final answer of the agent. Defaults to False.                   |
+| **Markdown** _(optional)_              | `markdown`              | `Optional[bool]`            | Whether the task should instruct the agent to return the final answer formatted in Markdown. Defaults to False. |
+| **Config** _(optional)_                | `config`                | `Optional[Dict[str, Any]]`  | Task-specific configuration parameters.                                                                         |
+| **Output File** _(optional)_           | `output_file`           | `Optional[str]`             | File path for storing the task output.                                                                          |
+| **Create Directory** _(optional)_      | `create_directory`      | `Optional[bool]`            | Whether to create the directory for output_file if it doesn't exist. Defaults to True.                          |
+| **Output JSON** _(optional)_           | `output_json`           | `Optional[Type[BaseModel]]` | A Pydantic model to structure the JSON output.                                                                  |
+| **Output Pydantic** _(optional)_       | `output_pydantic`       | `Optional[Type[BaseModel]]` | A Pydantic model for task output.                                                                               |
+| **Callback** _(optional)_              | `callback`              | `Optional[Any]`             | Function/object to be executed after task completion.                                                           |
+| **Guardrail** _(optional)_             | `guardrail`             | `Optional[Callable]`        | Function to validate task output before proceeding to next task.                                                |
+| **Guardrails** _(optional)_            | `guardrails`            | `Optional[List[Callable]    | List[str]]`                                                                                                     | List of guardrails to validate task output before proceeding to next task. |
+| **Guardrail Max Retries** _(optional)_ | `guardrail_max_retries` | `Optional[int]`             | Maximum number of retries when guardrail validation fails. Defaults to 3.                                       |
 
 <Note type="warning" title="Deprecated: max_retries">
   The task attribute `max_retries` is deprecated and will be removed in v1.0.0.
-  Use `guardrail_max_retries` instead to control retry attempts when a guardrail fails.
+  Use `guardrail_max_retries` instead to control retry attempts when a guardrail
+  fails.
 </Note>
 
 ## Creating Tasks
@@ -87,7 +91,7 @@ crew.kickoff(inputs={'topic': 'AI Agents'})
 
 Here's an example of how to configure tasks using YAML:
 
-```yaml tasks.yaml
+````yaml tasks.yaml
 research_task:
   description: >
     Conduct a thorough research about {topic}
@@ -107,7 +111,7 @@ reporting_task:
   agent: reporting_analyst
   markdown: true
   output_file: report.md
-```
+````
 
 To use this YAML configuration in your code, create a crew class that inherits from `CrewBase`:
 
@@ -165,7 +169,8 @@ class LatestAiDevelopmentCrew():
 ```
 
 <Note>
-The names you use in your YAML files (`agents.yaml` and `tasks.yaml`) should match the method names in your Python code.
+  The names you use in your YAML files (`agents.yaml` and `tasks.yaml`) should
+  match the method names in your Python code.
 </Note>
 
 ### Direct Code Definition (Alternative)
@@ -202,7 +207,8 @@ reporting_task = Task(
 ```
 
 <Tip>
-  Directly specify an `agent` for assignment or let the `hierarchical` CrewAI's process decide based on roles, availability, etc.
+  Directly specify an `agent` for assignment or let the `hierarchical` CrewAI's
+  process decide based on roles, availability, etc.
 </Tip>
 
 ## Task Output
@@ -224,7 +230,7 @@ By default, the `TaskOutput` will only include the `raw` output. A `TaskOutput`
 | **JSON Dict**     | `json_dict`     | `Optional[Dict[str, Any]]` | A dictionary representing the JSON output of the task.                                             |
 | **Agent**         | `agent`         | `str`                      | The agent that executed the task.                                                                  |
 | **Output Format** | `output_format` | `OutputFormat`             | The format of the task output, with options including RAW, JSON, and Pydantic. The default is RAW. |
-| **Messages**      | `messages`      | `list[LLMMessage]`         | The messages from the last task execution.                                                           |
+| **Messages**      | `messages`      | `list[LLMMessage]`         | The messages from the last task execution.                                                         |
 
 ### Task Methods and Properties
 
@@ -287,12 +293,13 @@ formatted_task = Task(
 ```
 
 When `markdown=True`, the agent will receive additional instructions to format the output using:
+
 - `#` for headers
 - `**text**` for bold text
 - `*text*` for italic text
 - `-` or `*` for bullet points
 - `` `code` `` for inline code
-- ``` ```language ``` for code blocks
+- ` `language ``` for code blocks
 
 ### YAML Configuration with Markdown
 
@@ -303,7 +310,7 @@ analysis_task:
   expected_output: >
     A comprehensive analysis with charts and key findings
   agent: analyst
-  markdown: true  # Enable markdown formatting
+  markdown: true # Enable markdown formatting
   output_file: analysis.md
 ```
 
@@ -315,7 +322,9 @@ analysis_task:
 - **Cross-Platform Compatibility**: Markdown is universally supported
 
 <Note>
-The markdown formatting instructions are automatically added to the task prompt when `markdown=True`, so you don't need to specify formatting requirements in your task description.
+  The markdown formatting instructions are automatically added to the task
+  prompt when `markdown=True`, so you don't need to specify formatting
+  requirements in your task description.
 </Note>
 
 ## Task Dependencies and Context
@@ -383,6 +392,7 @@ blog_task = Task(
 Instead of writing custom validation functions, you can use string descriptions that leverage LLM-based validation. When you provide a string to the `guardrail` or `guardrails` parameter, CrewAI automatically creates an `LLMGuardrail` that uses the agent's LLM to validate the output based on your description.
 
 **Requirements**:
+
 - The task must have an `agent` assigned (the guardrail uses the agent's LLM)
 - Provide a clear, descriptive string explaining the validation criteria
 
@@ -399,11 +409,13 @@ blog_task = Task(
 ```
 
 LLM-based guardrails are particularly useful for:
+
 - **Complex validation logic** that's difficult to express programmatically
 - **Subjective criteria** like tone, style, or quality assessments
 - **Natural language requirements** that are easier to describe than code
 
 The LLM guardrail will:
+
 1. Analyze the task output against your description
 2. Return `(True, output)` if the output complies with the criteria
 3. Return `(False, feedback)` with specific feedback if validation fails
@@ -431,6 +443,7 @@ research_task = Task(
 You can apply multiple guardrails to a task using the `guardrails` parameter. Multiple guardrails are executed sequentially, with each guardrail receiving the output from the previous one. This allows you to chain validation and transformation steps.
 
 The `guardrails` parameter accepts:
+
 - A list of guardrail functions or string descriptions
 - A single guardrail function or string (same as `guardrail`)
 
@@ -480,6 +493,7 @@ blog_task = Task(
 ```
 
 In this example, the guardrails execute in order:
+
 1. `validate_word_count` checks the word count
 2. `validate_no_profanity` checks for inappropriate language (using the output from step 1)
 3. `format_output` formats the final result (using the output from step 2)
@@ -522,6 +536,7 @@ This approach combines the precision of programmatic validation with the flexibi
 ### Guardrail Function Requirements
 
 1. **Function Signature**:
+
    - Must accept exactly one parameter (the task output)
    - Should return a tuple of `(bool, Any)`
    - Type hints are recommended but optional
@@ -530,11 +545,10 @@ This approach combines the precision of programmatic validation with the flexibi
    - On success: it returns a tuple of `(bool, Any)`. For example: `(True, validated_result)`
    - On Failure: it returns a tuple of `(bool, str)`. For example: `(False, "Error message explain the failure")`
 
-
-
 ### Error Handling Best Practices
 
 1. **Structured Error Responses**:
+
 ```python Code
 from crewai import TaskOutput, LLMGuardrail
 
@@ -550,11 +564,13 @@ def validate_with_context(result: TaskOutput) -> Tuple[bool, Any]:
 ```
 
 2. **Error Categories**:
+
    - Use specific error codes
    - Include relevant context
    - Provide actionable feedback
 
 3. **Validation Chain**:
+
 ```python Code
 from typing import Any, Dict, List, Tuple, Union
 from crewai import TaskOutput
@@ -581,6 +597,7 @@ def complex_validation(result: TaskOutput) -> Tuple[bool, Any]:
 ### Handling Guardrail Results
 
 When a guardrail returns `(False, error)`:
+
 1. The error is sent back to the agent
 2. The agent attempts to fix the issue
 3. The process repeats until:
@@ -588,6 +605,7 @@ When a guardrail returns `(False, error)`:
    - Maximum retries are reached (`guardrail_max_retries`)
 
 Example with retry handling:
+
 ```python Code
 from typing import Optional, Tuple, Union
 from crewai import TaskOutput, Task
@@ -613,10 +631,12 @@ task = Task(
 ## Getting Structured Consistent Outputs from Tasks
 
 <Note>
-It's also important to note that the output of the final task of a crew becomes the final output of the actual crew itself.
+  It's also important to note that the output of the final task of a crew
+  becomes the final output of the actual crew itself.
 </Note>
 
 ### Using `output_pydantic`
+
 The `output_pydantic` property allows you to define a Pydantic model that the task output should conform to. This ensures that the output is not only structured but also validated according to the Pydantic model.
 
 Here's an example demonstrating how to use output_pydantic:
@@ -686,18 +706,22 @@ print("Accessing Properties - Option 5")
 print("Blog:", result)
 
 ```
+
 In this example:
-* A Pydantic model Blog is defined with title and content fields.
-* The task task1 uses the output_pydantic property to specify that its output should conform to the Blog model.
-* After executing the crew, you can access the structured output in multiple ways as shown.
+
+- A Pydantic model Blog is defined with title and content fields.
+- The task task1 uses the output_pydantic property to specify that its output should conform to the Blog model.
+- After executing the crew, you can access the structured output in multiple ways as shown.
 
 #### Explanation of Accessing the Output
-1. Dictionary-Style Indexing: You can directly access the fields using result["field_name"]. This works because the CrewOutput class implements the __getitem__ method.
+
+1. Dictionary-Style Indexing: You can directly access the fields using result["field_name"]. This works because the CrewOutput class implements the **getitem** method.
 2. Directly from Pydantic Model: Access the attributes directly from the result.pydantic object.
 3. Using to_dict() Method: Convert the output to a dictionary and access the fields.
 4. Printing the Entire Object: Simply print the result object to see the structured output.
 
 ### Using `output_json`
+
 The `output_json` property allows you to define the expected output in JSON format. This ensures that the task's output is a valid JSON structure that can be easily parsed and used in your application.
 
 Here's an example demonstrating how to use `output_json`:
@@ -757,14 +781,15 @@ print("Blog:", result)
 ```
 
 In this example:
-* A Pydantic model Blog is defined with title and content fields, which is used to specify the structure of the JSON output.
-* The task task1 uses the output_json property to indicate that it expects a JSON output conforming to the Blog model.
-* After executing the crew, you can access the structured JSON output in two ways as shown.
+
+- A Pydantic model Blog is defined with title and content fields, which is used to specify the structure of the JSON output.
+- The task task1 uses the output_json property to indicate that it expects a JSON output conforming to the Blog model.
+- After executing the crew, you can access the structured JSON output in two ways as shown.
 
 #### Explanation of Accessing the Output
 
-1. Accessing Properties Using Dictionary-Style Indexing: You can access the fields directly using result["field_name"]. This is possible because the CrewOutput class implements the __getitem__ method, allowing you to treat the output like a dictionary. In this option, we're retrieving the title and content from the result.
-2. Printing the Entire Blog Object: By printing result, you get the string representation of the CrewOutput object. Since the __str__ method is implemented to return the JSON output, this will display the entire output as a formatted string representing the Blog object.
+1. Accessing Properties Using Dictionary-Style Indexing: You can access the fields directly using result["field_name"]. This is possible because the CrewOutput class implements the **getitem** method, allowing you to treat the output like a dictionary. In this option, we're retrieving the title and content from the result.
+2. Printing the Entire Blog Object: By printing result, you get the string representation of the CrewOutput object. Since the **str** method is implemented to return the JSON output, this will display the entire output as a formatted string representing the Blog object.
 
 ---
 
@@ -954,8 +979,6 @@ While creating and executing tasks, certain validation mechanisms are in place t
 
 These validations help in maintaining the consistency and reliability of task executions within the crewAI framework.
 
-
-
 ## Creating Directories when Saving Files
 
 The `create_directory` parameter controls whether CrewAI should automatically create directories when saving task outputs to files. This feature is particularly useful for organizing outputs and ensuring that file paths are correctly structured, especially when working with complex project hierarchies.
@@ -1002,7 +1025,7 @@ analysis_task:
     A comprehensive financial report with quarterly insights
   agent: financial_analyst
   output_file: reports/quarterly/q4_2024_analysis.pdf
-  create_directory: true  # Automatically create 'reports/quarterly/' directory
+  create_directory: true # Automatically create 'reports/quarterly/' directory
 
 audit_task:
   description: >
@@ -1011,18 +1034,20 @@ audit_task:
     A compliance audit report
   agent: auditor
   output_file: audit/compliance_report.md
-  create_directory: false  # Directory must already exist
+  create_directory: false # Directory must already exist
 ```
 
 ### Use Cases
 
 **Automatic Directory Creation (`create_directory=True`):**
+
 - Development and prototyping environments
 - Dynamic report generation with date-based folders
 - Automated workflows where directory structure may vary
 - Multi-tenant applications with user-specific folders
 
 **Manual Directory Management (`create_directory=False`):**
+
 - Production environments with strict file system controls
 - Security-sensitive applications where directories must be pre-configured
 - Systems with specific permission requirements

docs/en/concepts/tools.mdx

@@ -17,9 +17,10 @@ This includes tools from the [CrewAI Toolkit](https://github.com/joaomdmoura/cre
 enabling everything from simple searches to complex interactions and effective teamwork among agents.
 
 <Note type="info" title="Enterprise Enhancement: Tools Repository">
-CrewAI AOP provides a comprehensive Tools Repository with pre-built integrations for common business systems and APIs. Deploy agents with enterprise tools in minutes instead of days.
+CrewAI AMP provides a comprehensive Tools Repository with pre-built integrations for common business systems and APIs. Deploy agents with enterprise tools in minutes instead of days.
 
 The Enterprise Tools Repository includes:
+
 - Pre-built connectors for popular enterprise systems
 - Custom tool creation interface
 - Version control and sharing capabilities

docs/en/enterprise/features/rbac.mdx

@@ -7,10 +7,10 @@ mode: "wide"
 
 ## Overview
 
-RBAC in CrewAI AOP enables secure, scalable access management through a combination of organization‑level roles and automation‑level visibility controls.
+RBAC in CrewAI AMP enables secure, scalable access management through a combination of organization‑level roles and automation‑level visibility controls.
 
 <Frame>
-  <img src="/images/enterprise/users_and_roles.png" alt="RBAC overview in CrewAI AOP" />
+  <img src="/images/enterprise/users_and_roles.png" alt="RBAC overview in CrewAI AMP" />
 
 </Frame>
 
@@ -28,10 +28,11 @@ You can configure users and roles in Settings → Roles.
 
 <Steps>
   <Step title="Open Roles settings">
-    Go to <b>Settings → Roles</b> in CrewAI AOP.
+    Go to <b>Settings → Roles</b> in CrewAI AMP.
   </Step>
   <Step title="Choose a role type">
-    Use a predefined role (<b>Owner</b>, <b>Member</b>) or click <b>Create role</b> to define a custom one.
+    Use a predefined role (<b>Owner</b>, <b>Member</b>) or click{" "}
+    <b>Create role</b> to define a custom one.
   </Step>
   <Step title="Assign to members">
     Select users and assign the role. You can change this anytime.
@@ -40,10 +41,10 @@ You can configure users and roles in Settings → Roles.
 
 ### Configuration summary
 
-| Area | Where to configure | Options |
-|:---|:---|:---|
-| Users & Roles | Settings → Roles | Predefined: Owner, Member; Custom roles |
-| Automation visibility | Automation → Settings → Visibility | Private; Whitelist users/roles |
+| Area                  | Where to configure                 | Options                                 |
+| :-------------------- | :--------------------------------- | :-------------------------------------- |
+| Users & Roles         | Settings → Roles                   | Predefined: Owner, Member; Custom roles |
+| Automation visibility | Automation → Settings → Visibility | Private; Whitelist users/roles          |
 
 ## Automation‑level Access Control
 
@@ -70,30 +71,34 @@ You can configure automation‑level access control in Automation → Settings
     Navigate to <b>Automation → Settings → Visibility</b>.
   </Step>
   <Step title="Set visibility">
-    Choose <b>Private</b> to restrict access. The organization owner always retains access.
+    Choose <b>Private</b> to restrict access. The organization owner always
+    retains access.
   </Step>
   <Step title="Whitelist access">
-    Add specific users and roles allowed to view, run, and access logs/metrics/settings.
+    Add specific users and roles allowed to view, run, and access
+    logs/metrics/settings.
   </Step>
   <Step title="Save and verify">
-    Save changes, then confirm that non‑whitelisted users cannot view or run the automation.
+    Save changes, then confirm that non‑whitelisted users cannot view or run the
+    automation.
   </Step>
 </Steps>
 
 ### Private visibility: access outcomes
 
-| Action | Owner | Whitelisted user/role | Not whitelisted |
-|:---|:---|:---|:---|
-| View automation | ✓ | ✓ | ✗ |
-| Run automation/API | ✓ | ✓ | ✗ |
-| Access logs/metrics/settings | ✓ | ✓ | ✗ |
+| Action                       | Owner | Whitelisted user/role | Not whitelisted |
+| :--------------------------- | :---- | :-------------------- | :-------------- |
+| View automation              | ✓     | ✓                     | ✗               |
+| Run automation/API           | ✓     | ✓                     | ✗               |
+| Access logs/metrics/settings | ✓     | ✓                     | ✗               |
 
 <Tip>
-The organization owner always has access. In private mode, only whitelisted users and roles can view, run, and access logs/metrics/settings.
+  The organization owner always has access. In private mode, only whitelisted
+  users and roles can view, run, and access logs/metrics/settings.
 </Tip>
 
 <Frame>
-  <img src="/images/enterprise/visibility.png" alt="Automation Visibility settings in CrewAI AOP" />
+  <img src="/images/enterprise/visibility.png" alt="Automation Visibility settings in CrewAI AMP" />
 
 </Frame>
 

docs/en/enterprise/features/tools-and-integrations.mdx

@@ -18,222 +18,226 @@ Tools & Integrations is the central hub for connecting third‑party apps and ma
 <Tabs>
   <Tab title="Integrations" icon="plug">
 
-  ## Agent Apps (Integrations)
+## Agent Apps (Integrations)
 
-  Connect enterprise‑grade applications (e.g., Gmail, Google Drive, HubSpot, Slack) via OAuth to enable agent actions.
+Connect enterprise‑grade applications (e.g., Gmail, Google Drive, HubSpot, Slack) via OAuth to enable agent actions.
 
-  <Steps>
-    <Step title="Connect">
-      Click <b>Connect</b> on an app and complete OAuth.
-    </Step>
-    <Step title="Configure">
-      Optionally adjust scopes, triggers, and action availability.
-    </Step>
-    <Step title="Use in Agents">
-      Connected services become available as tools for your agents.
-    </Step>
-  </Steps>
+{" "}
+<Steps>
+  <Step title="Connect">
+    Click <b>Connect</b> on an app and complete OAuth.
+  </Step>
+  <Step title="Configure">
+    Optionally adjust scopes, triggers, and action availability.
+  </Step>
+  <Step title="Use in Agents">
+    Connected services become available as tools for your agents.
+  </Step>
+</Steps>
 
-  <Frame>
-    ![Integrations Grid](/images/enterprise/agent-apps.png)
-  </Frame>
+{" "}
+<Frame>![Integrations Grid](/images/enterprise/agent-apps.png)</Frame>
 
-  ### Connect your Account
+### Connect your Account
 
-  1. Go to <Link href="https://app.crewai.com/crewai_plus/connectors">Integrations</Link>
-  2. Click <b>Connect</b> on the desired service
-  3. Complete the OAuth flow and grant scopes
-  4. Copy your Enterprise Token from <Link href="https://app.crewai.com/crewai_plus/settings/integrations">Integration Settings</Link>
+1. Go to <Link href="https://app.crewai.com/crewai_plus/connectors">Integrations</Link>
+2. Click <b>Connect</b> on the desired service
+3. Complete the OAuth flow and grant scopes
+4. Copy your Enterprise Token from <Link href="https://app.crewai.com/crewai_plus/settings/integrations">Integration Settings</Link>
 
-  <Frame>
-    ![Enterprise Token](/images/enterprise/enterprise_action_auth_token.png)
-  </Frame>
+{" "}
+<Frame>
+  ![Enterprise Token](/images/enterprise/enterprise_action_auth_token.png)
+</Frame>
 
-  ### Install Integration Tools
+### Install Integration Tools
 
-  To use the integrations locally, you need to install the latest `crewai-tools` package.
+To use the integrations locally, you need to install the latest `crewai-tools` package.
 
-  ```bash
-  uv add crewai-tools
-  ```
+```bash
+uv add crewai-tools
+```
 
-  ### Environment Variable Setup
+### Environment Variable Setup
 
-  <Note>
-    To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
-  </Note>
+{" "}
+<Note>
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
+</Note>
 
-  ```bash
-  export CREWAI_PLATFORM_INTEGRATION_TOKEN="your_enterprise_token"
-  ```
+```bash
+export CREWAI_PLATFORM_INTEGRATION_TOKEN="your_enterprise_token"
+```
 
-  Or add it to your `.env` file:
+Or add it to your `.env` file:
 
-  ```
-  CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
-  ```
+```
+CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
+```
 
-  ### Usage Example
+### Usage Example
 
-  <Tip>
-    Use the new streamlined approach to integrate enterprise apps. Simply specify the app and its actions directly in the Agent configuration.
-  </Tip>
+{" "}
+<Tip>
+  Use the new streamlined approach to integrate enterprise apps. Simply specify
+  the app and its actions directly in the Agent configuration.
+</Tip>
 
-  ```python
-  from crewai import Agent, Task, Crew
+```python
+from crewai import Agent, Task, Crew
 
-  # Create an agent with Gmail capabilities
-  email_agent = Agent(
-      role="Email Manager",
-      goal="Manage and organize email communications",
-      backstory="An AI assistant specialized in email management and communication.",
-      apps=['gmail', 'gmail/send_email']  # Using canonical name 'gmail'
-  )
+# Create an agent with Gmail capabilities
+email_agent = Agent(
+    role="Email Manager",
+    goal="Manage and organize email communications",
+    backstory="An AI assistant specialized in email management and communication.",
+    apps=['gmail', 'gmail/send_email']  # Using canonical name 'gmail'
+)
 
-  # Task to send an email
-  email_task = Task(
-      description="Draft and send a follow-up email to john@example.com about the project update",
-      agent=email_agent,
-      expected_output="Confirmation that email was sent successfully"
-  )
+# Task to send an email
+email_task = Task(
+    description="Draft and send a follow-up email to john@example.com about the project update",
+    agent=email_agent,
+    expected_output="Confirmation that email was sent successfully"
+)
 
-  # Run the task
-  crew = Crew(
-      agents=[email_agent],
-      tasks=[email_task]
-  )
+# Run the task
+crew = Crew(
+    agents=[email_agent],
+    tasks=[email_task]
+)
 
-  # Run the crew
-  crew.kickoff()
-  ```
+# Run the crew
+crew.kickoff()
+```
 
-  ### Filtering Tools
+### Filtering Tools
 
-  ```python
-  from crewai import Agent, Task, Crew
+```python
+from crewai import Agent, Task, Crew
 
-  # Create agent with specific Gmail actions only
-  gmail_agent = Agent(
-      role="Gmail Manager",
-      goal="Manage gmail communications and notifications",
-      backstory="An AI assistant that helps coordinate gmail communications.",
-      apps=['gmail/fetch_emails']  # Using canonical name with specific action
-  )
+# Create agent with specific Gmail actions only
+gmail_agent = Agent(
+    role="Gmail Manager",
+    goal="Manage gmail communications and notifications",
+    backstory="An AI assistant that helps coordinate gmail communications.",
+    apps=['gmail/fetch_emails']  # Using canonical name with specific action
+)
 
-  notification_task = Task(
-      description="Find the email from john@example.com",
-      agent=gmail_agent,
-      expected_output="Email found from john@example.com"
-  )
+notification_task = Task(
+    description="Find the email from john@example.com",
+    agent=gmail_agent,
+    expected_output="Email found from john@example.com"
+)
 
-  crew = Crew(
-      agents=[gmail_agent],
-      tasks=[notification_task]
-  )
-  ```
+crew = Crew(
+    agents=[gmail_agent],
+    tasks=[notification_task]
+)
+```
 
-  On a deployed crew, you can specify which actions are available for each integration from the service settings page.
+On a deployed crew, you can specify which actions are available for each integration from the service settings page.
 
-  <Frame>
-    ![Filter Actions](/images/enterprise/filtering_enterprise_action_tools.png)
-  </Frame>
+{" "}
+<Frame>
+  ![Filter Actions](/images/enterprise/filtering_enterprise_action_tools.png)
+</Frame>
 
-  ### Scoped Deployments (multi‑user orgs)
+### Scoped Deployments (multi‑user orgs)
 
-  You can scope each integration to a specific user. For example, a crew that connects to Google can use a specific user’s Gmail account.
+You can scope each integration to a specific user. For example, a crew that connects to Google can use a specific user’s Gmail account.
 
-  <Tip>
-    Useful when different teams/users must keep data access separated.
-  </Tip>
+{" "}
+<Tip>Useful when different teams/users must keep data access separated.</Tip>
 
-  Use the `user_bearer_token` to scope authentication to the requesting user. If the user isn’t logged in, the crew won’t use connected integrations. Otherwise it falls back to the default bearer token configured for the deployment.
+Use the `user_bearer_token` to scope authentication to the requesting user. If the user isn’t logged in, the crew won’t use connected integrations. Otherwise it falls back to the default bearer token configured for the deployment.
 
-  <Frame>
-    ![User Bearer Token](/images/enterprise/user_bearer_token.png)
-  </Frame>
+{" "}
+<Frame>![User Bearer Token](/images/enterprise/user_bearer_token.png)</Frame>
 
-  <div id="catalog"></div>
-  ### Catalog
+{" "}
+<div id="catalog"></div>
+### Catalog
 
-  #### Communication & Collaboration
-  - Gmail — Manage emails and drafts
-  - Slack — Workspace notifications and alerts
-  - Microsoft — Office 365 and Teams integration
+#### Communication & Collaboration
 
-  #### Project Management
-  - Jira — Issue tracking and project management
-  - ClickUp — Task and productivity management
-  - Asana — Team task and project coordination
-  - Notion — Page and database management
-  - Linear — Software project and bug tracking
-  - GitHub — Repository and issue management
+- Gmail — Manage emails and drafts
+- Slack — Workspace notifications and alerts
+- Microsoft — Office 365 and Teams integration
 
-  #### Customer Relationship Management
-  - Salesforce — CRM account and opportunity management
-  - HubSpot — Sales pipeline and contact management
-  - Zendesk — Customer support ticket management
+#### Project Management
 
-  #### Business & Finance
-  - Stripe — Payment processing and customer management
-  - Shopify — E‑commerce store and product management
+- Jira — Issue tracking and project management
+- ClickUp — Task and productivity management
+- Asana — Team task and project coordination
+- Notion — Page and database management
+- Linear — Software project and bug tracking
+- GitHub — Repository and issue management
 
-  #### Productivity & Storage
-  - Google Sheets — Spreadsheet data synchronization
-  - Google Calendar — Event and schedule management
-  - Box — File storage and document management
+#### Customer Relationship Management
 
-  …and more to come!
+- Salesforce — CRM account and opportunity management
+- HubSpot — Sales pipeline and contact management
+- Zendesk — Customer support ticket management
+
+#### Business & Finance
+
+- Stripe — Payment processing and customer management
+- Shopify — E‑commerce store and product management
+
+#### Productivity & Storage
+
+- Google Sheets — Spreadsheet data synchronization
+- Google Calendar — Event and schedule management
+- Box — File storage and document management
+
+…and more to come!
 
   </Tab>
   <Tab title="Internal Tools" icon="toolbox">
 
-  ## Internal Tools
+## Internal Tools
 
-  Create custom tools locally, publish them on CrewAI AOP Tool Repository and use them in your agents.
+Create custom tools locally, publish them on CrewAI AMP Tool Repository and use them in your agents.
 
-  <Tip>
-  Before running the commands below, make sure you log in to your CrewAI AOP account by running this command:
-    ```bash
-    crewai login
-    ```
-  </Tip>
+{" "}
+<Tip>
+  Before running the commands below, make sure you log in to your CrewAI AMP
+  account by running this command: ```bash crewai login ```
+</Tip>
 
-  <Frame>
-    ![Internal Tool Detail](/images/enterprise/tools-integrations-internal.png)
-  </Frame>
+{" "}
+<Frame>
+  ![Internal Tool Detail](/images/enterprise/tools-integrations-internal.png)
+</Frame>
 
-  <Steps>
-    <Step title="Create">
-      Create a new tool locally.
-      ```bash
-      crewai tool create your-tool
-      ```
-    </Step>
-    <Step title="Publish">
-      Publish the tool to the CrewAI AOP Tool Repository.
-      ```bash
-      crewai tool publish
-      ```
-    </Step>
-    <Step title="Install">
-      Install the tool from the CrewAI AOP Tool Repository.
-      ```bash
-      crewai tool install your-tool
-      ```
-    </Step>
-  </Steps>
+{" "}
+<Steps>
+  <Step title="Create">
+    Create a new tool locally. ```bash crewai tool create your-tool ```
+  </Step>
+  <Step title="Publish">
+    Publish the tool to the CrewAI AMP Tool Repository. ```bash crewai tool
+    publish ```
+  </Step>
+  <Step title="Install">
+    Install the tool from the CrewAI AMP Tool Repository. ```bash crewai tool
+    install your-tool ```
+  </Step>
+</Steps>
 
-  Manage:
+Manage:
 
-  - Name and description
-  - Visibility (Private / Public)
-  - Required environment variables
-  - Version history and downloads
-  - Team and role access
+- Name and description
+- Visibility (Private / Public)
+- Required environment variables
+- Version history and downloads
+- Team and role access
 
-  <Frame>
-    ![Internal Tool Detail](/images/enterprise/tool-configs.png)
-  </Frame>
+{" "}
+<Frame>![Internal Tool Detail](/images/enterprise/tool-configs.png)</Frame>
 
   </Tab>
 </Tabs>
@@ -241,10 +245,18 @@ Tools & Integrations is the central hub for connecting third‑party apps and ma
 ## Related
 
 <CardGroup cols={2}>
-  <Card title="Tool Repository" href="/en/enterprise/guides/tool-repository#tool-repository" icon="toolbox">
+  <Card
+    title="Tool Repository"
+    href="/en/enterprise/guides/tool-repository#tool-repository"
+    icon="toolbox"
+  >
     Create, publish, and version custom tools for your organization.
   </Card>
-  <Card title="Webhook Automation" href="/en/enterprise/guides/webhook-automation" icon="bolt">
+  <Card
+    title="Webhook Automation"
+    href="/en/enterprise/guides/webhook-automation"
+    icon="bolt"
+  >
     Automate workflows and integrate with external platforms and services.
   </Card>
 </CardGroup>

docs/en/enterprise/features/traces.mdx

@@ -11,7 +11,7 @@ Traces provide comprehensive visibility into your crew executions, helping you m
 
 ## What are Traces?
 
-Traces in CrewAI AOP are detailed execution records that capture every aspect of your crew's operation, from initial inputs to final outputs. They record:
+Traces in CrewAI AMP are detailed execution records that capture every aspect of your crew's operation, from initial inputs to final outputs. They record:
 
 - Agent thoughts and reasoning
 - Task execution details
@@ -20,15 +20,13 @@ Traces in CrewAI AOP are detailed execution records that capture every aspect of
 - Execution times
 - Cost estimates
 
-<Frame>
-  ![Traces Overview](/images/enterprise/traces-overview.png)
-</Frame>
+<Frame>![Traces Overview](/images/enterprise/traces-overview.png)</Frame>
 
 ## Accessing Traces
 
 <Steps>
   <Step title="Navigate to the Traces Tab">
-    Once in your CrewAI AOP dashboard, click on the **Traces** to view all execution records.
+    Once in your CrewAI AMP dashboard, click on the **Traces** to view all execution records.
   </Step>
 
   <Step title="Select an Execution">
@@ -51,9 +49,7 @@ The top section displays high-level metrics about the execution:
 - **Execution Time**: Total duration of the crew run
 - **Estimated Cost**: Approximate cost based on token usage
 
-<Frame>
-  ![Execution Summary](/images/enterprise/trace-summary.png)
-</Frame>
+<Frame>![Execution Summary](/images/enterprise/trace-summary.png)</Frame>
 
 ### 2. Tasks & Agents
 
@@ -64,33 +60,25 @@ This section shows all tasks and agents that were part of the crew execution:
 - Status (completed/failed)
 - Individual execution time of the task
 
-<Frame>
-  ![Task List](/images/enterprise/trace-tasks.png)
-</Frame>
+<Frame>![Task List](/images/enterprise/trace-tasks.png)</Frame>
 
 ### 3. Final Output
 
 Displays the final result produced by the crew after all tasks are completed.
 
-<Frame>
-  ![Final Output](/images/enterprise/final-output.png)
-</Frame>
+<Frame>![Final Output](/images/enterprise/final-output.png)</Frame>
 
 ### 4. Execution Timeline
 
 A visual representation of when each task started and ended, helping you identify bottlenecks or parallel execution patterns.
 
-<Frame>
-  ![Execution Timeline](/images/enterprise/trace-timeline.png)
-</Frame>
+<Frame>![Execution Timeline](/images/enterprise/trace-timeline.png)</Frame>
 
 ### 5. Detailed Task View
 
 When you click on a specific task in the timeline or task list, you'll see:
 
-<Frame>
-  ![Detailed Task View](/images/enterprise/trace-detailed-task.png)
-</Frame>
+<Frame>![Detailed Task View](/images/enterprise/trace-detailed-task.png)</Frame>
 
 - **Task Key**: Unique identifier for the task
 - **Task ID**: Technical identifier in the system
@@ -104,7 +92,6 @@ When you click on a specific task in the timeline or task list, you'll see:
 - **Input**: Any input provided to this task from previous tasks
 - **Output**: The actual result produced by the agent
 
-
 ## Using Traces for Debugging
 
 Traces are invaluable for troubleshooting issues with your crews:
@@ -121,6 +108,7 @@ Traces are invaluable for troubleshooting issues with your crews:
     <Frame>
       ![Failure Points](/images/enterprise/failure.png)
     </Frame>
+
   </Step>
 
   <Step title="Optimize Performance">
@@ -130,6 +118,7 @@ Traces are invaluable for troubleshooting issues with your crews:
     - Excessive token usage
     - Redundant tool operations
     - Unnecessary API calls
+
   </Step>
 
   <Step title="Improve Cost Efficiency">
@@ -139,6 +128,7 @@ Traces are invaluable for troubleshooting issues with your crews:
     - Refine prompts to be more concise
     - Cache frequently accessed information
     - Structure tasks to minimize redundant operations
+
   </Step>
 </Steps>
 
@@ -153,5 +143,6 @@ CrewAI batches trace uploads to reduce overhead on high-volume runs:
 This yields more stable tracing under load while preserving detailed task/agent telemetry.
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with trace analysis or any other CrewAI AOP features.
+  Contact our support team for assistance with trace analysis or any other
+  CrewAI AMP features.
 </Card>

docs/en/enterprise/features/webhook-streaming.mdx

@@ -8,7 +8,7 @@ mode: "wide"
 ## Overview
 
 Enterprise Event Streaming lets you receive real-time webhook updates about your crews and flows deployed to
-CrewAI AOP, such as model calls, tool usage, and flow steps.
+CrewAI AMP, such as model calls, tool usage, and flow steps.
 
 ## Usage
 
@@ -16,7 +16,7 @@ When using the Kickoff API, include a `webhooks` object to your request, for exa
 
 ```json
 {
-  "inputs": {"foo": "bar"},
+  "inputs": { "foo": "bar" },
   "webhooks": {
     "events": ["crew_kickoff_started", "llm_call_started"],
     "url": "https://your.endpoint/webhook",
@@ -46,8 +46,8 @@ Each webhook sends a list of events:
       "data": {
         "model": "gpt-4",
         "messages": [
-          {"role": "system", "content": "You are an assistant."},
-          {"role": "user", "content": "Summarize this article."}
+          { "role": "system", "content": "You are an assistant." },
+          { "role": "user", "content": "Summarize this article." }
         ]
       }
     }
@@ -65,104 +65,109 @@ CrewAI supports both system events and custom events in Enterprise Event Streami
 
 ### Flow Events:
 
-  - `flow_created`
-  - `flow_started`
-  - `flow_finished`
-  - `flow_plot`
-  - `method_execution_started`
-  - `method_execution_finished`
-  - `method_execution_failed`
+- `flow_created`
+- `flow_started`
+- `flow_finished`
+- `flow_plot`
+- `method_execution_started`
+- `method_execution_finished`
+- `method_execution_failed`
 
 ### Agent Events:
 
-  - `agent_execution_started`
-  - `agent_execution_completed`
-  - `agent_execution_error`
-  - `lite_agent_execution_started`
-  - `lite_agent_execution_completed`
-  - `lite_agent_execution_error`
-  - `agent_logs_started`
-  - `agent_logs_execution`
-  - `agent_evaluation_started`
-  - `agent_evaluation_completed`
-  - `agent_evaluation_failed`
+- `agent_execution_started`
+- `agent_execution_completed`
+- `agent_execution_error`
+- `lite_agent_execution_started`
+- `lite_agent_execution_completed`
+- `lite_agent_execution_error`
+- `agent_logs_started`
+- `agent_logs_execution`
+- `agent_evaluation_started`
+- `agent_evaluation_completed`
+- `agent_evaluation_failed`
 
 ### Crew Events:
 
-  - `crew_kickoff_started`
-  - `crew_kickoff_completed`
-  - `crew_kickoff_failed`
-  - `crew_train_started`
-  - `crew_train_completed`
-  - `crew_train_failed`
-  - `crew_test_started`
-  - `crew_test_completed`
-  - `crew_test_failed`
-  - `crew_test_result`
+- `crew_kickoff_started`
+- `crew_kickoff_completed`
+- `crew_kickoff_failed`
+- `crew_train_started`
+- `crew_train_completed`
+- `crew_train_failed`
+- `crew_test_started`
+- `crew_test_completed`
+- `crew_test_failed`
+- `crew_test_result`
 
 ### Task Events:
 
-  - `task_started`
-  - `task_completed`
-  - `task_failed`
-  - `task_evaluation`
+- `task_started`
+- `task_completed`
+- `task_failed`
+- `task_evaluation`
 
 ### Tool Usage Events:
 
-  - `tool_usage_started`
-  - `tool_usage_finished`
-  - `tool_usage_error`
-  - `tool_validate_input_error`
-  - `tool_selection_error`
-  - `tool_execution_error`
+- `tool_usage_started`
+- `tool_usage_finished`
+- `tool_usage_error`
+- `tool_validate_input_error`
+- `tool_selection_error`
+- `tool_execution_error`
 
 ### LLM Events:
 
-  - `llm_call_started`
-  - `llm_call_completed`
-  - `llm_call_failed`
-  - `llm_stream_chunk`
+- `llm_call_started`
+- `llm_call_completed`
+- `llm_call_failed`
+- `llm_stream_chunk`
 
 ### LLM Guardrail Events:
 
-  - `llm_guardrail_started`
-  - `llm_guardrail_completed`
+- `llm_guardrail_started`
+- `llm_guardrail_completed`
 
 ### Memory Events:
 
-  - `memory_query_started`
-  - `memory_query_completed`
-  - `memory_query_failed`
-  - `memory_save_started`
-  - `memory_save_completed`
-  - `memory_save_failed`
-  - `memory_retrieval_started`
-  - `memory_retrieval_completed`
+- `memory_query_started`
+- `memory_query_completed`
+- `memory_query_failed`
+- `memory_save_started`
+- `memory_save_completed`
+- `memory_save_failed`
+- `memory_retrieval_started`
+- `memory_retrieval_completed`
 
 ### Knowledge Events:
 
-  - `knowledge_search_query_started`
-  - `knowledge_search_query_completed`
-  - `knowledge_search_query_failed`
-  - `knowledge_query_started`
-  - `knowledge_query_completed`
-  - `knowledge_query_failed`
+- `knowledge_search_query_started`
+- `knowledge_search_query_completed`
+- `knowledge_search_query_failed`
+- `knowledge_query_started`
+- `knowledge_query_completed`
+- `knowledge_query_failed`
 
 ### Reasoning Events:
 
-  - `agent_reasoning_started`
-  - `agent_reasoning_completed`
-  - `agent_reasoning_failed`
+- `agent_reasoning_started`
+- `agent_reasoning_completed`
+- `agent_reasoning_failed`
 
 Event names match the internal event bus. See GitHub for the full list of events.
 
 You can emit your own custom events, and they will be delivered through the webhook stream alongside system events.
 
 <CardGroup>
- <Card title="GitHub" icon="github" href="https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events">
-  Full list of events
- </Card>
-<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with webhook integration or troubleshooting.
-</Card>
+  <Card
+    title="GitHub"
+    icon="github"
+    href="https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events"
+  >
+    Full list of events
+  </Card>
+  <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+    Contact our support team for assistance with webhook integration or
+    troubleshooting.
+  </Card>
 </CardGroup>

docs/en/enterprise/guides/automation-triggers.mdx

@@ -1,11 +1,11 @@
 ---
 title: "Triggers Overview"
-description: "Understand how CrewAI AOP triggers work, how to manage them, and where to find integration-specific playbooks"
+description: "Understand how CrewAI AMP triggers work, how to manage them, and where to find integration-specific playbooks"
 icon: "face-smile"
 mode: "wide"
 ---
 
-CrewAI AOP triggers connect your automations to real-time events across the tools your teams already use. Instead of polling systems or relying on manual kickoffs, triggers listen for changes—new emails, calendar updates, CRM status changes—and immediately launch the crew or flow you specify.
+CrewAI AMP triggers connect your automations to real-time events across the tools your teams already use. Instead of polling systems or relying on manual kickoffs, triggers listen for changes—new emails, calendar updates, CRM status changes—and immediately launch the crew or flow you specify.
 
 <Frame>
   ![Automation Triggers Overview](/images/enterprise/crew_connectors.png)
@@ -20,37 +20,61 @@ Deep-dive guides walk through setup and sample workflows for each integration:
     <a href="/en/enterprise/guides/gmail-trigger">Enable crews when emails arrive or threads update.</a>
   </Card>
 
-  <Card title="Google Calendar Trigger" icon="calendar-days">
-    <a href="/en/enterprise/guides/google-calendar-trigger">React to calendar events as they are created, updated, or cancelled.</a>
-  </Card>
+{" "}
+<Card title="Google Calendar Trigger" icon="calendar-days">
+  <a href="/en/enterprise/guides/google-calendar-trigger">
+    React to calendar events as they are created, updated, or cancelled.
+  </a>
+</Card>
 
-  <Card title="Google Drive Trigger" icon="folder-open">
-    <a href="/en/enterprise/guides/google-drive-trigger">Handle Drive file uploads, edits, and deletions.</a>
-  </Card>
+{" "}
+<Card title="Google Drive Trigger" icon="folder-open">
+  <a href="/en/enterprise/guides/google-drive-trigger">
+    Handle Drive file uploads, edits, and deletions.
+  </a>
+</Card>
 
-  <Card title="Outlook Trigger" icon="envelope-open">
-    <a href="/en/enterprise/guides/outlook-trigger">Automate responses to new Outlook messages and calendar updates.</a>
-  </Card>
+{" "}
+<Card title="Outlook Trigger" icon="envelope-open">
+  <a href="/en/enterprise/guides/outlook-trigger">
+    Automate responses to new Outlook messages and calendar updates.
+  </a>
+</Card>
 
-  <Card title="OneDrive Trigger" icon="cloud">
-    <a href="/en/enterprise/guides/onedrive-trigger">Audit file activity and sharing changes in OneDrive.</a>
-  </Card>
+{" "}
+<Card title="OneDrive Trigger" icon="cloud">
+  <a href="/en/enterprise/guides/onedrive-trigger">
+    Audit file activity and sharing changes in OneDrive.
+  </a>
+</Card>
 
-  <Card title="Microsoft Teams Trigger" icon="comments">
-    <a href="/en/enterprise/guides/microsoft-teams-trigger">Kick off workflows when new Teams chats start.</a>
-  </Card>
+{" "}
+<Card title="Microsoft Teams Trigger" icon="comments">
+  <a href="/en/enterprise/guides/microsoft-teams-trigger">
+    Kick off workflows when new Teams chats start.
+  </a>
+</Card>
 
-  <Card title="HubSpot Trigger" icon="hubspot">
-    <a href="/en/enterprise/guides/hubspot-trigger">Launch automations from HubSpot workflows and lifecycle events.</a>
-  </Card>
+{" "}
+<Card title="HubSpot Trigger" icon="hubspot">
+  <a href="/en/enterprise/guides/hubspot-trigger">
+    Launch automations from HubSpot workflows and lifecycle events.
+  </a>
+</Card>
 
-  <Card title="Salesforce Trigger" icon="salesforce">
-    <a href="/en/enterprise/guides/salesforce-trigger">Connect Salesforce processes to CrewAI for CRM automation.</a>
-  </Card>
+{" "}
+<Card title="Salesforce Trigger" icon="salesforce">
+  <a href="/en/enterprise/guides/salesforce-trigger">
+    Connect Salesforce processes to CrewAI for CRM automation.
+  </a>
+</Card>
 
-  <Card title="Slack Trigger" icon="slack">
-    <a href="/en/enterprise/guides/slack-trigger">Start crews directly from Slack slash commands.</a>
-  </Card>
+{" "}
+<Card title="Slack Trigger" icon="slack">
+  <a href="/en/enterprise/guides/slack-trigger">
+    Start crews directly from Slack slash commands.
+  </a>
+</Card>
 
   <Card title="Zapier Trigger" icon="bolt">
     <a href="/en/enterprise/guides/zapier-trigger">Bridge CrewAI with thousands of Zapier-supported apps.</a>
@@ -76,7 +100,10 @@ To access and manage your automation triggers:
 2. Click on the **Triggers** tab to view all available trigger integrations
 
 <Frame caption="Example of available automation triggers for a Gmail deployment">
-  <img src="/images/enterprise/list-available-triggers.png" alt="List of available automation triggers" />
+  <img
+    src="/images/enterprise/list-available-triggers.png"
+    alt="List of available automation triggers"
+  />
 </Frame>
 
 This view shows all the trigger integrations available for your deployment, along with their current connection status.
@@ -86,7 +113,10 @@ This view shows all the trigger integrations available for your deployment, alon
 Each trigger can be easily enabled or disabled using the toggle switch:
 
 <Frame caption="Enable or disable triggers with toggle">
-  <img src="/images/enterprise/trigger-selected.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/trigger-selected.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 - **Enabled (blue toggle)**: The trigger is active and will automatically execute your deployment when the specified events occur
@@ -99,7 +129,10 @@ Simply click the toggle to change the trigger state. Changes take effect immedia
 Track the performance and history of your triggered executions:
 
 <Frame caption="List of executions triggered by automation">
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+  <img
+    src="/images/enterprise/list-executions.png"
+    alt="List of executions triggered by automation"
+  />
 </Frame>
 
 ## Building Trigger-Driven Automations
@@ -130,6 +163,7 @@ crewai triggers list
 ```
 
 This command displays all triggers available based on your connected integrations, showing:
+
 - Integration name and connection status
 - Available trigger types
 - Trigger names and descriptions
@@ -149,6 +183,7 @@ crewai triggers run microsoft_onedrive/file_changed
 ```
 
 This command:
+
 - Executes your crew locally
 - Passes a complete, realistic trigger payload
 - Simulates exactly how your crew will be called in production
@@ -161,7 +196,6 @@ This command:
   - If your crew expects parameters that aren't in the trigger payload, execution may fail
 </Warning>
 
-
 ### Triggers with Crew
 
 Your existing crew definitions work seamlessly with triggers, you just need to have a task to parse the received payload:
@@ -193,10 +227,12 @@ class MyAutomatedCrew:
 The crew will automatically receive and can access the trigger payload through the standard CrewAI context mechanisms.
 
 <Note>
-  Crew and Flow inputs can include `crewai_trigger_payload`. CrewAI automatically injects this payload:
-  - Tasks: appended to the first task's description by default ("Trigger Payload: {crewai_trigger_payload}")
-  - Control via `allow_crewai_trigger_context`: set `True` to always inject, `False` to never inject
-  - Flows: any `@start()` method that accepts a `crewai_trigger_payload` parameter will receive it
+  Crew and Flow inputs can include `crewai_trigger_payload`. CrewAI
+  automatically injects this payload: - Tasks: appended to the first task's
+  description by default ("Trigger Payload: {crewai_trigger_payload}") - Control
+  via `allow_crewai_trigger_context`: set `True` to always inject, `False` to
+  never inject - Flows: any `@start()` method that accepts a
+  `crewai_trigger_payload` parameter will receive it
 </Note>
 
 ### Integration with Flows
@@ -264,17 +300,20 @@ def delegate_to_crew(self, crewai_trigger_payload: dict = None):
 ## Troubleshooting
 
 **Trigger not firing:**
+
 - Verify the trigger is enabled in your deployment's Triggers tab
 - Check integration connection status under Tools & Integrations
 - Ensure all required environment variables are properly configured
 
 **Execution failures:**
+
 - Check the execution logs for error details
 - Use `crewai triggers run <trigger_name>` to test locally and see the exact payload structure
 - Verify your crew can handle the `crewai_trigger_payload` parameter
 - Ensure your crew doesn't expect parameters that aren't included in the trigger payload
 
 **Development issues:**
+
 - Always test with `crewai triggers run <trigger>` before deploying to see the complete payload
 - Remember that `crewai run` does NOT simulate trigger calls—use `crewai triggers run` instead
 - Use `crewai triggers list` to verify which triggers are available for your connected integrations

docs/en/enterprise/guides/azure-openai-setup.mdx

@@ -19,8 +19,8 @@ This guide walks you through connecting Azure OpenAI with Crew Studio for seamle
             </Frame>
     </Step>
 
-    <Step title="Configure CrewAI AOP Connection">
-        4. In another tab, open `CrewAI AOP > LLM Connections`. Name your LLM Connection, select Azure as the provider, and choose the same model you selected in Azure.
+    <Step title="Configure CrewAI AMP Connection">
+        4. In another tab, open `CrewAI AMP > LLM Connections`. Name your LLM Connection, select Azure as the provider, and choose the same model you selected in Azure.
         5. On the same page, add environment variables from step 3:
             - One named `AZURE_DEPLOYMENT_TARGET_URL` (using the Target URI). The URL should look like this: https://your-deployment.openai.azure.com/openai/deployments/gpt-4o/chat/completions?api-version=2024-08-01-preview
             - Another named `AZURE_API_KEY` (using the Key).
@@ -28,7 +28,7 @@ This guide walks you through connecting Azure OpenAI with Crew Studio for seamle
     </Step>
 
     <Step title="Set Default Configuration">
-        7. In `CrewAI AOP > Settings > Defaults > Crew Studio LLM Settings`, set the new LLM Connection and model as defaults.
+        7. In `CrewAI AMP > Settings > Defaults > Crew Studio LLM Settings`, set the new LLM Connection and model as defaults.
     </Step>
 
     <Step title="Configure Network Access">
@@ -37,6 +37,7 @@ This guide walks you through connecting Azure OpenAI with Crew Studio for seamle
             - Navigate to `Resource Management > Networking`.
             - Ensure that `Allow access from all networks` is enabled. If this setting is restricted, CrewAI may be blocked from accessing your Azure OpenAI endpoint.
     </Step>
+
 </Steps>
 
 ## Verification
@@ -46,6 +47,7 @@ You're all set! Crew Studio will now use your Azure OpenAI connection. Test the
 ## Troubleshooting
 
 If you encounter issues:
+
 - Verify the Target URI format matches the expected pattern
 - Check that the API key is correct and has proper permissions
 - Ensure network access is configured to allow CrewAI connections

docs/en/enterprise/guides/build-crew.mdx

@@ -7,7 +7,7 @@ mode: "wide"
 
 ## Overview
 
-[CrewAI AOP](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
+[CrewAI AMP](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
 
 ## Getting Started
 
@@ -22,21 +22,27 @@ mode: "wide"
 
 ### Installation and Setup
 
-<Card title="Follow Standard Installation" icon="wrench" href="/en/installation">
-  Follow our standard installation guide to set up CrewAI CLI and create your first project.
+<Card
+  title="Follow Standard Installation"
+  icon="wrench"
+  href="/en/installation"
+>
+  Follow our standard installation guide to set up CrewAI CLI and create your
+  first project.
 </Card>
 
 ### Building Your Crew
 
 <Card title="Quickstart Tutorial" icon="rocket" href="/en/quickstart">
-  Follow our quickstart guide to create your first agent crew using YAML configuration.
+  Follow our quickstart guide to create your first agent crew using YAML
+  configuration.
 </Card>
 
 ## Support and Resources
 
 For Enterprise-specific support or questions, contact our dedicated support team at [support@crewai.com](mailto:support@crewai.com).
 
-
 <Card title="Schedule a Demo" icon="calendar" href="mailto:support@crewai.com">
-  Book time with our team to learn more about Enterprise features and how they can benefit your organization.
+  Book time with our team to learn more about Enterprise features and how they
+  can benefit your organization.
 </Card>

docs/en/enterprise/guides/capture_telemetry_logs.mdx

@@ -1,11 +1,11 @@
 ---
 title: "Open Telemetry Logs"
-description: "Understand how to capture telemetry logs from your CrewAI AOP deployments"
+description: "Understand how to capture telemetry logs from your CrewAI AMP deployments"
 icon: "magnifying-glass-chart"
 mode: "wide"
 ---
 
-CrewAI AOP provides a powerful way to capture telemetry logs from your deployments. This allows you to monitor the performance of your agents and workflows, and to debug issues that may arise.
+CrewAI AMP provides a powerful way to capture telemetry logs from your deployments. This allows you to monitor the performance of your agents and workflows, and to debug issues that may arise.
 
 ## Prerequisites
 
@@ -14,22 +14,17 @@ CrewAI AOP provides a powerful way to capture telemetry logs from your deploymen
     Your organization should have ENTERPRISE OTEL SETUP enabled
   </Card>
   <Card title="OTEL collector setup" icon="server">
-    Your organization should have an OTEL collector setup or a provider like Datadog log intake setup
+    Your organization should have an OTEL collector setup or a provider like
+    Datadog log intake setup
   </Card>
 </CardGroup>
 
-
 ## How to capture telemetry logs
 
 1. Go to settings/organization tab
 2. Configure your OTEL collector setup
 3. Save
 
-
-
 Example to setup OTEL log collection capture to Datadog.
 
-
-<Frame>
-  ![Capture Telemetry Logs](/images/crewai-otel-export.png)
-</Frame>
+<Frame>![Capture Telemetry Logs](/images/crewai-otel-export.png)</Frame>

docs/en/enterprise/guides/deploy-crew.mdx

@@ -1,22 +1,26 @@
 ---
 title: "Deploy Crew"
-description: "Deploying a Crew on CrewAI AOP"
+description: "Deploying a Crew on CrewAI AMP"
 icon: "rocket"
 mode: "wide"
 ---
 
 <Note>
-After creating a crew locally or through Crew Studio, the next step is deploying it to the CrewAI AOP platform. This guide covers multiple deployment methods to help you choose the best approach for your workflow.
+  After creating a crew locally or through Crew Studio, the next step is
+  deploying it to the CrewAI AMP platform. This guide covers multiple deployment
+  methods to help you choose the best approach for your workflow.
 </Note>
 
 ## Prerequisites
 
 <CardGroup cols={2}>
   <Card title="Crew Ready for Deployment" icon="users">
-    You should have a working crew either built locally or created through Crew Studio
+    You should have a working crew either built locally or created through Crew
+    Studio
   </Card>
   <Card title="GitHub Repository" icon="github">
-    Your crew code should be in a GitHub repository (for GitHub integration method)
+    Your crew code should be in a GitHub repository (for GitHub integration
+    method)
   </Card>
 </CardGroup>
 
@@ -39,10 +43,10 @@ The CLI provides the fastest way to deploy locally developed crews to the Enterp
   </Step>
 
   <Step title="Authenticate with the Enterprise Platform">
-    First, you need to authenticate your CLI with the CrewAI AOP platform:
+    First, you need to authenticate your CLI with the CrewAI AMP platform:
 
     ```bash
-    # If you already have a CrewAI AOP account, or want to create one:
+    # If you already have a CrewAI AMP account, or want to create one:
     crewai login
     ```
 
@@ -105,38 +109,38 @@ The CLI provides the fastest way to deploy locally developed crews to the Enterp
 
 The CrewAI CLI offers several commands to manage your deployments:
 
-  ```bash
-  # List all your deployments
-  crewai deploy list
+```bash
+# List all your deployments
+crewai deploy list
 
-  # Get the status of your deployment
-  crewai deploy status
+# Get the status of your deployment
+crewai deploy status
 
-  # View the logs of your deployment
-  crewai deploy logs
+# View the logs of your deployment
+crewai deploy logs
 
-  # Push updates after code changes
-  crewai deploy push
+# Push updates after code changes
+crewai deploy push
 
-  # Remove a deployment
-  crewai deploy remove <deployment_id>
-  ```
+# Remove a deployment
+crewai deploy remove <deployment_id>
+```
 
 ## Option 2: Deploy Directly via Web Interface
 
-You can also deploy your crews directly through the CrewAI AOP web interface by connecting your GitHub account. This approach doesn't require using the CLI on your local machine.
+You can also deploy your crews directly through the CrewAI AMP web interface by connecting your GitHub account. This approach doesn't require using the CLI on your local machine.
 
 <Steps>
 
   <Step title="Pushing to GitHub">
 
-  You need to push your crew to a GitHub repository. If you haven't created a crew yet, you can [follow this tutorial](/en/quickstart).
+You need to push your crew to a GitHub repository. If you haven't created a crew yet, you can [follow this tutorial](/en/quickstart).
 
   </Step>
 
-  <Step title="Connecting GitHub to CrewAI AOP">
+  <Step title="Connecting GitHub to CrewAI AMP">
 
-    1. Log in to [CrewAI AOP](https://app.crewai.com)
+    1. Log in to [CrewAI AMP](https://app.crewai.com)
     2. Click on the button "Connect GitHub"
 
     <Frame>
@@ -194,7 +198,7 @@ For automated deployments in CI/CD pipelines, you can use the CrewAI API to trig
 <Steps>
   <Step title="Get Your Personal Access Token">
 
-    Navigate to your CrewAI AOP account settings to generate an API token:
+    Navigate to your CrewAI AMP account settings to generate an API token:
 
     1. Go to [app.crewai.com](https://app.crewai.com)
     2. Click on **Settings** → **Account** → **Personal Access Token**
@@ -207,7 +211,7 @@ For automated deployments in CI/CD pipelines, you can use the CrewAI API to trig
 
     Locate the unique identifier for your deployed crew:
 
-    1. Go to **Automations** in your CrewAI AOP dashboard
+    1. Go to **Automations** in your CrewAI AMP dashboard
     2. Select your existing automation/crew
     3. Click on **Additional Details**
     4. Copy the **UUID** - this identifies your specific crew deployment
@@ -238,7 +242,6 @@ For automated deployments in CI/CD pipelines, you can use the CrewAI API to trig
     If your automation was first created connected to Git, the API will automatically pull the latest changes from your repository before redeploying.
     </Info>
 
-
   </Step>
 
   <Step title="GitHub Actions Integration Example">
@@ -276,12 +279,14 @@ For automated deployments in CI/CD pipelines, you can use the CrewAI API to trig
     </Tip>
 
     </Step>
+
   </Steps>
 
 ## ⚠️ Environment Variable Security Requirements
 
 <Warning>
-**Important**: CrewAI AOP has security restrictions on environment variable names that can cause deployment failures if not followed.
+  **Important**: CrewAI AMP has security restrictions on environment variable
+  names that can cause deployment failures if not followed.
 </Warning>
 
 ### Blocked Environment Variable Patterns
@@ -289,12 +294,14 @@ For automated deployments in CI/CD pipelines, you can use the CrewAI API to trig
 For security reasons, the following environment variable naming patterns are **automatically filtered** and will cause deployment issues:
 
 **Blocked Patterns:**
+
 - Variables ending with `_TOKEN` (e.g., `MY_API_TOKEN`)
 - Variables ending with `_PASSWORD` (e.g., `DB_PASSWORD`)
 - Variables ending with `_SECRET` (e.g., `API_SECRET`)
 - Variables ending with `_KEY` in certain contexts
 
 **Specific Blocked Variables:**
+
 - `GITHUB_USER`, `GITHUB_TOKEN`
 - `AWS_REGION`, `AWS_DEFAULT_REGION`
 - Various internal CrewAI system variables
@@ -302,6 +309,7 @@ For security reasons, the following environment variable naming patterns are **a
 ### Allowed Exceptions
 
 Some variables are explicitly allowed despite matching blocked patterns:
+
 - `AZURE_AD_TOKEN`
 - `AZURE_OPENAI_AD_TOKEN`
 - `ENTERPRISE_ACTION_TOKEN`
@@ -331,7 +339,8 @@ API_CONFIG=secret123
 4. **Document changes**: Keep track of renamed variables for your team
 
 <Tip>
-If you encounter deployment failures with cryptic environment variable errors, check your variable names against these patterns first.
+  If you encounter deployment failures with cryptic environment variable errors,
+  check your variable names against these patterns first.
 </Tip>
 
 ### Interact with Your Deployed Crew
@@ -339,6 +348,7 @@ If you encounter deployment failures with cryptic environment variable errors, c
 Once deployment is complete, you can access your crew through:
 
 1. **REST API**: The platform generates a unique HTTPS endpoint with these key routes:
+
    - `/inputs`: Lists the required input parameters
    - `/kickoff`: Initiates an execution with provided inputs
    - `/status/{kickoff_id}`: Checks the execution status
@@ -378,5 +388,6 @@ The Enterprise platform also offers:
 - **Crew Studio**: Build crews through a chat interface without writing code
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with deployment issues or questions about the Enterprise platform.
+  Contact our support team for assistance with deployment issues or questions
+  about the Enterprise platform.
 </Card>

docs/en/enterprise/guides/enable-crew-studio.mdx

@@ -1,12 +1,13 @@
 ---
 title: "Enable Crew Studio"
-description: "Enabling Crew Studio on CrewAI AOP"
+description: "Enabling Crew Studio on CrewAI AMP"
 icon: "comments"
 mode: "wide"
 ---
 
 <Tip>
-Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly scaffold or build Crews through a conversational interface.
+  Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly
+  scaffold or build Crews through a conversational interface.
 </Tip>
 
 ## What is Crew Studio?
@@ -24,7 +25,7 @@ With Crew Studio, you can:
 - Select appropriate tools
 - Configure necessary inputs
 - Generate downloadable code for customization
-- Deploy directly to the CrewAI AOP platform
+- Deploy directly to the CrewAI AMP platform
 
 ## Configuration Steps
 
@@ -32,7 +33,7 @@ Before you can start using Crew Studio, you need to configure your LLM connectio
 
 <Steps>
   <Step title="Set Up LLM Connection">
-    Go to the **LLM Connections** tab in your CrewAI AOP dashboard and create a new LLM connection.
+    Go to the **LLM Connections** tab in your CrewAI AMP dashboard and create a new LLM connection.
 
     <Note>
       Feel free to use any LLM provider you want that is supported by CrewAI.
@@ -52,6 +53,7 @@ Before you can start using Crew Studio, you need to configure your LLM connectio
     <Frame>
       ![LLM Connection Configuration](/images/enterprise/llm-connection-config.png)
     </Frame>
+
   </Step>
 
   <Step title="Verify Connection Added">
@@ -60,6 +62,7 @@ Before you can start using Crew Studio, you need to configure your LLM connectio
     <Frame>
       ![Connection Added](/images/enterprise/connection-added.png)
     </Frame>
+
   </Step>
 
   <Step title="Configure LLM Defaults">
@@ -73,6 +76,7 @@ Before you can start using Crew Studio, you need to configure your LLM connectio
     <Frame>
       ![LLM Defaults Configuration](/images/enterprise/llm-defaults.png)
     </Frame>
+
   </Step>
 </Steps>
 
@@ -82,7 +86,7 @@ Now that you've configured your LLM connection and default settings, you're read
 
 <Steps>
   <Step title="Access Studio">
-    Navigate to the **Studio** section in your CrewAI AOP dashboard.
+    Navigate to the **Studio** section in your CrewAI AMP dashboard.
   </Step>
 
   <Step title="Start a Conversation">
@@ -93,6 +97,7 @@ Now that you've configured your LLM connection and default settings, you're read
     ```
 
     The Crew Assistant will ask clarifying questions to better understand your requirements.
+
   </Step>
 
   <Step title="Review Generated Crew">
@@ -104,14 +109,16 @@ Now that you've configured your LLM connection and default settings, you're read
     - Tools to be used
 
     This is your opportunity to refine the configuration before proceeding.
+
   </Step>
 
   <Step title="Deploy or Download">
     Once you're satisfied with the configuration, you can:
 
     - Download the generated code for local customization
-    - Deploy the crew directly to the CrewAI AOP platform
+    - Deploy the crew directly to the CrewAI AMP platform
     - Modify the configuration and regenerate the crew
+
   </Step>
 
   <Step title="Test Your Crew">
@@ -120,7 +127,9 @@ Now that you've configured your LLM connection and default settings, you're read
 </Steps>
 
 <Tip>
-For best results, provide clear, detailed descriptions of what you want your crew to accomplish. Include specific inputs and expected outputs in your description.
+  For best results, provide clear, detailed descriptions of what you want your
+  crew to accomplish. Include specific inputs and expected outputs in your
+  description.
 </Tip>
 
 ## Example Workflow
@@ -134,11 +143,14 @@ Here's a typical workflow for creating a crew with Crew Studio:
     ```md
     I need a crew that can analyze financial news and provide investment recommendations
     ```
+
   </Step>
 
-  <Step title="Answer Questions">
-    Respond to clarifying questions from the Crew Assistant to refine your requirements.
-  </Step>
+{" "}
+<Step title="Answer Questions">
+  Respond to clarifying questions from the Crew Assistant to refine your
+  requirements.
+</Step>
 
   <Step title="Review the Plan">
     Review the generated crew plan, which might include:
@@ -146,15 +158,18 @@ Here's a typical workflow for creating a crew with Crew Studio:
     - A Research Agent to gather financial news
     - An Analysis Agent to interpret the data
     - A Recommendations Agent to provide investment advice
+
   </Step>
 
-  <Step title="Approve or Modify">
-    Approve the plan or request changes if necessary.
-  </Step>
+{" "}
+<Step title="Approve or Modify">
+  Approve the plan or request changes if necessary.
+</Step>
 
-  <Step title="Download or Deploy">
-    Download the code for customization or deploy directly to the platform.
-  </Step>
+{" "}
+<Step title="Download or Deploy">
+  Download the code for customization or deploy directly to the platform.
+</Step>
 
   <Step title="Test and Refine">
     Test your crew with sample inputs and refine as needed.
@@ -162,5 +177,6 @@ Here's a typical workflow for creating a crew with Crew Studio:
 </Steps>
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Crew Studio or any other CrewAI AOP features.
+  Contact our support team for assistance with Crew Studio or any other CrewAI
+  AMP features.
 </Card>

docs/en/enterprise/guides/gmail-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Use the Gmail Trigger to kick off your deployed crews when Gmail events happen in connected accounts, such as receiving a new email or messages matching a label/filter.
 
 <Tip>
-  Make sure Gmail is connected in Tools & Integrations and the trigger is enabled for your deployment.
+  Make sure Gmail is connected in Tools & Integrations and the trigger is
+  enabled for your deployment.
 </Tip>
 
 ## Enabling the Gmail Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Gmail** and switch the toggle to enable
 
 <Frame>
-  <img src="/images/enterprise/trigger-selected.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/trigger-selected.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Process new emails
@@ -62,13 +66,15 @@ Test your Gmail trigger integration locally using the CrewAI CLI:
 crewai triggers list
 
 # Simulate a Gmail trigger with realistic payload
-crewai triggers run gmail/new_email
+crewai triggers run gmail/new_email_received
 ```
 
 The `crewai triggers run` command will execute your crew with a complete Gmail payload, allowing you to test your parsing logic before deployment.
 
 <Warning>
-  Use `crewai triggers run gmail/new_email` (not `crewai run`) to simulate trigger execution during development. After deployment, your crew will automatically receive the trigger payload.
+  Use `crewai triggers run gmail/new_email_received` (not `crewai run`) to
+  simulate trigger execution during development. After deployment, your crew
+  will automatically receive the trigger payload.
 </Warning>
 
 ## Monitoring Executions
@@ -76,13 +82,16 @@ The `crewai triggers run` command will execute your crew with a complete Gmail p
 Track history and performance of triggered runs:
 
 <Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+  <img
+    src="/images/enterprise/list-executions.png"
+    alt="List of executions triggered by automation"
+  />
 </Frame>
 
 ## Troubleshooting
 
 - Ensure Gmail is connected in Tools & Integrations
 - Verify the Gmail Trigger is enabled on the Triggers tab
-- Test locally with `crewai triggers run gmail/new_email` to see the exact payload structure
+- Test locally with `crewai triggers run gmail/new_email_received` to see the exact payload structure
 - Check the execution logs and confirm the payload is passed as `crewai_trigger_payload`
 - Remember: use `crewai triggers run` (not `crewai run`) to simulate trigger execution

docs/en/enterprise/guides/google-calendar-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Use the Google Calendar trigger to launch automations whenever calendar events change. Common use cases include briefing a team before a meeting, notifying stakeholders when a critical event is cancelled, or summarizing daily schedules.
 
 <Tip>
-  Make sure Google Calendar is connected in **Tools & Integrations** and enabled for the deployment you want to automate.
+  Make sure Google Calendar is connected in **Tools & Integrations** and enabled
+  for the deployment you want to automate.
 </Tip>
 
 ## Enabling the Google Calendar Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Google Calendar** and switch the toggle to enable
 
 <Frame>
-  <img src="/images/enterprise/calendar-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/calendar-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Summarize meeting details
@@ -54,7 +58,9 @@ crewai triggers run google_calendar/event_changed
 The `crewai triggers run` command will execute your crew with a complete Calendar payload, allowing you to test your parsing logic before deployment.
 
 <Warning>
-  Use `crewai triggers run google_calendar/event_changed` (not `crewai run`) to simulate trigger execution during development. After deployment, your crew will automatically receive the trigger payload.
+  Use `crewai triggers run google_calendar/event_changed` (not `crewai run`) to
+  simulate trigger execution during development. After deployment, your crew
+  will automatically receive the trigger payload.
 </Warning>
 
 ## Monitoring Executions
@@ -62,7 +68,10 @@ The `crewai triggers run` command will execute your crew with a complete Calenda
 The **Executions** list in the deployment dashboard tracks every triggered run and surfaces payload metadata, output summaries, and errors.
 
 <Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+  <img
+    src="/images/enterprise/list-executions.png"
+    alt="List of executions triggered by automation"
+  />
 </Frame>
 
 ## Troubleshooting

docs/en/enterprise/guides/google-drive-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Trigger your automations when files are created, updated, or removed in Google Drive. Typical workflows include summarizing newly uploaded content, enforcing sharing policies, or notifying owners when critical files change.
 
 <Tip>
-  Connect Google Drive in **Tools & Integrations** and confirm the trigger is enabled for the automation you want to monitor.
+  Connect Google Drive in **Tools & Integrations** and confirm the trigger is
+  enabled for the automation you want to monitor.
 </Tip>
 
 ## Enabling the Google Drive Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Google Drive** and switch the toggle to enable
 
 <Frame>
-  <img src="/images/enterprise/gdrive-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/gdrive-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Summarize file activity
@@ -51,7 +55,9 @@ crewai triggers run google_drive/file_changed
 The `crewai triggers run` command will execute your crew with a complete Drive payload, allowing you to test your parsing logic before deployment.
 
 <Warning>
-  Use `crewai triggers run google_drive/file_changed` (not `crewai run`) to simulate trigger execution during development. After deployment, your crew will automatically receive the trigger payload.
+  Use `crewai triggers run google_drive/file_changed` (not `crewai run`) to
+  simulate trigger execution during development. After deployment, your crew
+  will automatically receive the trigger payload.
 </Warning>
 
 ## Monitoring Executions
@@ -59,7 +65,10 @@ The `crewai triggers run` command will execute your crew with a complete Drive p
 Track history and performance of triggered runs with the **Executions** list in the deployment dashboard.
 
 <Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+  <img
+    src="/images/enterprise/list-executions.png"
+    alt="List of executions triggered by automation"
+  />
 </Frame>
 
 ## Troubleshooting

docs/en/enterprise/guides/hubspot-trigger.mdx

@@ -5,48 +5,57 @@ icon: "hubspot"
 mode: "wide"
 ---
 
-This guide provides a step-by-step process to set up HubSpot triggers for CrewAI AOP, enabling you to initiate crews directly from HubSpot Workflows.
+This guide provides a step-by-step process to set up HubSpot triggers for CrewAI AMP, enabling you to initiate crews directly from HubSpot Workflows.
 
 ## Prerequisites
 
-- A CrewAI AOP account
+- A CrewAI AMP account
 - A HubSpot account with the [HubSpot Workflows](https://knowledge.hubspot.com/workflows/create-workflows) feature
 
 ## Setup Steps
 
 <Steps>
-    <Step title="Connect your HubSpot account with CrewAI AOP">
-        - Log in to your `CrewAI AOP account > Triggers`
-        - Select `HubSpot` from the list of available triggers
-        - Choose the HubSpot account you want to connect with CrewAI AOP
-        - Follow the on-screen prompts to authorize CrewAI AOP access to your HubSpot account
-        - A confirmation message will appear once HubSpot is successfully connected with CrewAI AOP
-    </Step>
-    <Step title="Create a HubSpot Workflow">
-        - Log in to your `HubSpot account > Automations > Workflows > New workflow`
-        - Select the workflow type that fits your needs (e.g., Start from scratch)
-        - In the workflow builder, click the Plus (+) icon to add a new action.
-        - Choose `Integrated apps > CrewAI > Kickoff a Crew`.
-        - Select the Crew you want to initiate.
-        - Click `Save` to add the action to your workflow
-        <Frame>
-            <img src="/images/enterprise/hubspot-workflow-1.png" alt="HubSpot Workflow 1" />
-        </Frame>
-    </Step>
-    <Step title="Use Crew results with other actions">
-        - After the Kickoff a Crew step, click the Plus (+) icon to add a new action.
-        - For example, to send an internal email notification, choose `Communications > Send internal email notification`
-        - In the Body field, click `Insert data`, select `View properties or action outputs from > Action outputs > Crew Result` to include Crew data in the email
-            <Frame>
-                <img src="/images/enterprise/hubspot-workflow-2.png" alt="HubSpot Workflow 2" />
-            </Frame>
-        - Configure any additional actions as needed
-        - Review your workflow steps to ensure everything is set up correctly
-        - Activate the workflow
-            <Frame>
-                <img src="/images/enterprise/hubspot-workflow-3.png" alt="HubSpot Workflow 3" />
-            </Frame>
-    </Step>
+  <Step title="Connect your HubSpot account with CrewAI AMP">
+    - Log in to your `CrewAI AMP account > Triggers` - Select `HubSpot` from the
+    list of available triggers - Choose the HubSpot account you want to connect
+    with CrewAI AMP - Follow the on-screen prompts to authorize CrewAI AMP
+    access to your HubSpot account - A confirmation message will appear once
+    HubSpot is successfully connected with CrewAI AMP
+  </Step>
+  <Step title="Create a HubSpot Workflow">
+    - Log in to your `HubSpot account > Automations > Workflows > New workflow`
+    - Select the workflow type that fits your needs (e.g., Start from scratch) -
+    In the workflow builder, click the Plus (+) icon to add a new action. -
+    Choose `Integrated apps > CrewAI > Kickoff a Crew`. - Select the Crew you
+    want to initiate. - Click `Save` to add the action to your workflow
+    <Frame>
+      <img
+        src="/images/enterprise/hubspot-workflow-1.png"
+        alt="HubSpot Workflow 1"
+      />
+    </Frame>
+  </Step>
+  <Step title="Use Crew results with other actions">
+    - After the Kickoff a Crew step, click the Plus (+) icon to add a new
+    action. - For example, to send an internal email notification, choose
+    `Communications > Send internal email notification` - In the Body field,
+    click `Insert data`, select `View properties or action outputs from > Action
+    outputs > Crew Result` to include Crew data in the email
+    <Frame>
+      <img
+        src="/images/enterprise/hubspot-workflow-2.png"
+        alt="HubSpot Workflow 2"
+      />
+  </Frame>
+  - Configure any additional actions as needed - Review your workflow
+    steps to ensure everything is set up correctly - Activate the workflow
+    <Frame>
+      <img
+        src="/images/enterprise/hubspot-workflow-3.png"
+        alt="HubSpot Workflow 3"
+      />
+    </Frame>
+  </Step>
 </Steps>
 
 For more detailed information on available actions and customization options, refer to the [HubSpot Workflows Documentation](https://knowledge.hubspot.com/workflows/create-workflows).

docs/en/enterprise/guides/kickoff-crew.mdx

@@ -1,25 +1,23 @@
 ---
 title: "Kickoff Crew"
-description: "Kickoff a Crew on CrewAI AOP"
+description: "Kickoff a Crew on CrewAI AMP"
 icon: "flag-checkered"
 mode: "wide"
 ---
 
 ## Overview
 
-Once you've deployed your crew to the CrewAI AOP platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
+Once you've deployed your crew to the CrewAI AMP platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
 
 ## Method 1: Using the Web Interface
 
 ### Step 1: Navigate to Your Deployed Crew
 
-1. Log in to [CrewAI AOP](https://app.crewai.com)
+1. Log in to [CrewAI AMP](https://app.crewai.com)
 2. Click on the crew name from your projects list
 3. You'll be taken to the crew's detail page
 
-<Frame>
-  ![Crew Dashboard](/images/enterprise/crew-dashboard.png)
-</Frame>
+<Frame>![Crew Dashboard](/images/enterprise/crew-dashboard.png)</Frame>
 
 ### Step 2: Initiate Execution
 
@@ -31,9 +29,7 @@ From your crew's detail page, you have two options to kickoff an execution:
 2. Enter the required input parameters for your crew in the JSON editor
 3. Click the `Send Request` button
 
-<Frame>
-  ![Kickoff Endpoint](/images/enterprise/kickoff-endpoint.png)
-</Frame>
+<Frame>![Kickoff Endpoint](/images/enterprise/kickoff-endpoint.png)</Frame>
 
 #### Option B: Using the Visual Interface
 
@@ -41,9 +37,7 @@ From your crew's detail page, you have two options to kickoff an execution:
 2. Enter the required inputs in the form fields
 3. Click the `Run Crew` button
 
-<Frame>
-  ![Run Crew](/images/enterprise/run-crew.png)
-</Frame>
+<Frame>![Run Crew](/images/enterprise/run-crew.png)</Frame>
 
 ### Step 3: Monitor Execution Progress
 
@@ -52,9 +46,7 @@ After initiating the execution:
 1. You'll receive a response containing a `kickoff_id` - **copy this ID**
 2. This ID is essential for tracking your execution
 
-<Frame>
-  ![Copy Task ID](/images/enterprise/copy-task-id.png)
-</Frame>
+<Frame>![Copy Task ID](/images/enterprise/copy-task-id.png)</Frame>
 
 ### Step 4: Check Execution Status
 
@@ -64,11 +56,10 @@ To monitor the progress of your execution:
 2. Paste the `kickoff_id` into the designated field
 3. Click the "Get Status" button
 
-<Frame>
-  ![Get Status](/images/enterprise/get-status.png)
-</Frame>
+<Frame>![Get Status](/images/enterprise/get-status.png)</Frame>
 
 The status response will show:
+
 - Current execution state (`running`, `completed`, etc.)
 - Details about which tasks are in progress
 - Any outputs produced so far
@@ -83,7 +74,7 @@ Once execution is complete:
 
 ## Method 2: Using the API
 
-You can also kickoff crews programmatically using the CrewAI AOP REST API.
+You can also kickoff crews programmatically using the CrewAI AMP REST API.
 
 ### Authentication
 
@@ -122,7 +113,7 @@ curl -X GET \
 The response will be a JSON object containing an array of required input parameters, for example:
 
 ```json
-{"inputs":["topic","current_year"]}
+{ "inputs": ["topic", "current_year"] }
 ```
 
 This example shows that this particular crew requires two inputs: `topic` and `current_year`.
@@ -142,7 +133,7 @@ curl -X POST \
 The response will include a `kickoff_id` that you'll need for tracking:
 
 ```json
-{"kickoff_id":"abcd1234-5678-90ef-ghij-klmnopqrstuv"}
+{ "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv" }
 ```
 
 ### Step 3: Check Execution Status
@@ -182,5 +173,6 @@ If an execution fails:
 3. Look for LLM responses and tool usage in the trace details
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with execution issues or questions about the Enterprise platform.
+  Contact our support team for assistance with execution issues or questions
+  about the Enterprise platform.
 </Card>

docs/en/enterprise/guides/microsoft-teams-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Use the Microsoft Teams trigger to start automations whenever a new chat is created. Common patterns include summarizing inbound requests, routing urgent messages to support teams, or creating follow-up tasks in other systems.
 
 <Tip>
-  Confirm Microsoft Teams is connected under **Tools & Integrations** and enabled in the **Triggers** tab for your deployment.
+  Confirm Microsoft Teams is connected under **Tools & Integrations** and
+  enabled in the **Triggers** tab for your deployment.
 </Tip>
 
 ## Enabling the Microsoft Teams Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Microsoft Teams** and switch the toggle to enable
 
 <Frame caption="Microsoft Teams trigger connection">
-  <img src="/images/enterprise/msteams-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/msteams-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Summarize a new chat thread
@@ -52,7 +56,9 @@ crewai triggers run microsoft_teams/teams_message_created
 The `crewai triggers run` command will execute your crew with a complete Teams payload, allowing you to test your parsing logic before deployment.
 
 <Warning>
-  Use `crewai triggers run microsoft_teams/teams_message_created` (not `crewai run`) to simulate trigger execution during development. After deployment, your crew will automatically receive the trigger payload.
+  Use `crewai triggers run microsoft_teams/teams_message_created` (not `crewai
+  run`) to simulate trigger execution during development. After deployment, your
+  crew will automatically receive the trigger payload.
 </Warning>
 
 ## Troubleshooting

docs/en/enterprise/guides/onedrive-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Start automations when files change inside OneDrive. You can generate audit summaries, notify security teams about external sharing, or update downstream line-of-business systems with new document metadata.
 
 <Tip>
-  Connect OneDrive in **Tools & Integrations** and toggle the trigger on for your deployment.
+  Connect OneDrive in **Tools & Integrations** and toggle the trigger on for
+  your deployment.
 </Tip>
 
 ## Enabling the OneDrive Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **OneDrive** and switch the toggle to enable
 
 <Frame caption="Microsoft OneDrive trigger connection">
-  <img src="/images/enterprise/onedrive-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/onedrive-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Audit file permissions
@@ -51,7 +55,9 @@ crewai triggers run microsoft_onedrive/file_changed
 The `crewai triggers run` command will execute your crew with a complete OneDrive payload, allowing you to test your parsing logic before deployment.
 
 <Warning>
-  Use `crewai triggers run microsoft_onedrive/file_changed` (not `crewai run`) to simulate trigger execution during development. After deployment, your crew will automatically receive the trigger payload.
+  Use `crewai triggers run microsoft_onedrive/file_changed` (not `crewai run`)
+  to simulate trigger execution during development. After deployment, your crew
+  will automatically receive the trigger payload.
 </Warning>
 
 ## Troubleshooting

docs/en/enterprise/guides/outlook-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Automate responses when Outlook delivers a new message or when an event is removed from the calendar. Teams commonly route escalations, file tickets, or alert attendees of cancellations.
 
 <Tip>
-  Connect Outlook in **Tools & Integrations** and ensure the trigger is enabled for your deployment.
+  Connect Outlook in **Tools & Integrations** and ensure the trigger is enabled
+  for your deployment.
 </Tip>
 
 ## Enabling the Outlook Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Outlook** and switch the toggle to enable
 
 <Frame caption="Microsoft Outlook trigger connection">
-  <img src="/images/enterprise/outlook-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/outlook-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Summarize a new email
@@ -51,7 +55,9 @@ crewai triggers run microsoft_outlook/email_received
 The `crewai triggers run` command will execute your crew with a complete Outlook payload, allowing you to test your parsing logic before deployment.
 
 <Warning>
-  Use `crewai triggers run microsoft_outlook/email_received` (not `crewai run`) to simulate trigger execution during development. After deployment, your crew will automatically receive the trigger payload.
+  Use `crewai triggers run microsoft_outlook/email_received` (not `crewai run`)
+  to simulate trigger execution during development. After deployment, your crew
+  will automatically receive the trigger payload.
 </Warning>
 
 ## Troubleshooting

docs/en/enterprise/guides/react-component-export.mdx

@@ -1,11 +1,11 @@
 ---
 title: "React Component Export"
-description: "Learn how to export and integrate CrewAI AOP React components into your applications"
+description: "Learn how to export and integrate CrewAI AMP React components into your applications"
 icon: "react"
 mode: "wide"
 ---
 
-This guide explains how to export CrewAI AOP crews as React components and integrate them into your own applications.
+This guide explains how to export CrewAI AMP crews as React components and integrate them into your own applications.
 
 ## Exporting a React Component
 
@@ -17,6 +17,7 @@ This guide explains how to export CrewAI AOP crews as React components and integ
             <img src="/images/enterprise/export-react-component.png" alt="Export React Component" />
         </Frame>
     </Step>
+
 </Steps>
 
 ## Setting Up Your React Environment
@@ -83,6 +84,7 @@ To run this React component locally, you'll need to set up a React development e
             ```
         - This will start the development server, and your default web browser should open automatically to http://localhost:3000, where you'll see your React app running.
     </Step>
+
 </Steps>
 
 ## Customization
@@ -90,10 +92,16 @@ To run this React component locally, you'll need to set up a React development e
 You can then customise the `CrewLead.jsx` to add color, title etc
 
 <Frame>
-    <img src="/images/enterprise/customise-react-component.png" alt="Customise React Component" />
+  <img
+    src="/images/enterprise/customise-react-component.png"
+    alt="Customise React Component"
+  />
 </Frame>
 <Frame>
-    <img src="/images/enterprise/customise-react-component-2.png" alt="Customise React Component" />
+  <img
+    src="/images/enterprise/customise-react-component-2.png"
+    alt="Customise React Component"
+  />
 </Frame>
 
 ## Next Steps

docs/en/enterprise/guides/salesforce-trigger.mdx

@@ -5,7 +5,7 @@ icon: "salesforce"
 mode: "wide"
 ---
 
-CrewAI AOP can be triggered from Salesforce to automate customer relationship management workflows and enhance your sales operations.
+CrewAI AMP can be triggered from Salesforce to automate customer relationship management workflows and enhance your sales operations.
 
 ## Overview
 
@@ -31,7 +31,7 @@ Salesforce is a leading customer relationship management (CRM) platform that hel
 
 To set up Salesforce triggers:
 
-1. **Contact Support**: Reach out to CrewAI AOP support for assistance with Salesforce trigger setup
+1. **Contact Support**: Reach out to CrewAI AMP support for assistance with Salesforce trigger setup
 2. **Review Requirements**: Ensure you have the necessary Salesforce permissions and API access
 3. **Configure Connection**: Work with the support team to establish the connection between CrewAI and your Salesforce instance
 4. **Test Triggers**: Verify the triggers work correctly with your specific use cases
@@ -47,4 +47,4 @@ Common Salesforce + CrewAI trigger scenarios include:
 
 ## Next Steps
 
-For detailed setup instructions and advanced configuration options, please contact CrewAI AOP support who can provide tailored guidance for your specific Salesforce environment and business needs.
+For detailed setup instructions and advanced configuration options, please contact CrewAI AMP support who can provide tailored guidance for your specific Salesforce environment and business needs.

docs/en/enterprise/guides/team-management.mdx

@@ -1,40 +1,39 @@
 ---
 title: "Team Management"
-description: "Learn how to invite and manage team members in your CrewAI AOP organization"
+description: "Learn how to invite and manage team members in your CrewAI AMP organization"
 icon: "users"
 mode: "wide"
 ---
 
-As an administrator of a CrewAI AOP account, you can easily invite new team members to join your organization. This guide will walk you through the process step-by-step.
+As an administrator of a CrewAI AMP account, you can easily invite new team members to join your organization. This guide will walk you through the process step-by-step.
 
 ## Inviting Team Members
 
 <Steps>
-    <Step title="Access the Settings Page">
-        - Log in to your CrewAI AOP account
-        - Look for the gear icon (⚙️) in the top right corner of the dashboard
-        - Click on the gear icon to access the **Settings** page:
-            <Frame caption="Settings page">
-                <img src="/images/enterprise/settings-page.png" alt="Settings Page" />
-            </Frame>
-    </Step>
-    <Step title="Navigate to the Members Section">
-        - On the Settings page, you'll see a `Members` tab
-        - Click on the `Members` tab to access the **Members** page:
-            <Frame caption="Members tab">
-                <img src="/images/enterprise/members-tab.png" alt="Members Tab" />
-            </Frame>
-    </Step>
-    <Step title="Invite New Members">
-        - In the Members section, you'll see a list of current members (including yourself)
-        - Locate the `Email` input field
-        - Enter the email address of the person you want to invite
-        - Click the `Invite` button to send the invitation
-    </Step>
-    <Step title="Repeat as Needed">
-        - You can repeat this process to invite multiple team members
-        - Each invited member will receive an email invitation to join your organization
-    </Step>
+  <Step title="Access the Settings Page">
+    - Log in to your CrewAI AMP account - Look for the gear icon (⚙️) in the top
+    right corner of the dashboard - Click on the gear icon to access the
+    **Settings** page:
+    <Frame caption="Settings page">
+      <img src="/images/enterprise/settings-page.png" alt="Settings Page" />
+    </Frame>
+  </Step>
+  <Step title="Navigate to the Members Section">
+    - On the Settings page, you'll see a `Members` tab - Click on the `Members`
+    tab to access the **Members** page:
+    <Frame caption="Members tab">
+      <img src="/images/enterprise/members-tab.png" alt="Members Tab" />
+    </Frame>
+  </Step>
+  <Step title="Invite New Members">
+    - In the Members section, you'll see a list of current members (including
+    yourself) - Locate the `Email` input field - Enter the email address of the
+    person you want to invite - Click the `Invite` button to send the invitation
+  </Step>
+  <Step title="Repeat as Needed">
+    - You can repeat this process to invite multiple team members - Each invited
+    member will receive an email invitation to join your organization
+  </Step>
 </Steps>
 
 ## Adding Roles
@@ -42,40 +41,44 @@ As an administrator of a CrewAI AOP account, you can easily invite new team memb
 You can add roles to your team members to control their access to different parts of the platform.
 
 <Steps>
-    <Step title="Access the Settings Page">
-        - Log in to your CrewAI AOP account
-        - Look for the gear icon (⚙️) in the top right corner of the dashboard
-        - Click on the gear icon to access the **Settings** page:
-            <Frame>
-                <img src="/images/enterprise/settings-page.png" alt="Settings Page" />
-            </Frame>
-    </Step>
-    <Step title="Navigate to the Members Section">
-        - On the Settings page, you'll see a `Roles` tab
-        - Click on the `Roles` tab to access the **Roles** page.
-            <Frame>
-                <img src="/images/enterprise/roles-tab.png" alt="Roles Tab" />
-            </Frame>
-        - Click on the `Add Role` button to add a new role.
-        - Enter the details and permissions of the role and click the `Create Role` button to create the role.
-            <Frame>
-                <img src="/images/enterprise/add-role-modal.png" alt="Add Role Modal" />
-            </Frame>
-    </Step>
-    <Step title="Add Roles to Members">
-        - In the Members section, you'll see a list of current members (including yourself)
-           <Frame>
-                <img src="/images/enterprise/member-accepted-invitation.png" alt="Member Accepted Invitation" />
-           </Frame>
-        - Once the member has accepted the invitation, you can add a role to them.
-        - Navigate back to `Roles` tab
-        - Go to the member you want to add a role to and under the `Role` column, click on the dropdown
-        - Select the role you want to add to the member
-        - Click the `Update` button to save the role
-            <Frame>
-                <img src="/images/enterprise/assign-role.png" alt="Add Role to Member" />
-            </Frame>
-    </Step>
+  <Step title="Access the Settings Page">
+    - Log in to your CrewAI AMP account - Look for the gear icon (⚙️) in the top
+    right corner of the dashboard - Click on the gear icon to access the
+    **Settings** page:
+    <Frame>
+      <img src="/images/enterprise/settings-page.png" alt="Settings Page" />
+    </Frame>
+  </Step>
+  <Step title="Navigate to the Members Section">
+    - On the Settings page, you'll see a `Roles` tab - Click on the `Roles` tab
+    to access the **Roles** page.
+    <Frame>
+      <img src="/images/enterprise/roles-tab.png" alt="Roles Tab" />
+    </Frame>
+    - Click on the `Add Role` button to add a new role. - Enter the
+    details and permissions of the role and click the `Create Role` button to
+    create the role.
+    <Frame>
+      <img src="/images/enterprise/add-role-modal.png" alt="Add Role Modal" />
+    </Frame>
+  </Step>
+  <Step title="Add Roles to Members">
+    - In the Members section, you'll see a list of current members (including
+    yourself)
+    <Frame>
+      <img
+        src="/images/enterprise/member-accepted-invitation.png"
+        alt="Member Accepted Invitation"
+      />
+    </Frame>
+    - Once the member has accepted the invitation, you can add a role to
+    them. - Navigate back to `Roles` tab - Go to the member you want to add a
+    role to and under the `Role` column, click on the dropdown - Select the role
+    you want to add to the member - Click the `Update` button to save the role
+    <Frame>
+      <img src="/images/enterprise/assign-role.png" alt="Add Role to Member" />
+    </Frame>
+  </Step>
 </Steps>
 
 ## Important Notes
@@ -85,4 +88,4 @@ You can add roles to your team members to control their access to different part
 - **Invitation Acceptance**: Invited members will need to accept the invitation to join your organization
 - **Email Notifications**: You may want to inform your team members to check their email (including spam folders) for the invitation
 
-By following these steps, you can easily expand your team and collaborate more effectively within your CrewAI AOP organization.
+By following these steps, you can easily expand your team and collaborate more effectively within your CrewAI AMP organization.

docs/en/enterprise/guides/tool-repository.mdx

@@ -20,11 +20,11 @@ The repository is not a version control system. Use Git to track code changes an
 
 Before using the Tool Repository, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account
+- A [CrewAI AMP](https://app.crewai.com) account
 - [CrewAI CLI](/en/concepts/cli#cli) installed
 - uv>=0.5.0 installed. Check out [how to upgrade](https://docs.astral.sh/uv/getting-started/installation/#upgrading-uv)
 - [Git](https://git-scm.com) installed and configured
-- Access permissions to publish or install tools in your CrewAI AOP organization
+- Access permissions to publish or install tools in your CrewAI AMP organization
 
 ## Installing Tools
 
@@ -54,11 +54,11 @@ researcher = Agent(
 
 ## Adding other packages after installing a tool
 
-After installing a tool from the CrewAI AOP Tool Repository, you need to use the `crewai uv` command to add other packages to your project.
+After installing a tool from the CrewAI AMP Tool Repository, you need to use the `crewai uv` command to add other packages to your project.
 Using pure `uv` commands will fail due to authentication to tool repository being handled by the CLI. By using the `crewai uv` command, you can add other packages to your project without having to worry about authentication.
 Any `uv` command can be used with the `crewai uv` command, making it a powerful tool for managing your project's dependencies without the hassle of managing authentication through environment variables or other methods.
 
-Say that you have installed a custom tool from the CrewAI AOP Tool Repository called "my-tool":
+Say that you have installed a custom tool from the CrewAI AMP Tool Repository called "my-tool":
 
 ```bash
 crewai tool install my-tool
@@ -131,13 +131,13 @@ crewai tool publish
 
 To delete a tool:
 
-1. Go to [CrewAI AOP](https://app.crewai.com)
+1. Go to [CrewAI AMP](https://app.crewai.com)
 2. Navigate to **Tools**
 3. Select the tool
 4. Click **Delete**
 
 <Warning>
-Deletion is permanent. Deleted tools cannot be restored or re-installed.
+  Deletion is permanent. Deleted tools cannot be restored or re-installed.
 </Warning>
 
 ## Security Checks
@@ -146,8 +146,9 @@ Every published version undergoes automated security checks, and are only availa
 
 You can check the security check status of a tool at:
 
-`CrewAI AOP > Tools > Your Tool > Versions`
+`CrewAI AMP > Tools > Your Tool > Versions`
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with API integration or troubleshooting.
+  Contact our support team for assistance with API integration or
+  troubleshooting.
 </Card>

docs/en/enterprise/guides/update-crew.mdx

@@ -1,13 +1,14 @@
 ---
 title: "Update Crew"
-description: "Updating a Crew on CrewAI AOP"
+description: "Updating a Crew on CrewAI AMP"
 icon: "pencil"
 mode: "wide"
 ---
 
 <Note>
-After deploying your crew to CrewAI AOP, you may need to make updates to the code, security settings, or configuration.
-This guide explains how to perform these common update operations.
+  After deploying your crew to CrewAI AMP, you may need to make updates to the
+  code, security settings, or configuration. This guide explains how to perform
+  these common update operations.
 </Note>
 
 ## Why Update Your Crew?
@@ -15,6 +16,7 @@ This guide explains how to perform these common update operations.
 CrewAI won't automatically pick up GitHub updates by default, so you'll need to manually trigger updates, unless you checked the `Auto-update` option when deploying your crew.
 
 There are several reasons you might want to update your crew deployment:
+
 - You want to update the code with a latest commit you pushed to GitHub
 - You want to reset the bearer token for security reasons
 - You want to update environment variables
@@ -23,12 +25,10 @@ There are several reasons you might want to update your crew deployment:
 
 When you've pushed new commits to your GitHub repository and want to update your deployment:
 
-1. Navigate to your crew in the CrewAI AOP platform
+1. Navigate to your crew in the CrewAI AMP platform
 2. Click on the `Re-deploy` button on your crew details page
 
-<Frame>
-  ![Re-deploy Button](/images/enterprise/redeploy-button.png)
-</Frame>
+<Frame>![Re-deploy Button](/images/enterprise/redeploy-button.png)</Frame>
 
 This will trigger an update that you can track using the progress bar. The system will pull the latest code from your repository and rebuild your deployment.
 
@@ -36,16 +36,15 @@ This will trigger an update that you can track using the progress bar. The syste
 
 If you need to generate a new bearer token (for example, if you suspect the current token might have been compromised):
 
-1. Navigate to your crew in the CrewAI AOP platform
+1. Navigate to your crew in the CrewAI AMP platform
 2. Find the `Bearer Token` section
 3. Click the `Reset` button next to your current token
 
-<Frame>
-  ![Reset Token](/images/enterprise/reset-token.png)
-</Frame>
+<Frame>![Reset Token](/images/enterprise/reset-token.png)</Frame>
 
 <Warning>
-Resetting your bearer token will invalidate the previous token immediately. Make sure to update any applications or scripts that are using the old token.
+  Resetting your bearer token will invalidate the previous token immediately.
+  Make sure to update any applications or scripts that are using the old token.
 </Warning>
 
 ## 3. Updating Environment Variables
@@ -69,7 +68,8 @@ To update the environment variables for your crew:
 5. Finally, click the `Update Deployment` button at the bottom of the page to apply the changes
 
 <Note>
-Updating environment variables will trigger a new deployment, but this will only update the environment configuration and not the code itself.
+  Updating environment variables will trigger a new deployment, but this will
+  only update the environment configuration and not the code itself.
 </Note>
 
 ## After Updating
@@ -81,9 +81,11 @@ After performing any update:
 3. Once complete, test your crew to ensure the changes are working as expected
 
 <Tip>
-If you encounter any issues after updating, you can view deployment logs in the platform or contact support for assistance.
+  If you encounter any issues after updating, you can view deployment logs in
+  the platform or contact support for assistance.
 </Tip>
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with updating your crew or troubleshooting deployment issues.
+  Contact our support team for assistance with updating your crew or
+  troubleshooting deployment issues.
 </Card>

docs/en/enterprise/guides/webhook-automation.mdx

@@ -1,17 +1,17 @@
 ---
 title: "Webhook Automation"
-description: "Automate CrewAI AOP workflows using webhooks with platforms like ActivePieces, Zapier, and Make.com"
+description: "Automate CrewAI AMP workflows using webhooks with platforms like ActivePieces, Zapier, and Make.com"
 icon: "webhook"
 mode: "wide"
 ---
 
-CrewAI AOP allows you to automate your workflow using webhooks. This article will guide you through the process of setting up and using webhooks to kickoff your crew execution, with a focus on integration with ActivePieces, a workflow automation platform similar to Zapier and Make.com.
+CrewAI AMP allows you to automate your workflow using webhooks. This article will guide you through the process of setting up and using webhooks to kickoff your crew execution, with a focus on integration with ActivePieces, a workflow automation platform similar to Zapier and Make.com.
 
 ## Setting Up Webhooks
 
 <Steps>
     <Step title="Accessing the Kickoff Interface">
-        - Navigate to the CrewAI AOP dashboard
+        - Navigate to the CrewAI AMP dashboard
         - Look for the `/kickoff` section, which is used to start the crew execution
             <Frame>
                 <img src="/images/enterprise/kickoff-interface.png" alt="Kickoff Interface" />
@@ -44,7 +44,7 @@ CrewAI AOP allows you to automate your workflow using webhooks. This article wil
         3. Add an HTTP action step
             - Set the action to `Send HTTP request`
             - Use `POST` as the method
-            - Set the URL to your CrewAI AOP kickoff endpoint
+            - Set the URL to your CrewAI AMP kickoff endpoint
             - Add necessary headers (e.g., `Bearer Token`)
                 <Frame>
                     <img src="/images/enterprise/activepieces-headers.png" alt="ActivePieces Headers" />
@@ -76,6 +76,7 @@ CrewAI AOP allows you to automate your workflow using webhooks. This article wil
                     <img src="/images/enterprise/activepieces-email.png" alt="ActivePieces Email" />
                 </Frame>
     </Step>
+
 </Steps>
 
 ## Webhook Output Examples
@@ -152,4 +153,5 @@ CrewAI AOP allows you to automate your workflow using webhooks. This article wil
         }
         ```
     </Tab>
+
 </Tabs>

docs/en/enterprise/guides/zapier-trigger.mdx

@@ -5,11 +5,11 @@ icon: "bolt"
 mode: "wide"
 ---
 
-This guide will walk you through the process of setting up Zapier triggers for CrewAI AOP, allowing you to automate workflows between CrewAI AOP and other applications.
+This guide will walk you through the process of setting up Zapier triggers for CrewAI AMP, allowing you to automate workflows between CrewAI AMP and other applications.
 
 ## Prerequisites
 
-- A CrewAI AOP account
+- A CrewAI AMP account
 - A Zapier account
 - A Slack account (for this specific example)
 
@@ -32,7 +32,7 @@ This guide will walk you through the process of setting up Zapier triggers for C
         - Connect your Slack account if you haven't already.
     </Step>
 
-    <Step title="Configure the CrewAI AOP Action">
+    <Step title="Configure the CrewAI AMP Action">
         - Add a new action step to your Zap.
         - Choose CrewAI+ as your action app and Kickoff as the Action Event
 
@@ -41,8 +41,8 @@ This guide will walk you through the process of setting up Zapier triggers for C
         </Frame>
     </Step>
 
-    <Step title="Connect your CrewAI AOP account">
-        - Connect your CrewAI AOP account.
+    <Step title="Connect your CrewAI AMP account">
+        - Connect your CrewAI AMP account.
         - Select the appropriate Crew for your workflow.
 
         <Frame>
@@ -51,8 +51,8 @@ This guide will walk you through the process of setting up Zapier triggers for C
         - Configure the inputs for the Crew using the data from the Slack message.
     </Step>
 
-    <Step title="Format the CrewAI AOP Output">
-        - Add another action step to format the text output from CrewAI AOP.
+    <Step title="Format the CrewAI AMP Output">
+        - Add another action step to format the text output from CrewAI AMP.
         - Use Zapier's formatting tools to convert the Markdown output to HTML.
 
         <Frame>
@@ -67,7 +67,7 @@ This guide will walk you through the process of setting up Zapier triggers for C
         - Add a final action step to send the formatted output via email.
         - Choose your preferred email service (e.g., Gmail, Outlook).
         - Configure the email details, including recipient, subject, and body.
-        - Insert the formatted CrewAI AOP output into the email body.
+        - Insert the formatted CrewAI AMP output into the email body.
 
         <Frame>
             <img src="/images/enterprise/zapier-7.png" alt="Zapier 7" />
@@ -93,12 +93,13 @@ This guide will walk you through the process of setting up Zapier triggers for C
             <img src="/images/enterprise/zapier-9.png" alt="Zapier 12" />
         </Frame>
     </Step>
+
 </Steps>
 
 ## Tips for Success
 
-- Ensure that your CrewAI AOP inputs are correctly mapped from the Slack message.
+- Ensure that your CrewAI AMP inputs are correctly mapped from the Slack message.
 - Test your Zap thoroughly before turning it on to catch any potential issues.
 - Consider adding error handling steps to manage potential failures in the workflow.
 
-By following these steps, you'll have successfully set up Zapier triggers for CrewAI AOP, allowing for automated workflows triggered by Slack messages and resulting in email notifications with CrewAI AOP output.
+By following these steps, you'll have successfully set up Zapier triggers for CrewAI AMP, allowing for automated workflows triggered by Slack messages and resulting in email notifications with CrewAI AMP output.

docs/en/enterprise/integrations/asana.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage tasks, projects, and team coordination through Asan
 
 Before using the Asana integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - An Asana account with appropriate permissions
 - Connected your Asana account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Asana integration, ensure you have:
 
 ### 1. Connect Your Asana Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Asana** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for task and project management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -58,6 +60,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `task` (string, required): Task ID - The ID of the Task the comment will be added to. The comment will be authored by the currently authenticated user.
     - `text` (string, required): Text (example: "This is a comment.").
+
   </Accordion>
 
   <Accordion title="asana/create_project">
@@ -68,6 +71,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `workspace` (string, required): Workspace - Use Connect Portal Workflow Settings to allow users to select which Workspace to create Projects in. Defaults to the user's first Workspace if left blank.
     - `team` (string, optional): Team - Use Connect Portal Workflow Settings to allow users to select which Team to share this Project with. Defaults to the user's first Team if left blank.
     - `notes` (string, optional): Notes (example: "These are things we need to purchase.").
+
   </Accordion>
 
   <Accordion title="asana/get_projects">
@@ -76,6 +80,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `archived` (string, optional): Archived - Choose "true" to show archived projects, "false" to display only active projects, or "default" to show both archived and active projects.
       - Options: `default`, `true`, `false`
+
   </Accordion>
 
   <Accordion title="asana/get_project_by_id">
@@ -83,6 +88,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `projectFilterId` (string, required): Project ID.
+
   </Accordion>
 
   <Accordion title="asana/create_task">
@@ -97,6 +103,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `dueAtDate` (string, optional): Due At - The date and time (ISO timestamp) at which this task is due. Cannot be used together with Due On. (example: "2019-09-15T02:06:58.147Z").
     - `assignee` (string, optional): Assignee - The ID of the Asana user this task will be assigned to. Use Connect Portal Workflow Settings to allow users to select an Assignee.
     - `gid` (string, optional): External ID - An ID from your application to associate this task with. You can use this ID to sync updates to this task later.
+
   </Accordion>
 
   <Accordion title="asana/update_task">
@@ -112,6 +119,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `dueAtDate` (string, optional): Due At - The date and time (ISO timestamp) at which this task is due. Cannot be used together with Due On. (example: "2019-09-15T02:06:58.147Z").
     - `assignee` (string, optional): Assignee - The ID of the Asana user this task will be assigned to. Use Connect Portal Workflow Settings to allow users to select an Assignee.
     - `gid` (string, optional): External ID - An ID from your application to associate this task with. You can use this ID to sync updates to this task later.
+
   </Accordion>
 
   <Accordion title="asana/get_tasks">
@@ -122,6 +130,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `project` (string, optional): Project - The ID of the Project to filter tasks on. Use Connect Portal Workflow Settings to allow users to select a Project.
     - `assignee` (string, optional): Assignee - The ID of the assignee to filter tasks on. Use Connect Portal Workflow Settings to allow users to select an Assignee.
     - `completedSince` (string, optional): Completed since - Only return tasks that are either incomplete or that have been completed since this time (ISO or Unix timestamp). (example: "2014-04-25T16:15:47-04:00").
+
   </Accordion>
 
   <Accordion title="asana/get_tasks_by_id">
@@ -129,6 +138,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `taskId` (string, required): Task ID.
+
   </Accordion>
 
   <Accordion title="asana/get_task_by_external_id">
@@ -136,6 +146,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `gid` (string, required): External ID - The ID that this task is associated or synced with, from your application.
+
   </Accordion>
 
   <Accordion title="asana/add_task_to_section">
@@ -146,6 +157,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `taskId` (string, required): Task ID - The ID of the task. (example: "1204619611402340").
     - `beforeTaskId` (string, optional): Before Task ID - The ID of a task in this section that this task will be inserted before. Cannot be used with After Task ID. (example: "1204619611402340").
     - `afterTaskId` (string, optional): After Task ID - The ID of a task in this section that this task will be inserted after. Cannot be used with Before Task ID. (example: "1204619611402340").
+
   </Accordion>
 
   <Accordion title="asana/get_teams">
@@ -153,12 +165,14 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `workspace` (string, required): Workspace - Returns the teams in this workspace visible to the authorized user.
+
   </Accordion>
 
   <Accordion title="asana/get_workspaces">
     **Description:** Get a list of workspaces in Asana.
 
     **Parameters:** None required.
+
   </Accordion>
 </AccordionGroup>
 

docs/en/enterprise/integrations/box.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage files, folders, and documents through Box. Upload f
 
 Before using the Box integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Box account with appropriate permissions
 - Connected your Box account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Box integration, ensure you have:
 
 ### 1. Connect Your Box Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Box** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for file and folder management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -66,6 +68,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       }
       ```
     - `file` (string, required): File URL - Files must be smaller than 50MB in size. (example: "https://picsum.photos/200/300").
+
   </Accordion>
 
   <Accordion title="box/save_file_from_object">
@@ -75,6 +78,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `file` (string, required): File - Accepts a File Object containing file data. Files must be smaller than 50MB in size.
     - `fileName` (string, required): File Name (example: "qwerty.png").
     - `folder` (string, optional): Folder - Use Connect Portal Workflow Settings to allow users to select the File's Folder destination. Defaults to the user's root folder if left blank.
+
   </Accordion>
 
   <Accordion title="box/get_file_by_id">
@@ -82,6 +86,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `fileId` (string, required): File ID - The unique identifier that represents a file. (example: "12345").
+
   </Accordion>
 
   <Accordion title="box/list_files">
@@ -107,6 +112,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         ]
       }
       ```
+
   </Accordion>
 
   <Accordion title="box/create_folder">
@@ -120,6 +126,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "id": "123456"
       }
       ```
+
   </Accordion>
 
   <Accordion title="box/move_folder">
@@ -134,6 +141,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "id": "123456"
       }
       ```
+
   </Accordion>
 
   <Accordion title="box/get_folder_by_id">
@@ -141,6 +149,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `folderId` (string, required): Folder ID - The unique identifier that represents a folder. (example: "0").
+
   </Accordion>
 
   <Accordion title="box/search_folders">
@@ -166,6 +175,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         ]
       }
       ```
+
   </Accordion>
 
   <Accordion title="box/delete_folder">
@@ -174,6 +184,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `folderId` (string, required): Folder ID - The unique identifier that represents a folder. (example: "0").
     - `recursive` (boolean, optional): Recursive - Delete a folder that is not empty by recursively deleting the folder and all of its content.
+
   </Accordion>
 </AccordionGroup>
 

docs/en/enterprise/integrations/clickup.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage tasks, projects, and productivity workflows through
 
 Before using the ClickUp integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A ClickUp account with appropriate permissions
 - Connected your ClickUp account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the ClickUp integration, ensure you have:
 
 ### 1. Connect Your ClickUp Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **ClickUp** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for task and project management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -75,6 +77,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       }
       ```
       Available fields: `space_ids%5B%5D`, `project_ids%5B%5D`, `list_ids%5B%5D`, `statuses%5B%5D`, `include_closed`, `assignees%5B%5D`, `tags%5B%5D`, `due_date_gt`, `due_date_lt`, `date_created_gt`, `date_created_lt`, `date_updated_gt`, `date_updated_lt`
+
   </Accordion>
 
   <Accordion title="clickup/get_task_in_list">
@@ -83,6 +86,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `listId` (string, required): List - Select a List to get tasks from. Use Connect Portal User Settings to allow users to select a ClickUp List.
     - `taskFilterFormula` (string, optional): Search for tasks that match specified filters. For example: name=task1.
+
   </Accordion>
 
   <Accordion title="clickup/create_task">
@@ -96,6 +100,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `assignees` (string, optional): Assignees - Select a Member (or an array of member IDs) to be assigned to this task. Use Connect Portal User Settings to allow users to select a ClickUp Member.
     - `dueDate` (string, optional): Due Date - Specify a date for this task to be due on.
     - `additionalFields` (string, optional): Additional Fields - Specify additional fields to include on this task as JSON.
+
   </Accordion>
 
   <Accordion title="clickup/update_task">
@@ -110,6 +115,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `assignees` (string, optional): Assignees - Select a Member (or an array of member IDs) to be assigned to this task. Use Connect Portal User Settings to allow users to select a ClickUp Member.
     - `dueDate` (string, optional): Due Date - Specify a date for this task to be due on.
     - `additionalFields` (string, optional): Additional Fields - Specify additional fields to include on this task as JSON.
+
   </Accordion>
 
   <Accordion title="clickup/delete_task">
@@ -117,6 +123,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `taskId` (string, required): Task ID - The ID of the task to delete.
+
   </Accordion>
 
   <Accordion title="clickup/get_list">
@@ -124,6 +131,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `spaceId` (string, required): Space ID - The ID of the space containing the lists.
+
   </Accordion>
 
   <Accordion title="clickup/get_custom_fields_in_list">
@@ -131,6 +139,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `listId` (string, required): List ID - The ID of the list to get custom fields from.
+
   </Accordion>
 
   <Accordion title="clickup/get_all_fields_in_list">
@@ -138,6 +147,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `listId` (string, required): List ID - The ID of the list to get all fields from.
+
   </Accordion>
 
   <Accordion title="clickup/get_space">
@@ -145,6 +155,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `spaceId` (string, optional): Space ID - The ID of the space to retrieve.
+
   </Accordion>
 
   <Accordion title="clickup/get_folders">
@@ -152,12 +163,14 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `spaceId` (string, required): Space ID - The ID of the space containing the folders.
+
   </Accordion>
 
   <Accordion title="clickup/get_member">
     **Description:** Get Member information in ClickUp.
 
     **Parameters:** None required.
+
   </Accordion>
 </AccordionGroup>
 
@@ -284,5 +297,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with ClickUp integration setup or troubleshooting.
+  Contact our support team for assistance with ClickUp integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/github.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage repositories, issues, and releases through GitHub.
 
 Before using the GitHub integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A GitHub account with appropriate repository permissions
 - Connected your GitHub account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the GitHub integration, ensure you have:
 
 ### 1. Connect Your GitHub Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **GitHub** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for repository and issue management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -61,6 +63,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `title` (string, required): Issue Title - Specify the title of the issue to create.
     - `body` (string, optional): Issue Body - Specify the body contents of the issue to create.
     - `assignees` (string, optional): Assignees - Specify the assignee(s)' GitHub login as an array of strings for this issue. (example: `["octocat"]`).
+
   </Accordion>
 
   <Accordion title="github/update_issue">
@@ -75,6 +78,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `assignees` (string, optional): Assignees - Specify the assignee(s)' GitHub login as an array of strings for this issue. (example: `["octocat"]`).
     - `state` (string, optional): State - Specify the updated state of the issue.
       - Options: `open`, `closed`
+
   </Accordion>
 
   <Accordion title="github/get_issue_by_number">
@@ -84,6 +88,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `owner` (string, required): Owner - Specify the name of the account owner of the associated repository for this Issue. (example: "abc").
     - `repo` (string, required): Repository - Specify the name of the associated repository for this Issue.
     - `issue_number` (string, required): Issue Number - Specify the number of the issue to fetch.
+
   </Accordion>
 
   <Accordion title="github/lock_issue">
@@ -95,6 +100,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `issue_number` (string, required): Issue Number - Specify the number of the issue to lock.
     - `lock_reason` (string, required): Lock Reason - Specify a reason for locking the issue or pull request conversation.
       - Options: `off-topic`, `too heated`, `resolved`, `spam`
+
   </Accordion>
 
   <Accordion title="github/search_issue">
@@ -122,6 +128,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       }
       ```
       Available fields: `assignee`, `creator`, `mentioned`, `labels`
+
   </Accordion>
 
   <Accordion title="github/create_release">
@@ -140,6 +147,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `discussion_category_name` (string, optional): Discussion Category Name - If specified, a discussion of the specified category is created and linked to the release. The value must be a category that already exists in the repository.
     - `generate_release_notes` (string, optional): Release Notes - Specify whether the created release should automatically create release notes using the provided name and body specified.
       - Options: `true`, `false`
+
   </Accordion>
 
   <Accordion title="github/update_release">
@@ -159,6 +167,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `discussion_category_name` (string, optional): Discussion Category Name - If specified, a discussion of the specified category is created and linked to the release. The value must be a category that already exists in the repository.
     - `generate_release_notes` (string, optional): Release Notes - Specify whether the created release should automatically create release notes using the provided name and body specified.
       - Options: `true`, `false`
+
   </Accordion>
 
   <Accordion title="github/get_release_by_id">
@@ -168,6 +177,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `owner` (string, required): Owner - Specify the name of the account owner of the associated repository for this Release. (example: "abc").
     - `repo` (string, required): Repository - Specify the name of the associated repository for this Release.
     - `id` (string, required): Release ID - Specify the release ID of the release to fetch.
+
   </Accordion>
 
   <Accordion title="github/get_release_by_tag_name">
@@ -177,6 +187,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `owner` (string, required): Owner - Specify the name of the account owner of the associated repository for this Release. (example: "abc").
     - `repo` (string, required): Repository - Specify the name of the associated repository for this Release.
     - `tag_name` (string, required): Name - Specify the tag of the release to fetch. (example: "v1.0.0").
+
   </Accordion>
 
   <Accordion title="github/delete_release">
@@ -186,6 +197,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `owner` (string, required): Owner - Specify the name of the account owner of the associated repository for this Release. (example: "abc").
     - `repo` (string, required): Repository - Specify the name of the associated repository for this Release.
     - `id` (string, required): Release ID - Specify the ID of the release to delete.
+
   </Accordion>
 </AccordionGroup>
 
@@ -314,5 +326,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with GitHub integration setup or troubleshooting.
+  Contact our support team for assistance with GitHub integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/gmail.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage emails, contacts, and drafts through Gmail. Send em
 
 Before using the Gmail integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Gmail account with appropriate permissions
 - Connected your Gmail account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Gmail integration, ensure you have:
 
 ### 1. Connect Your Gmail Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Gmail** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for email and contact management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -62,6 +64,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `pageToken` (string, optional): Page token to retrieve a specific page of results.
     - `labelIds` (array, optional): Only return messages with labels that match all of the specified label IDs.
     - `includeSpamTrash` (boolean, optional): Include messages from SPAM and TRASH in the results. (default: false)
+
   </Accordion>
 
   <Accordion title="gmail/send_email">
@@ -77,6 +80,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `from` (string, optional): Sender email address (if different from authenticated user).
     - `replyTo` (string, optional): Reply-to email address.
     - `threadId` (string, optional): Thread ID if replying to an existing conversation.
+
   </Accordion>
 
   <Accordion title="gmail/delete_email">
@@ -85,6 +89,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `userId` (string, required): The user's email address or 'me' for the authenticated user.
     - `id` (string, required): The ID of the message to delete.
+
   </Accordion>
 
   <Accordion title="gmail/create_draft">
@@ -94,6 +99,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `userId` (string, required): The user's email address or 'me' for the authenticated user.
     - `message` (object, required): Message object containing the draft content.
       - `raw` (string, required): Base64url encoded email message.
+
   </Accordion>
 
   <Accordion title="gmail/get_message">
@@ -104,6 +110,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `id` (string, required): The ID of the message to retrieve.
     - `format` (string, optional): The format to return the message in. Options: "full", "metadata", "minimal", "raw". (default: "full")
     - `metadataHeaders` (array, optional): When given and format is METADATA, only include headers specified.
+
   </Accordion>
 
   <Accordion title="gmail/get_attachment">
@@ -113,6 +120,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `userId` (string, required): The user's email address or 'me' for the authenticated user. (default: "me")
     - `messageId` (string, required): The ID of the message containing the attachment.
     - `id` (string, required): The ID of the attachment to retrieve.
+
   </Accordion>
 
   <Accordion title="gmail/fetch_thread">
@@ -123,6 +131,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `id` (string, required): The ID of the thread to retrieve.
     - `format` (string, optional): The format to return the messages in. Options: "full", "metadata", "minimal". (default: "full")
     - `metadataHeaders` (array, optional): When given and format is METADATA, only include headers specified.
+
   </Accordion>
 
   <Accordion title="gmail/modify_thread">
@@ -133,6 +142,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `id` (string, required): The ID of the thread to modify.
     - `addLabelIds` (array, optional): A list of IDs of labels to add to this thread.
     - `removeLabelIds` (array, optional): A list of IDs of labels to remove from this thread.
+
   </Accordion>
 
   <Accordion title="gmail/trash_thread">
@@ -141,6 +151,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `userId` (string, required): The user's email address or 'me' for the authenticated user. (default: "me")
     - `id` (string, required): The ID of the thread to trash.
+
   </Accordion>
 
   <Accordion title="gmail/untrash_thread">
@@ -149,6 +160,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `userId` (string, required): The user's email address or 'me' for the authenticated user. (default: "me")
     - `id` (string, required): The ID of the thread to untrash.
+
   </Accordion>
 </AccordionGroup>
 
@@ -286,5 +298,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Gmail integration setup or troubleshooting.
+  Contact our support team for assistance with Gmail integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/google_calendar.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage calendar events, schedules, and availability throug
 
 Before using the Google Calendar integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Google account with Google Calendar access
 - Connected your Google account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Google Calendar integration, ensure you have:
 
 ### 1. Connect Your Google Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Google Calendar** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for calendar access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -69,6 +71,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `timeZone` (string, optional): Time zone used in the response. The default is UTC.
     - `groupExpansionMax` (integer, optional): Maximal number of calendar identifiers to be provided for a single group. Maximum: 100
     - `calendarExpansionMax` (integer, optional): Maximal number of calendars for which FreeBusy information is to be provided. Maximum: 50
+
   </Accordion>
 
   <Accordion title="google_calendar/create_event">
@@ -117,6 +120,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       ```
     - `visibility` (string, optional): Visibility of the event. Options: default, public, private, confidential. Default: default
     - `transparency` (string, optional): Whether the event blocks time on the calendar. Options: opaque, transparent. Default: opaque
+
   </Accordion>
 
   <Accordion title="google_calendar/view_events">
@@ -136,6 +140,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `timeZone` (string, optional): Time zone used in the response.
     - `updatedMin` (string, optional): Lower bound for an event's last modification time (RFC3339) to filter by.
     - `iCalUID` (string, optional): Specifies an event ID in the iCalendar format to be provided in the response.
+
   </Accordion>
 
   <Accordion title="google_calendar/update_event">
@@ -148,6 +153,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `description` (string, optional): Updated event description
     - `start_dateTime` (string, optional): Updated start time
     - `end_dateTime` (string, optional): Updated end time
+
   </Accordion>
 
   <Accordion title="google_calendar/delete_event">
@@ -156,6 +162,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `calendarId` (string, required): Calendar ID
     - `eventId` (string, required): Event ID to delete
+
   </Accordion>
 
   <Accordion title="google_calendar/view_calendar_list">
@@ -167,6 +174,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `showDeleted` (boolean, optional): Whether to include deleted calendar list entries in the result. Default: false
     - `showHidden` (boolean, optional): Whether to show hidden entries. Default: false
     - `minAccessRole` (string, optional): The minimum access role for the user in the returned entries. Options: freeBusyReader, owner, reader, writer
+
   </Accordion>
 </AccordionGroup>
 
@@ -327,22 +335,26 @@ crew.kickoff()
 ### Common Issues
 
 **Authentication Errors**
+
 - Ensure your Google account has the necessary permissions for calendar access
 - Verify that the OAuth connection includes all required scopes for Google Calendar API
 - Check if calendar sharing settings allow the required access level
 
 **Event Creation Issues**
+
 - Verify that time formats are correct (RFC3339 format)
 - Ensure attendee email addresses are properly formatted
 - Check that the target calendar exists and is accessible
 - Verify time zones are correctly specified
 
 **Availability and Time Conflicts**
+
 - Use proper RFC3339 format for time ranges when checking availability
 - Ensure time zones are consistent across all operations
 - Verify that calendar IDs are correct when checking multiple calendars
 
 **Event Updates and Deletions**
+
 - Verify that event IDs are correct and events exist
 - Ensure you have edit permissions for the events
 - Check that calendar ownership allows modifications
@@ -350,5 +362,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Google Calendar integration setup or troubleshooting.
+  Contact our support team for assistance with Google Calendar integration setup
+  or troubleshooting.
 </Card>

docs/en/enterprise/integrations/google_contacts.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage contacts and directory information through Google C
 
 Before using the Google Contacts integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Google account with Google Contacts access
 - Connected your Google account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Google Contacts integration, ensure you have:
 
 ### 1. Connect Your Google Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Google Contacts** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for contacts and directory access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -61,6 +63,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `personFields` (string, optional): Fields to include (e.g., 'names,emailAddresses,phoneNumbers'). Default: names,emailAddresses,phoneNumbers
     - `requestSyncToken` (boolean, optional): Whether the response should include a sync token. Default: false
     - `sortOrder` (string, optional): The order in which the connections should be sorted. Options: LAST_MODIFIED_ASCENDING, LAST_MODIFIED_DESCENDING, FIRST_NAME_ASCENDING, LAST_NAME_ASCENDING
+
   </Accordion>
 
   <Accordion title="google_contacts/search_contacts">
@@ -72,6 +75,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `pageSize` (integer, optional): Number of results to return. Minimum: 1, Maximum: 30
     - `pageToken` (string, optional): Token specifying which result page to return.
     - `sources` (array, optional): The sources to search in. Options: READ_SOURCE_TYPE_CONTACT, READ_SOURCE_TYPE_PROFILE. Default: READ_SOURCE_TYPE_CONTACT
+
   </Accordion>
 
   <Accordion title="google_contacts/list_directory_people">
@@ -84,6 +88,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `readMask` (string, optional): Fields to read (e.g., 'names,emailAddresses')
     - `requestSyncToken` (boolean, optional): Whether the response should include a sync token. Default: false
     - `mergeSources` (array, optional): Additional data to merge into the directory people responses. Options: CONTACT
+
   </Accordion>
 
   <Accordion title="google_contacts/search_directory_people">
@@ -94,6 +99,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `sources` (string, required): Directory sources (use 'DIRECTORY_SOURCE_TYPE_DOMAIN_PROFILE')
     - `pageSize` (integer, optional): Number of results to return
     - `readMask` (string, optional): Fields to read
+
   </Accordion>
 
   <Accordion title="google_contacts/list_other_contacts">
@@ -104,6 +110,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `pageToken` (string, optional): Token specifying which result page to return.
     - `readMask` (string, optional): Fields to read
     - `requestSyncToken` (boolean, optional): Whether the response should include a sync token. Default: false
+
   </Accordion>
 
   <Accordion title="google_contacts/search_other_contacts">
@@ -113,6 +120,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `query` (string, required): Search query
     - `readMask` (string, required): Fields to read (e.g., 'names,emailAddresses')
     - `pageSize` (integer, optional): Number of results
+
   </Accordion>
 
   <Accordion title="google_contacts/get_person">
@@ -121,6 +129,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `resourceName` (string, required): The resource name of the person to get (e.g., 'people/c123456789')
     - `personFields` (string, optional): Fields to include (e.g., 'names,emailAddresses,phoneNumbers'). Default: names,emailAddresses,phoneNumbers
+
   </Accordion>
 
   <Accordion title="google_contacts/create_contact">
@@ -174,6 +183,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         }
       ]
       ```
+
   </Accordion>
 
   <Accordion title="google_contacts/update_contact">
@@ -185,6 +195,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `names` (array, optional): Person's names
     - `emailAddresses` (array, optional): Email addresses
     - `phoneNumbers` (array, optional): Phone numbers
+
   </Accordion>
 
   <Accordion title="google_contacts/delete_contact">
@@ -192,6 +203,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `resourceName` (string, required): The resource name of the person to delete (e.g., 'people/c123456789')
+
   </Accordion>
 
   <Accordion title="google_contacts/batch_get_people">
@@ -200,6 +212,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `resourceNames` (array, required): Resource names of people to get. Maximum: 200 items
     - `personFields` (string, optional): Fields to include (e.g., 'names,emailAddresses,phoneNumbers'). Default: names,emailAddresses,phoneNumbers
+
   </Accordion>
 
   <Accordion title="google_contacts/list_contact_groups">
@@ -209,6 +222,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `pageSize` (integer, optional): Number of contact groups to return. Minimum: 1, Maximum: 1000
     - `pageToken` (string, optional): Token specifying which result page to return.
     - `groupFields` (string, optional): Fields to include (e.g., 'name,memberCount,clientData'). Default: name,memberCount
+
   </Accordion>
 </AccordionGroup>
 
@@ -377,36 +391,43 @@ crew.kickoff()
 ### Common Issues
 
 **Permission Errors**
+
 - Ensure your Google account has appropriate permissions for contacts access
 - Verify that the OAuth connection includes required scopes for Google Contacts API
 - Check that directory access permissions are granted for organization contacts
 
 **Resource Name Format Issues**
+
 - Ensure resource names follow the correct format (e.g., 'people/c123456789' for contacts)
 - Verify that contact group resource names use the format 'contactGroups/groupId'
 - Check that resource names exist and are accessible
 
 **Search and Query Issues**
+
 - Ensure search queries are properly formatted and not empty
 - Use appropriate readMask fields for the data you need
 - Verify that search sources are correctly specified (contacts vs profiles)
 
 **Contact Creation and Updates**
+
 - Ensure required fields are provided when creating contacts
 - Verify that email addresses and phone numbers are properly formatted
 - Check that updatePersonFields parameter includes all fields being updated
 
 **Directory Access Issues**
+
 - Ensure you have appropriate permissions to access organization directory
 - Verify that directory sources are correctly specified
 - Check that your organization allows API access to directory information
 
 **Pagination and Limits**
+
 - Be mindful of page size limits (varies by endpoint)
 - Use pageToken for pagination through large result sets
 - Respect API rate limits and implement appropriate delays
 
 **Contact Groups and Organization**
+
 - Ensure contact group names are unique when creating new groups
 - Verify that contacts exist before adding them to groups
 - Check that you have permissions to modify contact groups
@@ -414,5 +435,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Google Contacts integration setup or troubleshooting.
+  Contact our support team for assistance with Google Contacts integration setup
+  or troubleshooting.
 </Card>

docs/en/enterprise/integrations/google_docs.mdx

@@ -13,7 +13,7 @@ Enable your agents to create, edit, and manage Google Docs documents with text m
 
 Before using the Google Docs integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Google account with Google Docs access
 - Connected your Google account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Google Docs integration, ensure you have:
 
 ### 1. Connect Your Google Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Google Docs** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for document access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -57,6 +59,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `title` (string, optional): The title for the new document.
+
   </Accordion>
 
   <Accordion title="google_docs/get_document">
@@ -66,6 +69,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `documentId` (string, required): The ID of the document to retrieve.
     - `includeTabsContent` (boolean, optional): Whether to include tab content. Default is `false`.
     - `suggestionsViewMode` (string, optional): The suggestions view mode to apply to the document. Enum: `DEFAULT_FOR_CURRENT_ACCESS`, `PREVIEW_SUGGESTIONS_ACCEPTED`, `PREVIEW_WITHOUT_SUGGESTIONS`. Default is `DEFAULT_FOR_CURRENT_ACCESS`.
+
   </Accordion>
 
   <Accordion title="google_docs/batch_update">
@@ -75,6 +79,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `documentId` (string, required): The ID of the document to update.
     - `requests` (array, required): A list of updates to apply to the document. Each item is an object representing a request.
     - `writeControl` (object, optional): Provides control over how write requests are executed. Contains `requiredRevisionId` (string) and `targetRevisionId` (string).
+
   </Accordion>
 
   <Accordion title="google_docs/insert_text">
@@ -84,6 +89,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `documentId` (string, required): The ID of the document to update.
     - `text` (string, required): The text to insert.
     - `index` (integer, optional): The zero-based index where to insert the text. Default is `1`.
+
   </Accordion>
 
   <Accordion title="google_docs/replace_text">
@@ -94,6 +100,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `containsText` (string, required): The text to find and replace.
     - `replaceText` (string, required): The text to replace it with.
     - `matchCase` (boolean, optional): Whether the search should respect case. Default is `false`.
+
   </Accordion>
 
   <Accordion title="google_docs/delete_content_range">
@@ -103,6 +110,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `documentId` (string, required): The ID of the document to update.
     - `startIndex` (integer, required): The start index of the range to delete.
     - `endIndex` (integer, required): The end index of the range to delete.
+
   </Accordion>
 
   <Accordion title="google_docs/insert_page_break">
@@ -111,6 +119,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `documentId` (string, required): The ID of the document to update.
     - `index` (integer, optional): The zero-based index where to insert the page break. Default is `1`.
+
   </Accordion>
 
   <Accordion title="google_docs/create_named_range">
@@ -121,6 +130,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `name` (string, required): The name for the named range.
     - `startIndex` (integer, required): The start index of the range.
     - `endIndex` (integer, required): The end index of the range.
+
   </Accordion>
 </AccordionGroup>
 
@@ -216,29 +226,35 @@ crew.kickoff()
 ### Common Issues
 
 **Authentication Errors**
+
 - Ensure your Google account has the necessary permissions for Google Docs access.
 - Verify that the OAuth connection includes all required scopes (`https://www.googleapis.com/auth/documents`).
 
 **Document ID Issues**
+
 - Double-check document IDs for correctness.
 - Ensure the document exists and is accessible to your account.
 - Document IDs can be found in the Google Docs URL.
 
 **Text Insertion and Range Operations**
+
 - When using `insert_text` or `delete_content_range`, ensure index positions are valid.
 - Remember that Google Docs uses zero-based indexing.
 - The document must have content at the specified index positions.
 
 **Batch Update Request Formatting**
+
 - When using `batch_update`, ensure the `requests` array is correctly formatted according to the Google Docs API documentation.
 - Complex updates require specific JSON structures for each request type.
 
 **Replace Text Operations**
+
 - For `replace_text`, ensure the `containsText` parameter exactly matches the text you want to replace.
 - Use `matchCase` parameter to control case sensitivity.
 
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Google Docs integration setup or troubleshooting.
+  Contact our support team for assistance with Google Docs integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/google_drive.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage files and folders through Google Drive. Upload, dow
 
 Before using the Google Drive integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Google account with Google Drive access
 - Connected your Google account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Google Drive integration, ensure you have:
 
 ### 1. Connect Your Google Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Google Drive** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for file and folder management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -57,6 +59,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `file_id` (string, required): The ID of the file to retrieve.
+
   </Accordion>
 
   <Accordion title="google_drive/list_files">
@@ -68,6 +71,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `page_token` (string, optional): Token for retrieving the next page of results.
     - `order_by` (string, optional): Sort order (example: "name", "createdTime desc", "modifiedTime").
     - `spaces` (string, optional): Comma-separated list of spaces to query (drive, appDataFolder, photos).
+
   </Accordion>
 
   <Accordion title="google_drive/upload_file">
@@ -79,6 +83,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `mime_type` (string, optional): MIME type of the file (example: "text/plain", "application/pdf").
     - `parent_folder_id` (string, optional): ID of the parent folder where the file should be created.
     - `description` (string, optional): Description of the file.
+
   </Accordion>
 
   <Accordion title="google_drive/download_file">
@@ -87,6 +92,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file_id` (string, required): The ID of the file to download.
     - `mime_type` (string, optional): MIME type for export (required for Google Workspace documents).
+
   </Accordion>
 
   <Accordion title="google_drive/create_folder">
@@ -96,6 +102,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `name` (string, required): Name of the folder to create.
     - `parent_folder_id` (string, optional): ID of the parent folder where the new folder should be created.
     - `description` (string, optional): Description of the folder.
+
   </Accordion>
 
   <Accordion title="google_drive/delete_file">
@@ -103,6 +110,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `file_id` (string, required): The ID of the file to delete.
+
   </Accordion>
 
   <Accordion title="google_drive/share_file">
@@ -116,6 +124,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `domain` (string, optional): The domain to share with (required for domain type).
     - `send_notification_email` (boolean, optional): Whether to send a notification email (default: true).
     - `email_message` (string, optional): A plain text custom message to include in the notification email.
+
   </Accordion>
 
   <Accordion title="google_drive/update_file">
@@ -129,6 +138,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `description` (string, optional): New description for the file.
     - `add_parents` (string, optional): Comma-separated list of parent folder IDs to add.
     - `remove_parents` (string, optional): Comma-separated list of parent folder IDs to remove.
+
   </Accordion>
 </AccordionGroup>
 

docs/en/enterprise/integrations/google_sheets.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage spreadsheet data through Google Sheets. Read rows,
 
 Before using the Google Sheets integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Google account with Google Sheets access
 - Connected your Google account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 - Spreadsheets with proper column headers for data operations
@@ -22,7 +22,7 @@ Before using the Google Sheets integration, ensure you have:
 
 ### 1. Connect Your Google Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Google Sheets** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for spreadsheet access
@@ -37,7 +37,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -61,6 +63,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `ranges` (array, optional): The ranges to retrieve from the spreadsheet.
     - `includeGridData` (boolean, optional): True if grid data should be returned. Default: false
     - `fields` (string, optional): The fields to include in the response. Use this to improve performance by only returning needed data.
+
   </Accordion>
 
   <Accordion title="google_sheets/get_values">
@@ -72,6 +75,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `valueRenderOption` (string, optional): How values should be represented in the output. Options: FORMATTED_VALUE, UNFORMATTED_VALUE, FORMULA. Default: FORMATTED_VALUE
     - `dateTimeRenderOption` (string, optional): How dates, times, and durations should be represented in the output. Options: SERIAL_NUMBER, FORMATTED_STRING. Default: SERIAL_NUMBER
     - `majorDimension` (string, optional): The major dimension that results should use. Options: ROWS, COLUMNS. Default: ROWS
+
   </Accordion>
 
   <Accordion title="google_sheets/update_values">
@@ -88,6 +92,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       ]
       ```
     - `valueInputOption` (string, optional): How the input data should be interpreted. Options: RAW, USER_ENTERED. Default: USER_ENTERED
+
   </Accordion>
 
   <Accordion title="google_sheets/append_values">
@@ -105,6 +110,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       ```
     - `valueInputOption` (string, optional): How the input data should be interpreted. Options: RAW, USER_ENTERED. Default: USER_ENTERED
     - `insertDataOption` (string, optional): How the input data should be inserted. Options: OVERWRITE, INSERT_ROWS. Default: INSERT_ROWS
+
   </Accordion>
 
   <Accordion title="google_sheets/create_spreadsheet">
@@ -122,6 +128,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         }
       ]
       ```
+
   </Accordion>
 </AccordionGroup>
 
@@ -319,31 +326,37 @@ crew.kickoff()
 ### Common Issues
 
 **Permission Errors**
+
 - Ensure your Google account has edit access to the target spreadsheets
 - Verify that the OAuth connection includes required scopes for Google Sheets API
 - Check that spreadsheets are shared with the authenticated account
 
 **Spreadsheet Structure Issues**
+
 - Ensure worksheets have proper column headers before creating or updating rows
 - Verify that range notation (A1 format) is correct for the target cells
 - Check that the specified spreadsheet ID exists and is accessible
 
 **Data Type and Format Issues**
+
 - Ensure data values match the expected format for each column
 - Use proper date formats for date columns (ISO format recommended)
 - Verify that numeric values are properly formatted for number columns
 
 **Range and Cell Reference Issues**
+
 - Use proper A1 notation for ranges (e.g., "A1:C10", "Sheet1!A1:B5")
 - Ensure range references don't exceed the actual spreadsheet dimensions
 - Verify that sheet names in range references match actual sheet names
 
 **Value Input and Rendering Options**
+
 - Choose appropriate `valueInputOption` (RAW vs USER_ENTERED) for your data
 - Select proper `valueRenderOption` based on how you want data formatted
 - Consider `dateTimeRenderOption` for consistent date/time handling
 
 **Spreadsheet Creation Issues**
+
 - Ensure spreadsheet titles are unique and follow naming conventions
 - Verify that sheet properties are properly structured when creating sheets
 - Check that you have permissions to create new spreadsheets in your account
@@ -351,5 +364,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Google Sheets integration setup or troubleshooting.
+  Contact our support team for assistance with Google Sheets integration setup
+  or troubleshooting.
 </Card>

docs/en/enterprise/integrations/google_slides.mdx

@@ -13,7 +13,7 @@ Enable your agents to create, edit, and manage Google Slides presentations. Crea
 
 Before using the Google Slides integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Google account with Google Slides access
 - Connected your Google account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Google Slides integration, ensure you have:
 
 ### 1. Connect Your Google Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Google Slides** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for presentations, spreadsheets, and drive access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -57,6 +59,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `title` (string, required): The title of the presentation.
+
   </Accordion>
 
   <Accordion title="google_slides/get_presentation">
@@ -65,6 +68,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `presentationId` (string, required): The ID of the presentation to retrieve.
     - `fields` (string, optional): The fields to include in the response. Use this to improve performance by only returning needed data.
+
   </Accordion>
 
   <Accordion title="google_slides/batch_update_presentation">
@@ -89,6 +93,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "requiredRevisionId": "revision_id_string"
       }
       ```
+
   </Accordion>
 
   <Accordion title="google_slides/get_page">
@@ -97,6 +102,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `presentationId` (string, required): The ID of the presentation.
     - `pageObjectId` (string, required): The ID of the page to retrieve.
+
   </Accordion>
 
   <Accordion title="google_slides/get_thumbnail">
@@ -105,6 +111,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `presentationId` (string, required): The ID of the presentation.
     - `pageObjectId` (string, required): The ID of the page for thumbnail generation.
+
   </Accordion>
 
   <Accordion title="google_slides/import_data_from_sheet">
@@ -114,6 +121,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `presentationId` (string, required): The ID of the presentation.
     - `sheetId` (string, required): The ID of the Google Sheet to import from.
     - `dataRange` (string, required): The range of data to import from the sheet.
+
   </Accordion>
 
   <Accordion title="google_slides/upload_file_to_drive">
@@ -122,6 +130,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file` (string, required): The file data to upload.
     - `presentationId` (string, required): The ID of the presentation to link the uploaded file.
+
   </Accordion>
 
   <Accordion title="google_slides/link_file_to_presentation">
@@ -130,6 +139,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `presentationId` (string, required): The ID of the presentation.
     - `fileId` (string, required): The ID of the file to link.
+
   </Accordion>
 
   <Accordion title="google_slides/get_all_presentations">
@@ -138,6 +148,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `pageSize` (integer, optional): The number of presentations to return per page.
     - `pageToken` (string, optional): A token for pagination.
+
   </Accordion>
 
   <Accordion title="google_slides/delete_presentation">
@@ -145,6 +156,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `presentationId` (string, required): The ID of the presentation to delete.
+
   </Accordion>
 </AccordionGroup>
 
@@ -346,36 +358,43 @@ crew.kickoff()
 ### Common Issues
 
 **Permission Errors**
+
 - Ensure your Google account has appropriate permissions for Google Slides
 - Verify that the OAuth connection includes required scopes for presentations, spreadsheets, and drive access
 - Check that presentations are shared with the authenticated account
 
 **Presentation ID Issues**
+
 - Verify that presentation IDs are correct and presentations exist
 - Ensure you have access permissions to the presentations you're trying to modify
 - Check that presentation IDs are properly formatted
 
 **Content Update Issues**
+
 - Ensure batch update requests are properly formatted according to Google Slides API specifications
 - Verify that object IDs for slides and elements exist in the presentation
 - Check that write control revision IDs are current if using optimistic concurrency
 
 **Data Import Issues**
+
 - Verify that Google Sheet IDs are correct and accessible
 - Ensure data ranges are properly specified using A1 notation
 - Check that you have read permissions for the source spreadsheets
 
 **File Upload and Linking Issues**
+
 - Ensure file data is properly encoded for upload
 - Verify that Drive file IDs are correct when linking files
 - Check that you have appropriate Drive permissions for file operations
 
 **Page and Thumbnail Operations**
+
 - Verify that page object IDs exist in the specified presentation
 - Ensure presentations have content before attempting to generate thumbnails
 - Check that page structure is valid for thumbnail generation
 
 **Pagination and Listing Issues**
+
 - Use appropriate page sizes for listing presentations
 - Implement proper pagination using page tokens for large result sets
 - Handle empty result sets gracefully
@@ -383,5 +402,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Google Slides integration setup or troubleshooting.
+  Contact our support team for assistance with Google Slides integration setup
+  or troubleshooting.
 </Card>

docs/en/enterprise/integrations/hubspot.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage companies and contacts within HubSpot. Create new r
 
 Before using the HubSpot integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription.
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription.
 - A HubSpot account with appropriate permissions.
 - Connected your HubSpot account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors).
 
@@ -21,7 +21,7 @@ Before using the HubSpot integration, ensure you have:
 
 ### 1. Connect Your HubSpot Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors).
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors).
 2. Find **HubSpot** in the Authentication Integrations section.
 3. Click **Connect** and complete the OAuth flow.
 4. Grant the necessary permissions for company and contact management.
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -115,6 +117,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `web_technologies` (string, optional): Web Technologies used. Must be one of the predefined values.
     - `website` (string, optional): Website URL.
     - `founded_year` (string, optional): Year Founded.
+
   </Accordion>
 
   <Accordion title="hubspot/create_contact">
@@ -214,6 +217,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `hs_whatsapp_phone_number` (string, optional): WhatsApp Phone Number.
     - `work_email` (string, optional): Work email.
     - `hs_googleplusid` (string, optional): googleplus ID.
+
   </Accordion>
 
   <Accordion title="hubspot/create_deal">
@@ -229,6 +233,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `dealtype` (string, optional): The type of deal. Available values: `newbusiness`, `existingbusiness`.
     - `description` (string, optional): A description of the deal.
     - `hs_priority` (string, optional): The priority of the deal. Available values: `low`, `medium`, `high`.
+
   </Accordion>
 
   <Accordion title="hubspot/create_record_engagements">
@@ -246,6 +251,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `hs_meeting_body` (string, optional): The description for the meeting. (Used for `MEETING`)
     - `hs_meeting_start_time` (string, optional): The start time of the meeting. (Used for `MEETING`)
     - `hs_meeting_end_time` (string, optional): The end time of the meeting. (Used for `MEETING`)
+
   </Accordion>
 
   <Accordion title="hubspot/update_company">
@@ -263,6 +269,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `numberofemployees` (number, optional): Number of Employees.
     - `annualrevenue` (number, optional): Annual Revenue.
     - `description` (string, optional): Description.
+
   </Accordion>
 
   <Accordion title="hubspot/create_record_any">
@@ -271,6 +278,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `recordType` (string, required): The object type ID of the custom object.
     - Additional parameters depend on the custom object's schema.
+
   </Accordion>
 
   <Accordion title="hubspot/update_contact">
@@ -285,6 +293,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `company` (string, optional): Company Name.
     - `jobtitle` (string, optional): Job Title.
     - `lifecyclestage` (string, optional): Lifecycle Stage.
+
   </Accordion>
 
   <Accordion title="hubspot/update_deal">
@@ -298,6 +307,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `pipeline` (string, optional): The pipeline the deal belongs to.
     - `closedate` (string, optional): The date the deal is expected to close.
     - `dealtype` (string, optional): The type of deal.
+
   </Accordion>
 
   <Accordion title="hubspot/update_record_engagements">
@@ -309,6 +319,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `hs_task_subject` (string, optional): The title of the task.
     - `hs_task_body` (string, optional): The notes for the task.
     - `hs_task_status` (string, optional): The status of the task.
+
   </Accordion>
 
   <Accordion title="hubspot/update_record_any">
@@ -318,6 +329,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `recordId` (string, required): The ID of the record to update.
     - `recordType` (string, required): The object type ID of the custom object.
     - Additional parameters depend on the custom object's schema.
+
   </Accordion>
 
   <Accordion title="hubspot/list_companies">
@@ -325,6 +337,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/list_contacts">
@@ -332,6 +345,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/list_deals">
@@ -339,6 +353,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/get_records_engagements">
@@ -347,6 +362,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `objectName` (string, required): The type of engagement to fetch (e.g., "notes").
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/get_records_any">
@@ -355,6 +371,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `recordType` (string, required): The object type ID of the custom object.
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/get_company">
@@ -362,6 +379,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): The ID of the company to retrieve.
+
   </Accordion>
 
   <Accordion title="hubspot/get_contact">
@@ -369,6 +387,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): The ID of the contact to retrieve.
+
   </Accordion>
 
   <Accordion title="hubspot/get_deal">
@@ -376,6 +395,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): The ID of the deal to retrieve.
+
   </Accordion>
 
   <Accordion title="hubspot/get_record_by_id_engagements">
@@ -383,6 +403,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): The ID of the engagement to retrieve.
+
   </Accordion>
 
   <Accordion title="hubspot/get_record_by_id_any">
@@ -391,6 +412,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `recordType` (string, required): The object type ID of the custom object.
     - `recordId` (string, required): The ID of the record to retrieve.
+
   </Accordion>
 
   <Accordion title="hubspot/search_companies">
@@ -399,6 +421,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `filterFormula` (object, optional): A filter in disjunctive normal form (OR of ANDs).
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/search_contacts">
@@ -407,6 +430,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `filterFormula` (object, optional): A filter in disjunctive normal form (OR of ANDs).
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/search_deals">
@@ -415,6 +439,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `filterFormula` (object, optional): A filter in disjunctive normal form (OR of ANDs).
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/search_records_engagements">
@@ -423,6 +448,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `engagementFilterFormula` (object, optional): A filter for engagements.
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/search_records_any">
@@ -432,6 +458,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `recordType` (string, required): The object type ID to search.
     - `filterFormula` (string, optional): The filter formula to apply.
     - `paginationParameters` (object, optional): Use `pageCursor` to fetch subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/delete_record_companies">
@@ -439,6 +466,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): The ID of the company to delete.
+
   </Accordion>
 
   <Accordion title="hubspot/delete_record_contacts">
@@ -446,6 +474,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): The ID of the contact to delete.
+
   </Accordion>
 
   <Accordion title="hubspot/delete_record_deals">
@@ -453,6 +482,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): The ID of the deal to delete.
+
   </Accordion>
 
   <Accordion title="hubspot/delete_record_engagements">
@@ -460,6 +490,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): The ID of the engagement to delete.
+
   </Accordion>
 
   <Accordion title="hubspot/delete_record_any">
@@ -468,6 +499,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `recordType` (string, required): The object type ID of the custom object.
     - `recordId` (string, required): The ID of the record to delete.
+
   </Accordion>
 
   <Accordion title="hubspot/get_contacts_by_list_id">
@@ -476,6 +508,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `listId` (string, required): The ID of the list to get contacts from.
     - `paginationParameters` (object, optional): Use `pageCursor` for subsequent pages.
+
   </Accordion>
 
   <Accordion title="hubspot/describe_action_schema">
@@ -484,6 +517,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `recordType` (string, required): The object type ID (e.g., 'companies').
     - `operation` (string, required): The operation type (e.g., 'CREATE_RECORD').
+
   </Accordion>
 </AccordionGroup>
 
@@ -577,5 +611,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with HubSpot integration setup or troubleshooting.
+  Contact our support team for assistance with HubSpot integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/jira.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage issues, projects, and workflows through Jira. Creat
 
 Before using the Jira integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Jira account with appropriate project permissions
 - Connected your Jira account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Jira integration, ensure you have:
 
 ### 1. Connect Your Jira Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Jira** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for issue and project management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -70,6 +72,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "customfield_10001": "value"
       }
       ```
+
   </Accordion>
 
   <Accordion title="jira/update_issue">
@@ -85,6 +88,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       - Options: `description`, `descriptionJSON`
     - `description` (string, optional): Description - A detailed description of the issue. This field appears only when 'descriptionType' = 'description'.
     - `additionalFields` (string, optional): Additional Fields - Specify any other fields that should be included in JSON format.
+
   </Accordion>
 
   <Accordion title="jira/get_issue_by_key">
@@ -92,6 +96,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `issueKey` (string, required): Issue Key (example: "TEST-1234").
+
   </Accordion>
 
   <Accordion title="jira/filter_issues">
@@ -118,6 +123,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       ```
       Available operators: `$stringExactlyMatches`, `$stringDoesNotExactlyMatch`, `$stringIsIn`, `$stringIsNotIn`, `$stringContains`, `$stringDoesNotContain`, `$stringGreaterThan`, `$stringLessThan`
     - `limit` (string, optional): Limit results - Limit the maximum number of issues to return. Defaults to 10 if left blank.
+
   </Accordion>
 
   <Accordion title="jira/search_by_jql">
@@ -131,12 +137,14 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "pageCursor": "cursor_string"
       }
       ```
+
   </Accordion>
 
   <Accordion title="jira/update_issue_any">
     **Description:** Update any issue in Jira. Use DESCRIBE_ACTION_SCHEMA to get properties schema for this function.
 
     **Parameters:** No specific parameters - use JIRA_DESCRIBE_ACTION_SCHEMA first to get the expected schema.
+
   </Accordion>
 
   <Accordion title="jira/describe_action_schema">
@@ -146,6 +154,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `issueTypeId` (string, required): Issue Type ID.
     - `projectKey` (string, required): Project key.
     - `operation` (string, required): Operation Type value, for example CREATE_ISSUE or UPDATE_ISSUE.
+
   </Accordion>
 
   <Accordion title="jira/get_projects">
@@ -158,6 +167,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "pageCursor": "cursor_string"
       }
       ```
+
   </Accordion>
 
   <Accordion title="jira/get_issue_types_by_project">
@@ -165,12 +175,14 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `project` (string, required): Project key.
+
   </Accordion>
 
   <Accordion title="jira/get_issue_types">
     **Description:** Get all Issue Types in Jira.
 
     **Parameters:** None required.
+
   </Accordion>
 
   <Accordion title="jira/get_issue_status_by_project">
@@ -178,6 +190,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `project` (string, required): Project key.
+
   </Accordion>
 
   <Accordion title="jira/get_all_assignees_by_project">
@@ -185,6 +198,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `project` (string, required): Project key.
+
   </Accordion>
 </AccordionGroup>
 
@@ -348,31 +362,37 @@ crew.kickoff()
 ### Common Issues
 
 **Permission Errors**
+
 - Ensure your Jira account has necessary permissions for the target projects
 - Verify that the OAuth connection includes required scopes for Jira API
 - Check if you have create/edit permissions for issues in the specified projects
 
 **Invalid Project or Issue Keys**
+
 - Double-check project keys and issue keys for correct format (e.g., "PROJ-123")
 - Ensure projects exist and are accessible to your account
 - Verify that issue keys reference existing issues
 
 **Issue Type and Status Issues**
+
 - Use JIRA_GET_ISSUE_TYPES_BY_PROJECT to get valid issue types for a project
 - Use JIRA_GET_ISSUE_STATUS_BY_PROJECT to get valid statuses
 - Ensure issue types and statuses are available in the target project
 
 **JQL Query Problems**
+
 - Test JQL queries in Jira's issue search before using in API calls
 - Ensure field names in JQL are spelled correctly and exist in your Jira instance
 - Use proper JQL syntax for complex queries
 
 **Custom Fields and Schema Issues**
+
 - Use JIRA_DESCRIBE_ACTION_SCHEMA to get the correct schema for complex issue types
 - Ensure custom field IDs are correct (e.g., "customfield_10001")
 - Verify that custom fields are available in the target project and issue type
 
 **Filter Formula Issues**
+
 - Ensure filter formulas follow the correct JSON structure for disjunctive normal form
 - Use valid field names that exist in your Jira configuration
 - Test simple filters before building complex multi-condition queries
@@ -380,5 +400,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Jira integration setup or troubleshooting.
+  Contact our support team for assistance with Jira integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/linear.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage issues, projects, and development workflows through
 
 Before using the Linear integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Linear account with appropriate workspace permissions
 - Connected your Linear account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Linear integration, ensure you have:
 
 ### 1. Connect Your Linear Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Linear** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for issue and project management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -70,6 +72,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "labelIds": ["a70bdf0f-530a-4887-857d-46151b52b47c"]
       }
       ```
+
   </Accordion>
 
   <Accordion title="linear/update_issue">
@@ -90,6 +93,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "labelIds": ["a70bdf0f-530a-4887-857d-46151b52b47c"]
       }
       ```
+
   </Accordion>
 
   <Accordion title="linear/get_issue_by_id">
@@ -97,6 +101,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `issueId` (string, required): Issue ID - Specify the record ID of the issue to fetch. (example: "90fbc706-18cd-42c9-ae66-6bd344cc8977").
+
   </Accordion>
 
   <Accordion title="linear/get_issue_by_issue_identifier">
@@ -104,6 +109,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `externalId` (string, required): External ID - Specify the human-readable Issue identifier of the issue to fetch. (example: "ABC-1").
+
   </Accordion>
 
   <Accordion title="linear/search_issue">
@@ -131,6 +137,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       ```
       Available fields: `title`, `number`, `project`, `createdAt`
       Available operators: `$stringExactlyMatches`, `$stringDoesNotExactlyMatch`, `$stringIsIn`, `$stringIsNotIn`, `$stringStartsWith`, `$stringDoesNotStartWith`, `$stringEndsWith`, `$stringDoesNotEndWith`, `$stringContains`, `$stringDoesNotContain`, `$stringGreaterThan`, `$stringLessThan`, `$numberGreaterThanOrEqualTo`, `$numberLessThanOrEqualTo`, `$numberGreaterThan`, `$numberLessThan`, `$dateTimeAfter`, `$dateTimeBefore`
+
   </Accordion>
 
   <Accordion title="linear/delete_issue">
@@ -138,6 +145,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `issueId` (string, required): Issue ID - Specify the record ID of the issue to delete. (example: "90fbc706-18cd-42c9-ae66-6bd344cc8977").
+
   </Accordion>
 
   <Accordion title="linear/archive_issue">
@@ -145,6 +153,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `issueId` (string, required): Issue ID - Specify the record ID of the issue to archive. (example: "90fbc706-18cd-42c9-ae66-6bd344cc8977").
+
   </Accordion>
 
   <Accordion title="linear/create_sub_issue">
@@ -161,6 +170,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "lead": "linear_user_id"
       }
       ```
+
   </Accordion>
 
   <Accordion title="linear/create_project">
@@ -183,6 +193,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "description": ""
       }
       ```
+
   </Accordion>
 
   <Accordion title="linear/update_project">
@@ -199,6 +210,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "description": ""
       }
       ```
+
   </Accordion>
 
   <Accordion title="linear/get_project_by_id">
@@ -206,6 +218,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `projectId` (string, required): Project ID - Specify the Project ID of the project to fetch. (example: "a6634484-6061-4ac7-9739-7dc5e52c796b").
+
   </Accordion>
 
   <Accordion title="linear/delete_project">
@@ -213,6 +226,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `projectId` (string, required): Project ID - Specify the Project ID of the project to delete. (example: "a6634484-6061-4ac7-9739-7dc5e52c796b").
+
   </Accordion>
 
   <Accordion title="linear/search_teams">
@@ -238,6 +252,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       }
       ```
       Available fields: `id`, `name`
+
   </Accordion>
 </AccordionGroup>
 
@@ -401,37 +416,44 @@ crew.kickoff()
 ### Common Issues
 
 **Permission Errors**
+
 - Ensure your Linear account has necessary permissions for the target workspace
 - Verify that the OAuth connection includes required scopes for Linear API
 - Check if you have create/edit permissions for issues and projects in the workspace
 
 **Invalid IDs and References**
+
 - Double-check team IDs, issue IDs, and project IDs for correct UUID format
 - Ensure referenced entities (teams, projects, cycles) exist and are accessible
 - Verify that issue identifiers follow the correct format (e.g., "ABC-1")
 
 **Team and Project Association Issues**
+
 - Use LINEAR_SEARCH_TEAMS to get valid team IDs before creating issues or projects
 - Ensure teams exist and are active in your workspace
 - Verify that team IDs are properly formatted as UUIDs
 
 **Issue Status and Priority Problems**
+
 - Check that status IDs reference valid workflow states for the team
 - Ensure priority values are within the valid range for your Linear configuration
 - Verify that custom fields and labels exist before referencing them
 
 **Date and Time Format Issues**
+
 - Use ISO 8601 format for due dates and timestamps
 - Ensure time zones are handled correctly for due date calculations
 - Verify that date values are valid and in the future for due dates
 
 **Search and Filter Issues**
+
 - Ensure search queries are properly formatted and not empty
 - Use valid field names in filter formulas: `title`, `number`, `project`, `createdAt`
 - Test simple filters before building complex multi-condition queries
 - Verify that operator types match the data types of the fields being filtered
 
 **Sub-issue Creation Problems**
+
 - Ensure parent issue IDs are valid and accessible
 - Verify that the team ID for sub-issues matches or is compatible with the parent issue's team
 - Check that parent issues are not already archived or deleted
@@ -439,5 +461,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Linear integration setup or troubleshooting.
+  Contact our support team for assistance with Linear integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/microsoft_excel.mdx

@@ -13,7 +13,7 @@ Enable your agents to create and manage Excel workbooks, worksheets, tables, and
 
 Before using the Microsoft Excel integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Microsoft 365 account with Excel and OneDrive/SharePoint access
 - Connected your Microsoft account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Microsoft Excel integration, ensure you have:
 
 ### 1. Connect Your Microsoft Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Microsoft Excel** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for files and Excel workbook access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -68,6 +70,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         }
       ]
       ```
+
   </Accordion>
 
   <Accordion title="microsoft_excel/get_workbooks">
@@ -79,6 +82,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `expand` (string, optional): Expand related resources inline
     - `top` (integer, optional): Number of items to return. Minimum: 1, Maximum: 999
     - `orderby` (string, optional): Order results by specified properties
+
   </Accordion>
 
   <Accordion title="microsoft_excel/get_worksheets">
@@ -91,6 +95,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `expand` (string, optional): Expand related resources inline
     - `top` (integer, optional): Number of items to return. Minimum: 1, Maximum: 999
     - `orderby` (string, optional): Order results by specified properties
+
   </Accordion>
 
   <Accordion title="microsoft_excel/create_worksheet">
@@ -99,6 +104,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file_id` (string, required): The ID of the Excel file
     - `name` (string, required): Name of the new worksheet
+
   </Accordion>
 
   <Accordion title="microsoft_excel/get_range_data">
@@ -108,6 +114,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `file_id` (string, required): The ID of the Excel file
     - `worksheet_name` (string, required): Name of the worksheet
     - `range` (string, required): Range address (e.g., 'A1:C10')
+
   </Accordion>
 
   <Accordion title="microsoft_excel/update_range_data">
@@ -125,6 +132,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         ["Jane", 25, "Los Angeles"]
       ]
       ```
+
   </Accordion>
 
   <Accordion title="microsoft_excel/add_table">
@@ -135,6 +143,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `worksheet_name` (string, required): Name of the worksheet
     - `range` (string, required): Range for the table (e.g., 'A1:D10')
     - `has_headers` (boolean, optional): Whether the first row contains headers. Default: true
+
   </Accordion>
 
   <Accordion title="microsoft_excel/get_tables">
@@ -143,6 +152,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file_id` (string, required): The ID of the Excel file
     - `worksheet_name` (string, required): Name of the worksheet
+
   </Accordion>
 
   <Accordion title="microsoft_excel/add_table_row">
@@ -156,6 +166,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
       ```json
       ["John Doe", 35, "Manager", "Sales"]
       ```
+
   </Accordion>
 
   <Accordion title="microsoft_excel/create_chart">
@@ -167,6 +178,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `chart_type` (string, required): Type of chart (e.g., 'ColumnClustered', 'Line', 'Pie')
     - `source_data` (string, required): Range of data for the chart (e.g., 'A1:B10')
     - `series_by` (string, optional): How to interpret the data ('Auto', 'Columns', or 'Rows'). Default: Auto
+
   </Accordion>
 
   <Accordion title="microsoft_excel/get_cell">
@@ -177,6 +189,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `worksheet_name` (string, required): Name of the worksheet
     - `row` (integer, required): Row number (0-based)
     - `column` (integer, required): Column number (0-based)
+
   </Accordion>
 
   <Accordion title="microsoft_excel/get_used_range">
@@ -185,6 +198,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file_id` (string, required): The ID of the Excel file
     - `worksheet_name` (string, required): Name of the worksheet
+
   </Accordion>
 
   <Accordion title="microsoft_excel/list_charts">
@@ -193,6 +207,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file_id` (string, required): The ID of the Excel file
     - `worksheet_name` (string, required): Name of the worksheet
+
   </Accordion>
 
   <Accordion title="microsoft_excel/delete_worksheet">
@@ -201,6 +216,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file_id` (string, required): The ID of the Excel file
     - `worksheet_name` (string, required): Name of the worksheet to delete
+
   </Accordion>
 
   <Accordion title="microsoft_excel/delete_table">
@@ -210,6 +226,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `file_id` (string, required): The ID of the Excel file
     - `worksheet_name` (string, required): Name of the worksheet
     - `table_name` (string, required): Name of the table to delete
+
   </Accordion>
 
   <Accordion title="microsoft_excel/list_names">
@@ -217,6 +234,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `file_id` (string, required): The ID of the Excel file
+
   </Accordion>
 </AccordionGroup>
 
@@ -421,36 +439,43 @@ crew.kickoff()
 ### Common Issues
 
 **Permission Errors**
+
 - Ensure your Microsoft account has appropriate permissions for Excel and OneDrive/SharePoint
 - Verify that the OAuth connection includes required scopes (Files.Read.All, Files.ReadWrite.All)
 - Check that you have access to the specific workbooks you're trying to modify
 
 **File ID and Path Issues**
+
 - Verify that file IDs are correct and files exist in your OneDrive or SharePoint
 - Ensure file paths are properly formatted when creating new workbooks
 - Check that workbook files have the correct .xlsx extension
 
 **Worksheet and Range Issues**
+
 - Verify that worksheet names exist in the specified workbook
 - Ensure range addresses are properly formatted (e.g., 'A1:C10')
 - Check that ranges don't exceed worksheet boundaries
 
 **Data Format Issues**
+
 - Ensure data values are properly formatted for Excel (strings, numbers, integers)
 - Verify that 2D arrays for ranges have consistent row and column counts
 - Check that table data includes proper headers when has_headers is true
 
 **Chart Creation Issues**
+
 - Verify that chart types are supported (ColumnClustered, Line, Pie, etc.)
 - Ensure source data ranges contain appropriate data for the chart type
 - Check that the source data range exists and contains data
 
 **Table Management Issues**
+
 - Ensure table names are unique within worksheets
 - Verify that table ranges don't overlap with existing tables
 - Check that new row data matches the table's column structure
 
 **Cell and Range Operations**
+
 - Verify that row and column indices are 0-based for cell operations
 - Ensure ranges contain data when using get_used_range
 - Check that named ranges exist before referencing them
@@ -458,5 +483,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Microsoft Excel integration setup or troubleshooting.
+  Contact our support team for assistance with Microsoft Excel integration setup
+  or troubleshooting.
 </Card>

docs/en/enterprise/integrations/microsoft_onedrive.mdx

@@ -13,7 +13,7 @@ Enable your agents to upload, download, and manage files and folders in Microsof
 
 Before using the Microsoft OneDrive integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Microsoft account with OneDrive access
 - Connected your Microsoft account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Microsoft OneDrive integration, ensure you have:
 
 ### 1. Connect Your Microsoft Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Microsoft OneDrive** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for file access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -59,6 +61,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `top` (integer, optional): Number of items to retrieve (max 1000). Default is `50`.
     - `orderby` (string, optional): Order by field (e.g., "name asc", "lastModifiedDateTime desc"). Default is "name asc".
     - `filter` (string, optional): OData filter expression.
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/get_file_info">
@@ -66,6 +69,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `item_id` (string, required): The ID of the file or folder.
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/download_file">
@@ -73,6 +77,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `item_id` (string, required): The ID of the file to download.
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/upload_file">
@@ -81,6 +86,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file_name` (string, required): Name of the file to upload.
     - `content` (string, required): Base64 encoded file content.
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/create_folder">
@@ -88,6 +94,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `folder_name` (string, required): Name of the folder to create.
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/delete_item">
@@ -95,6 +102,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `item_id` (string, required): The ID of the file or folder to delete.
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/copy_item">
@@ -104,6 +112,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `item_id` (string, required): The ID of the file or folder to copy.
     - `parent_id` (string, optional): The ID of the destination folder (optional, defaults to root).
     - `new_name` (string, optional): New name for the copied item (optional).
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/move_item">
@@ -113,6 +122,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `item_id` (string, required): The ID of the file or folder to move.
     - `parent_id` (string, required): The ID of the destination folder.
     - `new_name` (string, optional): New name for the item (optional).
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/search_files">
@@ -121,6 +131,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `query` (string, required): Search query string.
     - `top` (integer, optional): Number of results to return (max 1000). Default is `50`.
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/share_item">
@@ -130,6 +141,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `item_id` (string, required): The ID of the file or folder to share.
     - `type` (string, optional): Type of sharing link. Enum: `view`, `edit`, `embed`. Default is `view`.
     - `scope` (string, optional): Scope of the sharing link. Enum: `anonymous`, `organization`. Default is `anonymous`.
+
   </Accordion>
 
   <Accordion title="microsoft_onedrive/get_thumbnails">
@@ -137,6 +149,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `item_id` (string, required): The ID of the file.
+
   </Accordion>
 </AccordionGroup>
 
@@ -232,29 +245,35 @@ crew.kickoff()
 ### Common Issues
 
 **Authentication Errors**
+
 - Ensure your Microsoft account has the necessary permissions for file access (e.g., `Files.Read`, `Files.ReadWrite`).
 - Verify that the OAuth connection includes all required scopes.
 
 **File Upload Issues**
+
 - Ensure `file_name` and `content` are provided for file uploads.
 - Content must be Base64 encoded for binary files.
 - Check that you have write permissions to OneDrive.
 
 **File/Folder ID Issues**
+
 - Double-check item IDs for correctness when accessing specific files or folders.
 - Item IDs are returned by other operations like `list_files` or `search_files`.
 - Ensure the referenced items exist and are accessible.
 
 **Search and Filter Operations**
+
 - Use appropriate search terms for `search_files` operations.
 - For `filter` parameters, use proper OData syntax.
 
 **File Operations (Copy/Move)**
+
 - For `move_item`, ensure both `item_id` and `parent_id` are provided.
 - For `copy_item`, only `item_id` is required; `parent_id` defaults to root if not specified.
 - Verify that destination folders exist and are accessible.
 
 **Sharing Link Creation**
+
 - Ensure the item exists before creating sharing links.
 - Choose appropriate `type` and `scope` based on your sharing requirements.
 - `anonymous` scope allows access without sign-in; `organization` requires organizational account.
@@ -262,5 +281,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Microsoft OneDrive integration setup or troubleshooting.
+  Contact our support team for assistance with Microsoft OneDrive integration
+  setup or troubleshooting.
 </Card>

docs/en/enterprise/integrations/microsoft_outlook.mdx

@@ -13,7 +13,7 @@ Enable your agents to access and manage Outlook emails, calendar events, and con
 
 Before using the Microsoft Outlook integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Microsoft account with Outlook access
 - Connected your Microsoft account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Microsoft Outlook integration, ensure you have:
 
 ### 1. Connect Your Microsoft Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Microsoft Outlook** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for mail, calendar, and contact access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -62,6 +64,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `orderby` (string, optional): Order by field (e.g., "receivedDateTime desc"). Default is "receivedDateTime desc".
     - `select` (string, optional): Select specific properties to return.
     - `expand` (string, optional): Expand related resources inline.
+
   </Accordion>
 
   <Accordion title="microsoft_outlook/send_email">
@@ -77,6 +80,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `importance` (string, optional): Message importance level. Enum: `low`, `normal`, `high`. Default is `normal`.
     - `reply_to` (array, optional): Array of reply-to email addresses.
     - `save_to_sent_items` (boolean, optional): Whether to save the message to Sent Items folder. Default is `true`.
+
   </Accordion>
 
   <Accordion title="microsoft_outlook/get_calendar_events">
@@ -87,6 +91,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `skip` (integer, optional): Number of events to skip. Default is `0`.
     - `filter` (string, optional): OData filter expression (e.g., "start/dateTime ge '2024-01-01T00:00:00Z'").
     - `orderby` (string, optional): Order by field (e.g., "start/dateTime asc"). Default is "start/dateTime asc".
+
   </Accordion>
 
   <Accordion title="microsoft_outlook/create_calendar_event">
@@ -100,6 +105,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `timezone` (string, optional): Time zone (e.g., 'Pacific Standard Time'). Default is `UTC`.
     - `location` (string, optional): Event location.
     - `attendees` (array, optional): Array of attendee email addresses.
+
   </Accordion>
 
   <Accordion title="microsoft_outlook/get_contacts">
@@ -110,6 +116,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `skip` (integer, optional): Number of contacts to skip. Default is `0`.
     - `filter` (string, optional): OData filter expression.
     - `orderby` (string, optional): Order by field (e.g., "displayName asc"). Default is "displayName asc".
+
   </Accordion>
 
   <Accordion title="microsoft_outlook/create_contact">
@@ -124,6 +131,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `homePhones` (array, optional): Array of home phone numbers.
     - `jobTitle` (string, optional): Contact's job title.
     - `companyName` (string, optional): Contact's company name.
+
   </Accordion>
 </AccordionGroup>
 
@@ -219,30 +227,36 @@ crew.kickoff()
 ### Common Issues
 
 **Authentication Errors**
+
 - Ensure your Microsoft account has the necessary permissions for mail, calendar, and contact access.
 - Required scopes include: `Mail.Read`, `Mail.Send`, `Calendars.Read`, `Calendars.ReadWrite`, `Contacts.Read`, `Contacts.ReadWrite`.
 - Verify that the OAuth connection includes all required scopes.
 
 **Email Sending Issues**
+
 - Ensure `to_recipients`, `subject`, and `body` are provided for `send_email`.
 - Check that email addresses are properly formatted.
 - Verify that the account has `Mail.Send` permissions.
 
 **Calendar Event Creation**
+
 - Ensure `subject`, `start_datetime`, and `end_datetime` are provided.
 - Use proper ISO 8601 format for datetime fields (e.g., '2024-01-20T10:00:00').
 - Verify timezone settings if events appear at incorrect times.
 
 **Contact Management**
+
 - For `create_contact`, ensure `displayName` is provided as it's required.
 - When providing `emailAddresses`, use the proper object format with `address` and `name` properties.
 
 **Search and Filter Issues**
+
 - Use proper OData syntax for `filter` parameters.
 - For date filters, use ISO 8601 format (e.g., "receivedDateTime ge '2024-01-01T00:00:00Z'").
 
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Microsoft Outlook integration setup or troubleshooting.
+  Contact our support team for assistance with Microsoft Outlook integration
+  setup or troubleshooting.
 </Card>

docs/en/enterprise/integrations/microsoft_sharepoint.mdx

@@ -13,7 +13,7 @@ Enable your agents to access and manage SharePoint sites, lists, and document li
 
 Before using the Microsoft SharePoint integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Microsoft 365 account with SharePoint access
 - Connected your Microsoft account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Microsoft SharePoint integration, ensure you have:
 
 ### 1. Connect Your Microsoft Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Microsoft SharePoint** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for SharePoint sites and content access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -63,6 +65,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `top` (integer, optional): Number of items to return. Minimum: 1, Maximum: 999
     - `skip` (integer, optional): Number of items to skip. Minimum: 0
     - `orderby` (string, optional): Order results by specified properties (e.g., 'displayName desc')
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/get_site">
@@ -72,6 +75,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `site_id` (string, required): The ID of the SharePoint site
     - `select` (string, optional): Select specific properties to return (e.g., 'displayName,id,webUrl,drives')
     - `expand` (string, optional): Expand related resources inline (e.g., 'drives,lists')
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/get_site_lists">
@@ -79,6 +83,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `site_id` (string, required): The ID of the SharePoint site
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/get_list">
@@ -87,6 +92,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `site_id` (string, required): The ID of the SharePoint site
     - `list_id` (string, required): The ID of the list
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/get_list_items">
@@ -96,6 +102,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `site_id` (string, required): The ID of the SharePoint site
     - `list_id` (string, required): The ID of the list
     - `expand` (string, optional): Expand related data (e.g., 'fields')
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/create_list_item">
@@ -112,6 +119,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "Status": "Active"
       }
       ```
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/update_list_item">
@@ -128,6 +136,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         "Status": "Completed"
       }
       ```
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/delete_list_item">
@@ -137,6 +146,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `site_id` (string, required): The ID of the SharePoint site
     - `list_id` (string, required): The ID of the list
     - `item_id` (string, required): The ID of the item to delete
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/upload_file_to_library">
@@ -146,6 +156,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `site_id` (string, required): The ID of the SharePoint site
     - `file_path` (string, required): The path where to upload the file (e.g., 'folder/filename.txt')
     - `content` (string, required): The file content to upload
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/get_drive_items">
@@ -153,6 +164,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `site_id` (string, required): The ID of the SharePoint site
+
   </Accordion>
 
   <Accordion title="microsoft_sharepoint/delete_drive_item">
@@ -161,6 +173,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `site_id` (string, required): The ID of the SharePoint site
     - `item_id` (string, required): The ID of the file or folder to delete
+
   </Accordion>
 </AccordionGroup>
 
@@ -363,36 +376,43 @@ crew.kickoff()
 ### Common Issues
 
 **Permission Errors**
+
 - Ensure your Microsoft account has appropriate permissions for SharePoint sites
 - Verify that the OAuth connection includes required scopes (Sites.Read.All, Sites.ReadWrite.All)
 - Check that you have access to the specific sites and lists you're trying to access
 
 **Site and List ID Issues**
+
 - Verify that site IDs and list IDs are correct and properly formatted
 - Ensure that sites and lists exist and are accessible to your account
 - Use the get_sites and get_site_lists actions to discover valid IDs
 
 **Field and Schema Issues**
+
 - Ensure field names match exactly with the SharePoint list schema
 - Verify that required fields are included when creating or updating list items
 - Check that field types and values are compatible with the list column definitions
 
 **File Upload Issues**
+
 - Ensure file paths are properly formatted and don't contain invalid characters
 - Verify that you have write permissions to the target document library
 - Check that file content is properly encoded for upload
 
 **OData Query Issues**
+
 - Use proper OData syntax for filter, select, expand, and orderby parameters
 - Verify that property names used in queries exist in the target resources
 - Test simple queries before building complex filter expressions
 
 **Pagination and Performance**
+
 - Use top and skip parameters appropriately for large result sets
 - Implement proper pagination for lists with many items
 - Consider using select parameters to return only needed properties
 
 **Document Library Operations**
+
 - Ensure you have proper permissions for document library operations
 - Verify that drive item IDs are correct when deleting files or folders
 - Check that file paths don't conflict with existing content
@@ -400,5 +420,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Microsoft SharePoint integration setup or troubleshooting.
+  Contact our support team for assistance with Microsoft SharePoint integration
+  setup or troubleshooting.
 </Card>

docs/en/enterprise/integrations/microsoft_teams.mdx

@@ -13,7 +13,7 @@ Enable your agents to access Teams data, send messages, create meetings, and man
 
 Before using the Microsoft Teams integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Microsoft account with Teams access
 - Connected your Microsoft account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Microsoft Teams integration, ensure you have:
 
 ### 1. Connect Your Microsoft Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Microsoft Teams** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for Teams access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -57,6 +59,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - No parameters required.
+
   </Accordion>
 
   <Accordion title="microsoft_teams/get_channels">
@@ -64,6 +67,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `team_id` (string, required): The ID of the team.
+
   </Accordion>
 
   <Accordion title="microsoft_teams/send_message">
@@ -74,6 +78,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `channel_id` (string, required): The ID of the channel.
     - `message` (string, required): The message content.
     - `content_type` (string, optional): Content type (html or text). Enum: `html`, `text`. Default is `text`.
+
   </Accordion>
 
   <Accordion title="microsoft_teams/get_messages">
@@ -83,6 +88,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `team_id` (string, required): The ID of the team.
     - `channel_id` (string, required): The ID of the channel.
     - `top` (integer, optional): Number of messages to retrieve (max 50). Default is `20`.
+
   </Accordion>
 
   <Accordion title="microsoft_teams/create_meeting">
@@ -92,6 +98,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `subject` (string, required): Meeting subject/title.
     - `startDateTime` (string, required): Meeting start time (ISO 8601 format with timezone).
     - `endDateTime` (string, required): Meeting end time (ISO 8601 format with timezone).
+
   </Accordion>
 
   <Accordion title="microsoft_teams/search_online_meetings_by_join_url">
@@ -99,6 +106,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `join_web_url` (string, required): The join web URL of the meeting to search for.
+
   </Accordion>
 </AccordionGroup>
 
@@ -194,35 +202,42 @@ crew.kickoff()
 ### Common Issues
 
 **Authentication Errors**
+
 - Ensure your Microsoft account has the necessary permissions for Teams access.
 - Required scopes include: `Team.ReadBasic.All`, `Channel.ReadBasic.All`, `ChannelMessage.Send`, `ChannelMessage.Read.All`, `OnlineMeetings.ReadWrite`, `OnlineMeetings.Read`.
 - Verify that the OAuth connection includes all required scopes.
 
 **Team and Channel Access**
+
 - Ensure you are a member of the teams you're trying to access.
 - Double-check team IDs and channel IDs for correctness.
 - Team and channel IDs can be obtained using the `get_teams` and `get_channels` actions.
 
 **Message Sending Issues**
+
 - Ensure `team_id`, `channel_id`, and `message` are provided for `send_message`.
 - Verify that you have permissions to send messages to the specified channel.
 - Choose appropriate `content_type` (text or html) based on your message format.
 
 **Meeting Creation**
+
 - Ensure `subject`, `startDateTime`, and `endDateTime` are provided.
 - Use proper ISO 8601 format with timezone for datetime fields (e.g., '2024-01-20T10:00:00-08:00').
 - Verify that the meeting times are in the future.
 
 **Message Retrieval Limitations**
+
 - The `get_messages` action can retrieve a maximum of 50 messages per request.
 - Messages are returned in reverse chronological order (newest first).
 
 **Meeting Search**
+
 - For `search_online_meetings_by_join_url`, ensure the join URL is exact and properly formatted.
 - The URL should be the complete Teams meeting join URL.
 
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Microsoft Teams integration setup or troubleshooting.
+  Contact our support team for assistance with Microsoft Teams integration setup
+  or troubleshooting.
 </Card>

docs/en/enterprise/integrations/microsoft_word.mdx

@@ -13,7 +13,7 @@ Enable your agents to create, read, and manage Word documents and text files in
 
 Before using the Microsoft Word integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Microsoft account with Word and OneDrive/SharePoint access
 - Connected your Microsoft account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Microsoft Word integration, ensure you have:
 
 ### 1. Connect Your Microsoft Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Microsoft Word** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for file access
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -61,6 +63,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `expand` (string, optional): Expand related resources inline.
     - `top` (integer, optional): Number of items to return (min 1, max 999).
     - `orderby` (string, optional): Order results by specified properties.
+
   </Accordion>
 
   <Accordion title="microsoft_word/create_text_document">
@@ -69,6 +72,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `file_name` (string, required): Name of the text document (should end with .txt).
     - `content` (string, optional): Text content for the document. Default is "This is a new text document created via API."
+
   </Accordion>
 
   <Accordion title="microsoft_word/get_document_content">
@@ -76,6 +80,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `file_id` (string, required): The ID of the document.
+
   </Accordion>
 
   <Accordion title="microsoft_word/get_document_properties">
@@ -83,6 +88,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `file_id` (string, required): The ID of the document.
+
   </Accordion>
 
   <Accordion title="microsoft_word/delete_document">
@@ -90,6 +96,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `file_id` (string, required): The ID of the document to delete.
+
   </Accordion>
 </AccordionGroup>
 
@@ -185,24 +192,29 @@ crew.kickoff()
 ### Common Issues
 
 **Authentication Errors**
+
 - Ensure your Microsoft account has the necessary permissions for file access (e.g., `Files.Read.All`, `Files.ReadWrite.All`).
 - Verify that the OAuth connection includes all required scopes.
 
 **File Creation Issues**
+
 - When creating text documents, ensure the `file_name` ends with `.txt` extension.
 - Verify that you have write permissions to the target location (OneDrive/SharePoint).
 
 **Document Access Issues**
+
 - Double-check document IDs for correctness when accessing specific documents.
 - Ensure the referenced documents exist and are accessible.
 - Note that this integration works best with text files (.txt) for content operations.
 
 **Content Retrieval Limitations**
+
 - The `get_document_content` action works best with text files (.txt).
 - For complex Word documents (.docx), consider using the document properties action to get metadata.
 
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Microsoft Word integration setup or troubleshooting.
+  Contact our support team for assistance with Microsoft Word integration setup
+  or troubleshooting.
 </Card>

docs/en/enterprise/integrations/notion.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage users and create comments through Notion. Access wo
 
 Before using the Notion integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Notion account with appropriate workspace permissions
 - Connected your Notion account through the [Integrations page](https://app.crewai.com/crewai_plus/connectors)
 
@@ -21,7 +21,7 @@ Before using the Notion integration, ensure you have:
 
 ### 1. Connect Your Notion Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Notion** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for user access and comment creation
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -58,6 +60,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `page_size` (integer, optional): Number of items returned in the response. Minimum: 1, Maximum: 100, Default: 100
     - `start_cursor` (string, optional): Cursor for pagination. Return results after this cursor.
+
   </Accordion>
 
   <Accordion title="notion/get_user">
@@ -65,6 +68,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `user_id` (string, required): The ID of the user to retrieve.
+
   </Accordion>
 
   <Accordion title="notion/create_comment">
@@ -96,6 +100,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
         }
       ]
       ```
+
   </Accordion>
 </AccordionGroup>
 
@@ -254,26 +259,31 @@ crew.kickoff()
 ### Common Issues
 
 **Permission Errors**
+
 - Ensure your Notion account has appropriate permissions to read user information
 - Verify that the OAuth connection includes required scopes for user access and comment creation
 - Check that you have permissions to comment on the target pages or discussions
 
 **User Access Issues**
+
 - Ensure you have workspace admin permissions to list all users
 - Verify that user IDs are correct and users exist in the workspace
 - Check that the workspace allows API access to user information
 
 **Comment Creation Issues**
+
 - Verify that page IDs or discussion IDs are correct and accessible
 - Ensure that rich text content follows Notion's API format specifications
 - Check that you have comment permissions on the target pages or discussions
 
 **API Rate Limits**
+
 - Be mindful of Notion's API rate limits when making multiple requests
 - Implement appropriate delays between requests if needed
 - Consider pagination for large user lists
 
 **Parent Object Specification**
+
 - Ensure parent object type is correctly specified (page_id or discussion_id)
 - Verify that the parent page or discussion exists and is accessible
 - Check that the parent object ID format is correct
@@ -281,5 +291,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Notion integration setup or troubleshooting.
+  Contact our support team for assistance with Notion integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/salesforce.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage customer relationships, sales processes, and data t
 
 Before using the Salesforce integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Salesforce account with appropriate permissions
 - Connected your Salesforce account through the [Integrations page](https://app.crewai.com/integrations)
 
@@ -21,7 +21,7 @@ Before using the Salesforce integration, ensure you have:
 
 ### 1. Connect Your Salesforce Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Salesforce** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for CRM and sales management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -65,6 +67,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `Title` (string, optional): Title of the contact, such as CEO or Vice President
     - `Description` (string, optional): A description of the Contact
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Contact fields
+
   </Accordion>
 
   <Accordion title="salesforce/create_record_lead">
@@ -81,6 +84,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `Status` (string, optional): Lead Status - Use Connect Portal Workflow Settings to select Lead Status
     - `Description` (string, optional): A description of the Lead
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Lead fields
+
   </Accordion>
 
   <Accordion title="salesforce/create_record_opportunity">
@@ -96,6 +100,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `OwnerId` (string, optional): The Salesforce user assigned to work on this Opportunity
     - `NextStep` (string, optional): Description of next task in closing Opportunity
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Opportunity fields
+
   </Accordion>
 
   <Accordion title="salesforce/create_record_task">
@@ -114,6 +119,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `isReminderSet` (boolean, optional): Whether reminder is set
     - `reminderDateTime` (string, optional): Reminder Date/Time in ISO format
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Task fields
+
   </Accordion>
 
   <Accordion title="salesforce/create_record_account">
@@ -126,12 +132,14 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `Phone` (string, optional): Phone number
     - `Description` (string, optional): Account description
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Account fields
+
   </Accordion>
 
   <Accordion title="salesforce/create_record_any">
     **Description:** Create a record of any object type in Salesforce.
 
     **Note:** This is a flexible tool for creating records of custom or unknown object types.
+
   </Accordion>
 </AccordionGroup>
 
@@ -150,6 +158,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `Title` (string, optional): Title of the contact
     - `Description` (string, optional): A description of the Contact
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Contact fields
+
   </Accordion>
 
   <Accordion title="salesforce/update_record_lead">
@@ -167,6 +176,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `Status` (string, optional): Lead Status
     - `Description` (string, optional): A description of the Lead
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Lead fields
+
   </Accordion>
 
   <Accordion title="salesforce/update_record_opportunity">
@@ -183,6 +193,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `OwnerId` (string, optional): The Salesforce user assigned to work on this Opportunity
     - `NextStep` (string, optional): Description of next task in closing Opportunity
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Opportunity fields
+
   </Accordion>
 
   <Accordion title="salesforce/update_record_task">
@@ -201,6 +212,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `isReminderSet` (boolean, optional): Whether reminder is set
     - `reminderDateTime` (string, optional): Reminder Date/Time in ISO format
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Task fields
+
   </Accordion>
 
   <Accordion title="salesforce/update_record_account">
@@ -214,12 +226,14 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `Phone` (string, optional): Phone number
     - `Description` (string, optional): Account description
     - `additionalFields` (object, optional): Additional fields in JSON format for custom Account fields
+
   </Accordion>
 
   <Accordion title="salesforce/update_record_any">
     **Description:** Update a record of any object type in Salesforce.
 
     **Note:** This is a flexible tool for updating records of custom or unknown object types.
+
   </Accordion>
 </AccordionGroup>
 
@@ -231,6 +245,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): Record ID of the Contact
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_id_lead">
@@ -238,6 +253,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): Record ID of the Lead
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_id_opportunity">
@@ -245,6 +261,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): Record ID of the Opportunity
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_id_task">
@@ -252,6 +269,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): Record ID of the Task
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_id_account">
@@ -259,6 +277,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `recordId` (string, required): Record ID of the Account
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_id_any">
@@ -267,6 +286,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `recordType` (string, required): Record Type (e.g., "CustomObject__c")
     - `recordId` (string, required): Record ID
+
   </Accordion>
 </AccordionGroup>
 
@@ -282,6 +302,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `sortDirection` (string, optional): Sort direction - Options: ASC, DESC
     - `includeAllFields` (boolean, optional): Include all fields in results
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/search_records_lead">
@@ -293,6 +314,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `sortDirection` (string, optional): Sort direction - Options: ASC, DESC
     - `includeAllFields` (boolean, optional): Include all fields in results
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/search_records_opportunity">
@@ -304,6 +326,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `sortDirection` (string, optional): Sort direction - Options: ASC, DESC
     - `includeAllFields` (boolean, optional): Include all fields in results
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/search_records_task">
@@ -315,6 +338,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `sortDirection` (string, optional): Sort direction - Options: ASC, DESC
     - `includeAllFields` (boolean, optional): Include all fields in results
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/search_records_account">
@@ -326,6 +350,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `sortDirection` (string, optional): Sort direction - Options: ASC, DESC
     - `includeAllFields` (boolean, optional): Include all fields in results
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/search_records_any">
@@ -336,6 +361,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `filterFormula` (string, optional): Filter search criteria
     - `includeAllFields` (boolean, optional): Include all fields in results
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 </AccordionGroup>
 
@@ -348,6 +374,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `listViewId` (string, required): List View ID
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_view_id_lead">
@@ -356,6 +383,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `listViewId` (string, required): List View ID
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_view_id_opportunity">
@@ -364,6 +392,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `listViewId` (string, required): List View ID
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_view_id_task">
@@ -372,6 +401,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `listViewId` (string, required): List View ID
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_view_id_account">
@@ -380,6 +410,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `listViewId` (string, required): List View ID
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 
   <Accordion title="salesforce/get_record_by_view_id_any">
@@ -389,6 +420,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `recordType` (string, required): Record Type
     - `listViewId` (string, required): List View ID
     - `paginationParameters` (object, optional): Pagination settings with pageCursor
+
   </Accordion>
 </AccordionGroup>
 
@@ -409,6 +441,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `description` (string, optional): Field description
     - `helperText` (string, optional): Helper text shown on hover
     - `defaultFieldValue` (string, optional): Default field value
+
   </Accordion>
 
   <Accordion title="salesforce/create_custom_field_lead">
@@ -425,6 +458,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `description` (string, optional): Field description
     - `helperText` (string, optional): Helper text shown on hover
     - `defaultFieldValue` (string, optional): Default field value
+
   </Accordion>
 
   <Accordion title="salesforce/create_custom_field_opportunity">
@@ -441,6 +475,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `description` (string, optional): Field description
     - `helperText` (string, optional): Helper text shown on hover
     - `defaultFieldValue` (string, optional): Default field value
+
   </Accordion>
 
   <Accordion title="salesforce/create_custom_field_task">
@@ -457,6 +492,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `description` (string, optional): Field description
     - `helperText` (string, optional): Helper text shown on hover
     - `defaultFieldValue` (string, optional): Default field value
+
   </Accordion>
 
   <Accordion title="salesforce/create_custom_field_account">
@@ -473,12 +509,14 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `description` (string, optional): Field description
     - `helperText` (string, optional): Helper text shown on hover
     - `defaultFieldValue` (string, optional): Default field value
+
   </Accordion>
 
   <Accordion title="salesforce/create_custom_field_any">
     **Description:** Deploy custom fields for any object type.
 
     **Note:** This is a flexible tool for creating custom fields on custom or unknown object types.
+
   </Accordion>
 </AccordionGroup>
 
@@ -490,6 +528,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `query` (string, required): SOQL Query (e.g., "SELECT Id, Name FROM Account WHERE Name = 'Example'")
+
   </Accordion>
 
   <Accordion title="salesforce/create_custom_object">
@@ -500,6 +539,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `pluralLabel` (string, required): Plural Label (e.g., "Accounts")
     - `description` (string, optional): A description of the Custom Object
     - `recordName` (string, required): Record Name that appears in layouts and searches (e.g., "Account Name")
+
   </Accordion>
 
   <Accordion title="salesforce/describe_action_schema">
@@ -510,6 +550,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `operation` (string, required): Operation Type (e.g., "CREATE_RECORD" or "UPDATE_RECORD")
 
     **Note:** Use this function first when working with custom objects to understand their schema before performing operations.
+
   </Accordion>
 </AccordionGroup>
 
@@ -639,5 +680,6 @@ This comprehensive documentation covers all the Salesforce tools organized by fu
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Salesforce integration setup or troubleshooting.
+  Contact our support team for assistance with Salesforce integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/shopify.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage e-commerce operations through Shopify. Handle custo
 
 Before using the Shopify integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Shopify store with appropriate admin permissions
 - Connected your Shopify store through the [Integrations page](https://app.crewai.com/integrations)
 
@@ -21,7 +21,7 @@ Before using the Shopify integration, ensure you have:
 
 ### 1. Connect Your Shopify Store
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Shopify** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for store and product management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -64,6 +66,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `updatedAtMin` (string, optional): Only return customers updated after this date (ISO or Unix timestamp)
     - `updatedAtMax` (string, optional): Only return customers updated before this date (ISO or Unix timestamp)
     - `limit` (string, optional): Maximum number of customers to return (defaults to 250)
+
   </Accordion>
 
   <Accordion title="shopify/search_customers">
@@ -72,6 +75,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `filterFormula` (object, optional): Advanced filter in disjunctive normal form with field-specific operators
     - `limit` (string, optional): Maximum number of customers to return (defaults to 250)
+
   </Accordion>
 
   <Accordion title="shopify/create_customer">
@@ -93,6 +97,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `note` (string, optional): Customer note
     - `sendEmailInvite` (boolean, optional): Whether to send email invitation
     - `metafields` (object, optional): Additional metafields in JSON format
+
   </Accordion>
 
   <Accordion title="shopify/update_customer">
@@ -115,6 +120,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `note` (string, optional): Customer note
     - `sendEmailInvite` (boolean, optional): Whether to send email invitation
     - `metafields` (object, optional): Additional metafields in JSON format
+
   </Accordion>
 </AccordionGroup>
 
@@ -131,6 +137,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `updatedAtMin` (string, optional): Only return orders updated after this date (ISO or Unix timestamp)
     - `updatedAtMax` (string, optional): Only return orders updated before this date (ISO or Unix timestamp)
     - `limit` (string, optional): Maximum number of orders to return (defaults to 250)
+
   </Accordion>
 
   <Accordion title="shopify/create_order">
@@ -144,6 +151,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `financialStatus` (string, optional): Financial status - Options: pending, authorized, partially_paid, paid, partially_refunded, refunded, voided
     - `inventoryBehaviour` (string, optional): Inventory behavior - Options: bypass, decrement_ignoring_policy, decrement_obeying_policy
     - `note` (string, optional): Order note
+
   </Accordion>
 
   <Accordion title="shopify/update_order">
@@ -158,6 +166,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `financialStatus` (string, optional): Financial status - Options: pending, authorized, partially_paid, paid, partially_refunded, refunded, voided
     - `inventoryBehaviour` (string, optional): Inventory behavior - Options: bypass, decrement_ignoring_policy, decrement_obeying_policy
     - `note` (string, optional): Order note
+
   </Accordion>
 
   <Accordion title="shopify/get_abandoned_carts">
@@ -170,6 +179,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `createdAtMin` (string, optional): Only return carts created after this date (ISO or Unix timestamp)
     - `createdAtMax` (string, optional): Only return carts created before this date (ISO or Unix timestamp)
     - `limit` (string, optional): Maximum number of carts to return (defaults to 250)
+
   </Accordion>
 </AccordionGroup>
 
@@ -190,6 +200,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `updatedAtMin` (string, optional): Only return products updated after this date (ISO or Unix timestamp)
     - `updatedAtMax` (string, optional): Only return products updated before this date (ISO or Unix timestamp)
     - `limit` (string, optional): Maximum number of products to return (defaults to 250)
+
   </Accordion>
 
   <Accordion title="shopify/create_product">
@@ -206,6 +217,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `imageUrl` (string, optional): Product image URL
     - `isPublished` (boolean, optional): Whether product is published
     - `publishToPointToSale` (boolean, optional): Whether to publish to point of sale
+
   </Accordion>
 
   <Accordion title="shopify/update_product">
@@ -223,6 +235,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `imageUrl` (string, optional): Product image URL
     - `isPublished` (boolean, optional): Whether product is published
     - `publishToPointToSale` (boolean, optional): Whether to publish to point of sale
+
   </Accordion>
 </AccordionGroup>
 
@@ -234,6 +247,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `productFilterFormula` (object, optional): Advanced filter in disjunctive normal form with support for fields like id, title, vendor, status, handle, tag, created_at, updated_at, published_at
+
   </Accordion>
 
   <Accordion title="shopify/create_product_graphql">
@@ -247,6 +261,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `tags` (string, optional): Product tags as array or comma-separated list
     - `media` (object, optional): Media objects with alt text, content type, and source URL
     - `additionalFields` (object, optional): Additional product fields like status, requiresSellingPlan, giftCard
+
   </Accordion>
 
   <Accordion title="shopify/update_product_graphql">
@@ -261,6 +276,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `tags` (string, optional): Product tags as array or comma-separated list
     - `media` (object, optional): Updated media objects with alt text, content type, and source URL
     - `additionalFields` (object, optional): Additional product fields like status, requiresSellingPlan, giftCard
+
   </Accordion>
 </AccordionGroup>
 
@@ -389,5 +405,6 @@ crew.kickoff()
 ### Getting Help
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Shopify integration setup or troubleshooting.
+  Contact our support team for assistance with Shopify integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/slack.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage team communication through Slack. Send messages, se
 
 Before using the Slack integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Slack workspace with appropriate permissions
 - Connected your Slack workspace through the [Integrations page](https://app.crewai.com/integrations)
 
@@ -21,7 +21,7 @@ Before using the Slack integration, ensure you have:
 
 ### 1. Connect Your Slack Workspace
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Slack** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for team communication
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -59,6 +61,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - No parameters required - retrieves all channel members
+
   </Accordion>
 
   <Accordion title="slack/get_user_by_email">
@@ -66,6 +69,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `email` (string, required): The email address of a user in the workspace
+
   </Accordion>
 
   <Accordion title="slack/get_users_by_name">
@@ -76,6 +80,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `displayName` (string, required): User's display name to search for
     - `paginationParameters` (object, optional): Pagination settings
       - `pageCursor` (string, optional): Page cursor for pagination
+
   </Accordion>
 </AccordionGroup>
 
@@ -87,6 +92,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - No parameters required - retrieves all accessible channels
+
   </Accordion>
 </AccordionGroup>
 
@@ -103,6 +109,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `botIcon` (string, required): Bot icon - Can be either an image URL or an emoji (e.g., ":dog:")
     - `blocks` (object, optional): Slack Block Kit JSON for rich message formatting with attachments and interactive elements
     - `authenticatedUser` (boolean, optional): If true, message appears to come from your authenticated Slack user instead of the application (defaults to false)
+
   </Accordion>
 
   <Accordion title="slack/send_direct_message">
@@ -115,6 +122,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `botIcon` (string, required): Bot icon - Can be either an image URL or an emoji (e.g., ":dog:")
     - `blocks` (object, optional): Slack Block Kit JSON for rich message formatting with attachments and interactive elements
     - `authenticatedUser` (boolean, optional): If true, message appears to come from your authenticated Slack user instead of the application (defaults to false)
+
   </Accordion>
 </AccordionGroup>
 
@@ -132,6 +140,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `from:@john in:#general` - Search for messages from John in the #general channel
     - `has:link after:2023-01-01` - Search for messages with links after January 1, 2023
     - `in:@channel before:yesterday` - Search for messages in a specific channel before yesterday
+
   </Accordion>
 </AccordionGroup>
 
@@ -140,6 +149,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 Slack's Block Kit allows you to create rich, interactive messages. Here are some examples of how to use the `blocks` parameter:
 
 ### Simple Text with Attachment
+
 ```json
 [
   {
@@ -154,6 +164,7 @@ Slack's Block Kit allows you to create rich, interactive messages. Here are some
 ```
 
 ### Rich Formatting with Sections
+
 ```json
 [
   {
@@ -311,5 +322,6 @@ crew.kickoff()
 ## Contact Support
 
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
-  Contact our support team for assistance with Slack integration setup or troubleshooting.
+  Contact our support team for assistance with Slack integration setup or
+  troubleshooting.
 </Card>

docs/en/enterprise/integrations/stripe.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage payments, subscriptions, and customer billing throu
 
 Before using the Stripe integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Stripe account with appropriate API permissions
 - Connected your Stripe account through the [Integrations page](https://app.crewai.com/integrations)
 
@@ -21,7 +21,7 @@ Before using the Stripe integration, ensure you have:
 
 ### 1. Connect Your Stripe Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Stripe** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for payment processing
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -62,6 +64,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `name` (string, optional): Customer's full name
     - `description` (string, optional): Customer description for internal reference
     - `metadataCreateCustomer` (object, optional): Additional metadata as key-value pairs (e.g., `{"field1": 1, "field2": 2}`)
+
   </Accordion>
 
   <Accordion title="stripe/get_customer_by_id">
@@ -69,6 +72,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `idGetCustomer` (string, required): The Stripe customer ID to retrieve
+
   </Accordion>
 
   <Accordion title="stripe/get_customers">
@@ -79,6 +83,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `createdAfter` (string, optional): Filter customers created after this date (Unix timestamp)
     - `createdBefore` (string, optional): Filter customers created before this date (Unix timestamp)
     - `limitGetCustomers` (string, optional): Maximum number of customers to return (defaults to 10)
+
   </Accordion>
 
   <Accordion title="stripe/update_customer">
@@ -90,6 +95,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `name` (string, optional): Updated customer name
     - `description` (string, optional): Updated customer description
     - `metadataUpdateCustomer` (object, optional): Updated metadata as key-value pairs
+
   </Accordion>
 </AccordionGroup>
 
@@ -103,6 +109,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `customerIdCreateSubscription` (string, required): The customer ID for whom the subscription will be created
     - `plan` (string, required): The plan ID for the subscription - Use Connect Portal Workflow Settings to allow users to select a plan
     - `metadataCreateSubscription` (object, optional): Additional metadata for the subscription
+
   </Accordion>
 
   <Accordion title="stripe/get_subscriptions">
@@ -112,6 +119,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `customerIdGetSubscriptions` (string, optional): Filter subscriptions by customer ID
     - `subscriptionStatus` (string, optional): Filter by subscription status - Options: incomplete, incomplete_expired, trialing, active, past_due, canceled, unpaid
     - `limitGetSubscriptions` (string, optional): Maximum number of subscriptions to return (defaults to 10)
+
   </Accordion>
 </AccordionGroup>
 
@@ -125,6 +133,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `productName` (string, required): The product name
     - `description` (string, optional): Product description
     - `metadataProduct` (object, optional): Additional product metadata as key-value pairs
+
   </Accordion>
 
   <Accordion title="stripe/get_product_by_id">
@@ -132,6 +141,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `productId` (string, required): The Stripe product ID to retrieve
+
   </Accordion>
 
   <Accordion title="stripe/get_products">
@@ -141,6 +151,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `createdAfter` (string, optional): Filter products created after this date (Unix timestamp)
     - `createdBefore` (string, optional): Filter products created before this date (Unix timestamp)
     - `limitGetProducts` (string, optional): Maximum number of products to return (defaults to 10)
+
   </Accordion>
 </AccordionGroup>
 
@@ -154,6 +165,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `balanceTransactionType` (string, optional): Filter by transaction type - Options: charge, refund, payment, payment_refund
     - `paginationParameters` (object, optional): Pagination settings
       - `pageCursor` (string, optional): Page cursor for pagination
+
   </Accordion>
 
   <Accordion title="stripe/get_plans">
@@ -163,6 +175,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `isPlanActive` (boolean, optional): Filter by plan status - true for active plans, false for inactive plans
     - `paginationParameters` (object, optional): Pagination settings
       - `pageCursor` (string, optional): Page cursor for pagination
+
   </Accordion>
 </AccordionGroup>
 

docs/en/enterprise/integrations/zendesk.mdx

@@ -13,7 +13,7 @@ Enable your agents to manage customer support operations through Zendesk. Create
 
 Before using the Zendesk integration, ensure you have:
 
-- A [CrewAI AOP](https://app.crewai.com) account with an active subscription
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
 - A Zendesk account with appropriate API permissions
 - Connected your Zendesk account through the [Integrations page](https://app.crewai.com/integrations)
 
@@ -21,7 +21,7 @@ Before using the Zendesk integration, ensure you have:
 
 ### 1. Connect Your Zendesk Account
 
-1. Navigate to [CrewAI AOP Integrations](https://app.crewai.com/crewai_plus/connectors)
+1. Navigate to [CrewAI AMP Integrations](https://app.crewai.com/crewai_plus/connectors)
 2. Find **Zendesk** in the Authentication Integrations section
 3. Click **Connect** and complete the OAuth flow
 4. Grant the necessary permissions for ticket and user management
@@ -36,7 +36,9 @@ uv add crewai-tools
 ### 3. Environment Variable Setup
 
 <Note>
-  To use integrations with `Agent(apps=[])`, you must set the `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise Token.
+  To use integrations with `Agent(apps=[])`, you must set the
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` environment variable with your Enterprise
+  Token.
 </Note>
 
 ```bash
@@ -70,6 +72,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `ticketTags` (string, optional): Array of tags to apply (e.g., `["enterprise", "other_tag"]`)
     - `ticketExternalId` (string, optional): External ID to link tickets to local records
     - `ticketCustomFields` (object, optional): Custom field values in JSON format
+
   </Accordion>
 
   <Accordion title="zendesk/update_ticket">
@@ -88,6 +91,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `ticketTags` (string, optional): Updated tags array
     - `ticketExternalId` (string, optional): Updated external ID
     - `ticketCustomFields` (object, optional): Updated custom field values
+
   </Accordion>
 
   <Accordion title="zendesk/get_ticket_by_id">
@@ -95,6 +99,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `ticketId` (string, required): The ticket ID to retrieve (e.g., "35436")
+
   </Accordion>
 
   <Accordion title="zendesk/add_comment_to_ticket">
@@ -105,6 +110,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `commentBody` (string, required): Comment message (accepts plain text or HTML, e.g., "Thanks for your help!")
     - `isInternalNote` (boolean, optional): Set to true for internal notes instead of public replies (defaults to false)
     - `isPublic` (boolean, optional): True for public comments, false for internal notes
+
   </Accordion>
 
   <Accordion title="zendesk/search_tickets">
@@ -126,6 +132,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `dueDate` (object, optional): Filter by due date with operator and value
     - `sort_by` (string, optional): Sort field - Options: created_at, updated_at, priority, status, ticket_type
     - `sort_order` (string, optional): Sort direction - Options: asc, desc
+
   </Accordion>
 </AccordionGroup>
 
@@ -143,6 +150,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `externalId` (string, optional): Unique identifier from another system
     - `details` (string, optional): Additional user details
     - `notes` (string, optional): Internal notes about the user
+
   </Accordion>
 
   <Accordion title="zendesk/update_user">
@@ -157,6 +165,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `externalId` (string, optional): Updated external ID
     - `details` (string, optional): Updated user details
     - `notes` (string, optional): Updated internal notes
+
   </Accordion>
 
   <Accordion title="zendesk/get_user_by_id">
@@ -164,6 +173,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
     **Parameters:**
     - `userId` (string, required): The user ID to retrieve
+
   </Accordion>
 
   <Accordion title="zendesk/search_users">
@@ -176,6 +186,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `externalId` (string, optional): Filter by external ID
     - `sort_by` (string, optional): Sort field - Options: created_at, updated_at
     - `sort_order` (string, optional): Sort direction - Options: asc, desc
+
   </Accordion>
 </AccordionGroup>
 
@@ -188,6 +199,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     **Parameters:**
     - `paginationParameters` (object, optional): Pagination settings
       - `pageCursor` (string, optional): Page cursor for pagination
+
   </Accordion>
 
   <Accordion title="zendesk/get_ticket_audits">
@@ -197,6 +209,7 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `ticketId` (string, optional): Get audits for specific ticket (if empty, retrieves audits for all non-archived tickets, e.g., "1234")
     - `paginationParameters` (object, optional): Pagination settings
       - `pageCursor` (string, optional): Page cursor for pagination
+
   </Accordion>
 </AccordionGroup>
 

docs/en/enterprise/introduction.mdx

@@ -1,5 +1,5 @@
 ---
-title: "CrewAI AOP"
+title: "CrewAI AMP"
 description: "Deploy, monitor, and scale your AI agent workflows"
 icon: "globe"
 mode: "wide"
@@ -7,13 +7,16 @@ mode: "wide"
 
 ## Introduction
 
-CrewAI AOP(Agent Operations Platform) provides a platform for deploying, monitoring, and scaling your crews and agents in a production environment.
+CrewAI AMP(Agent Management Platform) provides a platform for deploying, monitoring, and scaling your crews and agents in a production environment.
 
 <Frame>
-  <img src="/images/enterprise/crewai-enterprise-dashboard.png" alt="CrewAI AOP Dashboard" />
+  <img
+    src="/images/enterprise/crewai-enterprise-dashboard.png"
+    alt="CrewAI AMP Dashboard"
+  />
 </Frame>
 
-CrewAI AOP extends the power of the open-source framework with features designed for production deployments, collaboration, and scalability. Deploy your crews to a managed infrastructure and monitor their execution in real-time.
+CrewAI AMP extends the power of the open-source framework with features designed for production deployments, collaboration, and scalability. Deploy your crews to a managed infrastructure and monitor their execution in real-time.
 
 ## Key Features
 
@@ -22,7 +25,8 @@ CrewAI AOP extends the power of the open-source framework with features designed
     Deploy your crews to a managed infrastructure with a few clicks
   </Card>
   <Card title="API Access" icon="code">
-    Access your deployed crews via REST API for integration with existing systems
+    Access your deployed crews via REST API for integration with existing
+    systems
   </Card>
   <Card title="Observability" icon="chart-line">
     Monitor your crews with detailed execution traces and logs
@@ -57,11 +61,7 @@ CrewAI AOP extends the power of the open-source framework with features designed
 <Steps>
   <Step title="Sign up for an account">
     Create your account at [app.crewai.com](https://app.crewai.com)
-    <Card
-      title="Sign Up"
-      icon="user"
-      href="https://app.crewai.com/signup"
-    >
+    <Card title="Sign Up" icon="user" href="https://app.crewai.com/signup">
       Sign Up
     </Card>
   </Step>

docs/en/enterprise/resources/frequently-asked-questions.mdx

@@ -1,6 +1,6 @@
 ---
 title: FAQs
-description: "Frequently asked questions about CrewAI AOP"
+description: "Frequently asked questions about CrewAI AMP"
 icon: "circle-question"
 mode: "wide"
 ---
@@ -148,4 +148,5 @@ mode: "wide"
     <Accordion title="How can you control the maximum number of requests per minute that the entire crew can perform?">
         The `max_rpm` attribute sets the maximum number of requests per minute the crew can perform to avoid rate limits and will override individual agents' `max_rpm` settings if you set it.
     </Accordion>
+
 </AccordionGroup>

docs/en/installation.mdx

@@ -6,6 +6,7 @@ mode: "wide"
 ---
 
 ## Video Tutorial
+
 Watch this video tutorial for a step-by-step demonstration of the installation process:
 
 <iframe
@@ -18,21 +19,25 @@ Watch this video tutorial for a step-by-step demonstration of the installation p
 ></iframe>
 
 ## Text Tutorial
+
 <Note>
   **Python Version Requirements**
 
-  CrewAI requires `Python >=3.10 and <3.14`. Here's how to check your version:
-  ```bash
-  python3 --version
-  ```
+CrewAI requires `Python >=3.10 and <3.14`. Here's how to check your version:
+
+```bash
+python3 --version
+```
+
+If you need to update Python, visit [python.org/downloads](https://python.org/downloads)
 
-  If you need to update Python, visit [python.org/downloads](https://python.org/downloads)
 </Note>
 
 <Note>
   **OpenAI SDK Requirement**
 
-  CrewAI 0.175.0 requires `openai >= 1.13.3`. If you manage dependencies yourself, ensure your environment satisfies this constraint to avoid import/runtime issues.
+CrewAI 0.175.0 requires `openai >= 1.13.3`. If you manage dependencies yourself, ensure your environment satisfies this constraint to avoid import/runtime issues.
+
 </Note>
 
 CrewAI uses the `uv` as its dependency management and package handling tool. It simplifies project setup and execution, offering a seamless experience.
@@ -95,6 +100,7 @@ If you haven't installed `uv` yet, follow **step 1** to quickly get it set up on
         ```
       <Check>Installation successful! You're ready to create your first crew! 🎉</Check>
     </Step>
+
 </Steps>
 
 # Creating a CrewAI Project
@@ -128,6 +134,7 @@ We recommend using the `YAML` template scaffolding for a structured approach to
                   ├── agents.yaml
                   └── tasks.yaml
       ```
+
   </Step>
 
   <Step title="Customize Your Project">
@@ -144,6 +151,7 @@ We recommend using the `YAML` template scaffolding for a structured approach to
 
     - Start by editing `agents.yaml` and `tasks.yaml` to define your crew's behavior.
     - Keep sensitive information like API keys in `.env`.
+
   </Step>
 
   <Step title="Run your Crew">
@@ -167,13 +175,15 @@ We recommend using the `YAML` template scaffolding for a structured approach to
 <Note type="info">
 For teams and organizations, CrewAI offers enterprise deployment options that eliminate setup complexity:
 
-### CrewAI AOP (SaaS)
+### CrewAI AMP (SaaS)
+
 - Zero installation required - just sign up for free at [app.crewai.com](https://app.crewai.com)
 - Automatic updates and maintenance
 - Managed infrastructure and scaling
 - Build Crews with no Code
 
 ### CrewAI Factory (Self-hosted)
+
 - Containerized deployment for your infrastructure
 - Supports any hyperscaler including on prem deployments
 - Integration with your existing security systems
@@ -186,12 +196,9 @@ For teams and organizations, CrewAI offers enterprise deployment options that el
 ## Next Steps
 
 <CardGroup cols={2}>
-  <Card
-    title="Build Your First Agent"
-    icon="code"
-    href="/en/quickstart"
-  >
-    Follow our quickstart guide to create your first CrewAI agent and get hands-on experience.
+  <Card title="Build Your First Agent" icon="code" href="/en/quickstart">
+    Follow our quickstart guide to create your first CrewAI agent and get
+    hands-on experience.
   </Card>
   <Card
     title="Join the Community"

docs/en/introduction.mdx

@@ -7,110 +7,89 @@ mode: "wide"
 
 # What is CrewAI?
 
-**CrewAI is a lean, lightning-fast Python framework built entirely from scratch—completely independent of LangChain or other agent frameworks.**
+**CrewAI is the leading open-source framework for orchestrating autonomous AI agents and building complex workflows.**
 
-CrewAI empowers developers with both high-level simplicity and precise low-level control, ideal for creating autonomous AI agents tailored to any scenario:
+It empowers developers to build production-ready multi-agent systems by combining the collaborative intelligence of **Crews** with the precise control of **Flows**.
 
-- **[CrewAI Crews](/en/guides/crews/first-crew)**: Optimize for autonomy and collaborative intelligence, enabling you to create AI teams where each agent has specific roles, tools, and goals.
-- **[CrewAI Flows](/en/guides/flows/first-flow)**: Enable granular, event-driven control, single LLM calls for precise task orchestration and supports Crews natively.
+- **[CrewAI Flows](/en/guides/flows/first-flow)**: The backbone of your AI application. Flows allow you to create structured, event-driven workflows that manage state and control execution. They provide the scaffolding for your AI agents to work within.
+- **[CrewAI Crews](/en/guides/crews/first-crew)**: The units of work within your Flow. Crews are teams of autonomous agents that collaborate to solve specific tasks delegated to them by the Flow.
 
-With over 100,000 developers certified through our community courses, CrewAI is rapidly becoming the standard for enterprise-ready AI automation.
+With over 100,000 developers certified through our community courses, CrewAI is the standard for enterprise-ready AI automation.
 
+## The CrewAI Architecture
 
-## How Crews Work
+CrewAI's architecture is designed to balance autonomy with control.
+
+### 1. Flows: The Backbone
 
 <Note>
-  Just like a company has departments (Sales, Engineering, Marketing) working together under leadership to achieve business goals, CrewAI helps you create an organization of AI agents with specialized roles collaborating to accomplish complex tasks.
-</Note>
-
-<Frame caption="CrewAI Framework Overview">
-  <img src="/images/crews.png" alt="CrewAI Framework Overview" />
-</Frame>
-
-| Component | Description | Key Features |
-|:----------|:-----------:|:------------|
-| **Crew** | The top-level organization | • Manages AI agent teams<br/>• Oversees workflows<br/>• Ensures collaboration<br/>• Delivers outcomes |
-| **AI Agents** | Specialized team members | • Have specific roles (researcher, writer)<br/>• Use designated tools<br/>• Can delegate tasks<br/>• Make autonomous decisions |
-| **Process** | Workflow management system | • Defines collaboration patterns<br/>• Controls task assignments<br/>• Manages interactions<br/>• Ensures efficient execution |
-| **Tasks** | Individual assignments | • Have clear objectives<br/>• Use specific tools<br/>• Feed into larger process<br/>• Produce actionable results |
-
-### How It All Works Together
-
-1. The **Crew** organizes the overall operation
-2. **AI Agents** work on their specialized tasks
-3. The **Process** ensures smooth collaboration
-4. **Tasks** get completed to achieve the goal
-
-## Key Features
-
-<CardGroup cols={2}>
-  <Card title="Role-Based Agents" icon="users">
-    Create specialized agents with defined roles, expertise, and goals - from researchers to analysts to writers
-  </Card>
-  <Card title="Flexible Tools" icon="screwdriver-wrench">
-    Equip agents with custom tools and APIs to interact with external services and data sources
-  </Card>
-  <Card title="Intelligent Collaboration" icon="people-arrows">
-    Agents work together, sharing insights and coordinating tasks to achieve complex objectives
-  </Card>
-  <Card title="Task Management" icon="list-check">
-    Define sequential or parallel workflows, with agents automatically handling task dependencies
-  </Card>
-</CardGroup>
-
-## How Flows Work
-
-<Note>
-  While Crews excel at autonomous collaboration, Flows provide structured automations, offering granular control over workflow execution. Flows ensure tasks are executed reliably, securely, and efficiently, handling conditional logic, loops, and dynamic state management with precision. Flows integrate seamlessly with Crews, enabling you to balance high autonomy with exacting control.
+  Think of a Flow as the "manager" or the "process definition" of your application. It defines the steps, the logic, and how data moves through your system.
 </Note>
 
 <Frame caption="CrewAI Framework Overview">
   <img src="/images/flows.png" alt="CrewAI Framework Overview" />
 </Frame>
 
-| Component | Description | Key Features |
-|:----------|:-----------:|:------------|
-| **Flow** | Structured workflow orchestration | • Manages execution paths<br/>• Handles state transitions<br/>• Controls task sequencing<br/>• Ensures reliable execution |
-| **Events** | Triggers for workflow actions | • Initiate specific processes<br/>• Enable dynamic responses<br/>• Support conditional branching<br/>• Allow for real-time adaptation |
-| **States** | Workflow execution contexts | • Maintain execution data<br/>• Enable persistence<br/>• Support resumability<br/>• Ensure execution integrity |
-| **Crew Support** | Enhances workflow automation | • Injects pockets of agency when needed<br/>• Complements structured workflows<br/>• Balances automation with intelligence<br/>• Enables adaptive decision-making |
+Flows provide:
+- **State Management**: Persist data across steps and executions.
+- **Event-Driven Execution**: Trigger actions based on events or external inputs.
+- **Control Flow**: Use conditional logic, loops, and branching.
 
-### Key Capabilities
+### 2. Crews: The Intelligence
+
+<Note>
+  Crews are the "teams" that do the heavy lifting. Within a Flow, you can trigger a Crew to tackle a complex problem requiring creativity and collaboration.
+</Note>
+
+<Frame caption="CrewAI Framework Overview">
+  <img src="/images/crews.png" alt="CrewAI Framework Overview" />
+</Frame>
+
+Crews provide:
+- **Role-Playing Agents**: Specialized agents with specific goals and tools.
+- **Autonomous Collaboration**: Agents work together to solve tasks.
+- **Task Delegation**: Tasks are assigned and executed based on agent capabilities.
+
+## How It All Works Together
+
+1.  **The Flow** triggers an event or starts a process.
+2.  **The Flow** manages the state and decides what to do next.
+3.  **The Flow** delegates a complex task to a **Crew**.
+4.  **The Crew**'s agents collaborate to complete the task.
+5.  **The Crew** returns the result to the **Flow**.
+6.  **The Flow** continues execution based on the result.
+
+## Key Features
 
 <CardGroup cols={2}>
-  <Card title="Event-Driven Orchestration" icon="bolt">
-    Define precise execution paths responding dynamically to events
+  <Card title="Production-Grade Flows" icon="arrow-progress">
+    Build reliable, stateful workflows that can handle long-running processes and complex logic.
   </Card>
-  <Card title="Fine-Grained Control" icon="sliders">
-    Manage workflow states and conditional execution securely and efficiently
+  <Card title="Autonomous Crews" icon="users">
+    Deploy teams of agents that can plan, execute, and collaborate to achieve high-level goals.
   </Card>
-  <Card title="Native Crew Integration" icon="puzzle-piece">
-    Effortlessly combine with Crews for enhanced autonomy and intelligence
+  <Card title="Flexible Tools" icon="screwdriver-wrench">
+     Connect your agents to any API, database, or local tool.
   </Card>
-  <Card title="Deterministic Execution" icon="route">
-    Ensure predictable outcomes with explicit control flow and error handling
+  <Card title="Enterprise Security" icon="lock">
+    Designed with security and compliance in mind for enterprise deployments.
   </Card>
 </CardGroup>
 
 ## When to Use Crews vs. Flows
 
-<Note>
-  Understanding when to use [Crews](/en/guides/crews/first-crew) versus [Flows](/en/guides/flows/first-flow) is key to maximizing the potential of CrewAI in your applications.
-</Note>
+**The short answer: Use both.**
 
-| Use Case | Recommended Approach | Why? |
-|:---------|:---------------------|:-----|
-| **Open-ended research** | [Crews](/en/guides/crews/first-crew) | When tasks require creative thinking, exploration, and adaptation |
-| **Content generation** | [Crews](/en/guides/crews/first-crew) | For collaborative creation of articles, reports, or marketing materials |
-| **Decision workflows** | [Flows](/en/guides/flows/first-flow) | When you need predictable, auditable decision paths with precise control |
-| **API orchestration** | [Flows](/en/guides/flows/first-flow) | For reliable integration with multiple external services in a specific sequence |
-| **Hybrid applications** | Combined approach | Use [Flows](/en/guides/flows/first-flow) to orchestrate overall process with [Crews](/en/guides/crews/first-crew) handling complex subtasks |
+For any production-ready application, **start with a Flow**.
 
-### Decision Framework
+- **Use a Flow** to define the overall structure, state, and logic of your application.
+- **Use a Crew** within a Flow step when you need a team of agents to perform a specific, complex task that requires autonomy.
 
-- **Choose [Crews](/en/guides/crews/first-crew) when:** You need autonomous problem-solving, creative collaboration, or exploratory tasks
-- **Choose [Flows](/en/guides/flows/first-flow) when:** You require deterministic outcomes, auditability, or precise control over execution
-- **Combine both when:** Your application needs both structured processes and pockets of autonomous intelligence
+| Use Case | Architecture |
+| :--- | :--- |
+| **Simple Automation** | Single Flow with Python tasks |
+| **Complex Research** | Flow managing state -> Crew performing research |
+| **Application Backend** | Flow handling API requests -> Crew generating content -> Flow saving to DB |
 
 ## Why Choose CrewAI?
 
@@ -124,13 +103,6 @@ With over 100,000 developers certified through our community courses, CrewAI is
 ## Ready to Start Building?
 
 <CardGroup cols={2}>
-  <Card
-    title="Build Your First Crew"
-    icon="users-gear"
-    href="/en/guides/crews/first-crew"
-  >
-    Step-by-step tutorial to create a collaborative AI team that works together to solve complex problems.
-  </Card>
   <Card
     title="Build Your First Flow"
     icon="diagram-project"
@@ -138,6 +110,13 @@ With over 100,000 developers certified through our community courses, CrewAI is
   >
     Learn how to create structured, event-driven workflows with precise control over execution.
   </Card>
+  <Card
+    title="Build Your First Crew"
+    icon="users-gear"
+    href="/en/guides/crews/first-crew"
+  >
+    Step-by-step tutorial to create a collaborative AI team that works together to solve complex problems.
+  </Card>
 </CardGroup>
 
 <CardGroup cols={3}>

docs/en/learn/human-feedback-in-flows.mdx

@@ -0,0 +1,581 @@
+---
+title: Human Feedback in Flows
+description: Learn how to integrate human feedback directly into your CrewAI Flows using the @human_feedback decorator
+icon: user-check
+mode: "wide"
+---
+
+## Overview
+
+The `@human_feedback` decorator enables human-in-the-loop (HITL) workflows directly within CrewAI Flows. It allows you to pause flow execution, present output to a human for review, collect their feedback, and optionally route to different listeners based on the feedback outcome.
+
+This is particularly valuable for:
+
+- **Quality assurance**: Review AI-generated content before it's used downstream
+- **Decision gates**: Let humans make critical decisions in automated workflows
+- **Approval workflows**: Implement approve/reject/revise patterns
+- **Interactive refinement**: Collect feedback to improve outputs iteratively
+
+```mermaid
+flowchart LR
+    A[Flow Method] --> B[Output Generated]
+    B --> C[Human Reviews]
+    C --> D{Feedback}
+    D -->|emit specified| E[LLM Collapses to Outcome]
+    D -->|no emit| F[HumanFeedbackResult]
+    E --> G["@listen('approved')"]
+    E --> H["@listen('rejected')"]
+    F --> I[Next Listener]
+```
+
+## Quick Start
+
+Here's the simplest way to add human feedback to a flow:
+
+```python Code
+from crewai.flow.flow import Flow, start, listen
+from crewai.flow.human_feedback import human_feedback
+
+class SimpleReviewFlow(Flow):
+    @start()
+    @human_feedback(message="Please review this content:")
+    def generate_content(self):
+        return "This is AI-generated content that needs review."
+
+    @listen(generate_content)
+    def process_feedback(self, result):
+        print(f"Content: {result.output}")
+        print(f"Human said: {result.feedback}")
+
+flow = SimpleReviewFlow()
+flow.kickoff()
+```
+
+When this flow runs, it will:
+1. Execute `generate_content` and return the string
+2. Display the output to the user with the request message
+3. Wait for the user to type feedback (or press Enter to skip)
+4. Pass a `HumanFeedbackResult` object to `process_feedback`
+
+## The @human_feedback Decorator
+
+### Parameters
+
+| Parameter | Type | Required | Description |
+|-----------|------|----------|-------------|
+| `message` | `str` | Yes | The message shown to the human alongside the method output |
+| `emit` | `Sequence[str]` | No | List of possible outcomes. Feedback is collapsed to one of these, which triggers `@listen` decorators |
+| `llm` | `str \| BaseLLM` | When `emit` specified | LLM used to interpret feedback and map to an outcome |
+| `default_outcome` | `str` | No | Outcome to use if no feedback provided. Must be in `emit` |
+| `metadata` | `dict` | No | Additional data for enterprise integrations |
+| `provider` | `HumanFeedbackProvider` | No | Custom provider for async/non-blocking feedback. See [Async Human Feedback](#async-human-feedback-non-blocking) |
+
+### Basic Usage (No Routing)
+
+When you don't specify `emit`, the decorator simply collects feedback and passes a `HumanFeedbackResult` to the next listener:
+
+```python Code
+@start()
+@human_feedback(message="What do you think of this analysis?")
+def analyze_data(self):
+    return "Analysis results: Revenue up 15%, costs down 8%"
+
+@listen(analyze_data)
+def handle_feedback(self, result):
+    # result is a HumanFeedbackResult
+    print(f"Analysis: {result.output}")
+    print(f"Feedback: {result.feedback}")
+```
+
+### Routing with emit
+
+When you specify `emit`, the decorator becomes a router. The human's free-form feedback is interpreted by an LLM and collapsed into one of the specified outcomes:
+
+```python Code
+@start()
+@human_feedback(
+    message="Do you approve this content for publication?",
+    emit=["approved", "rejected", "needs_revision"],
+    llm="gpt-4o-mini",
+    default_outcome="needs_revision",
+)
+def review_content(self):
+    return "Draft blog post content here..."
+
+@listen("approved")
+def publish(self, result):
+    print(f"Publishing! User said: {result.feedback}")
+
+@listen("rejected")
+def discard(self, result):
+    print(f"Discarding. Reason: {result.feedback}")
+
+@listen("needs_revision")
+def revise(self, result):
+    print(f"Revising based on: {result.feedback}")
+```
+
+<Tip>
+The LLM uses structured outputs (function calling) when available to guarantee the response is one of your specified outcomes. This makes routing reliable and predictable.
+</Tip>
+
+## HumanFeedbackResult
+
+The `HumanFeedbackResult` dataclass contains all information about a human feedback interaction:
+
+```python Code
+from crewai.flow.human_feedback import HumanFeedbackResult
+
+@dataclass
+class HumanFeedbackResult:
+    output: Any              # The original method output shown to the human
+    feedback: str            # The raw feedback text from the human
+    outcome: str | None      # The collapsed outcome (if emit was specified)
+    timestamp: datetime      # When the feedback was received
+    method_name: str         # Name of the decorated method
+    metadata: dict           # Any metadata passed to the decorator
+```
+
+### Accessing in Listeners
+
+When a listener is triggered by a `@human_feedback` method with `emit`, it receives the `HumanFeedbackResult`:
+
+```python Code
+@listen("approved")
+def on_approval(self, result: HumanFeedbackResult):
+    print(f"Original output: {result.output}")
+    print(f"User feedback: {result.feedback}")
+    print(f"Outcome: {result.outcome}")  # "approved"
+    print(f"Received at: {result.timestamp}")
+```
+
+## Accessing Feedback History
+
+The `Flow` class provides two attributes for accessing human feedback:
+
+### last_human_feedback
+
+Returns the most recent `HumanFeedbackResult`:
+
+```python Code
+@listen(some_method)
+def check_feedback(self):
+    if self.last_human_feedback:
+        print(f"Last feedback: {self.last_human_feedback.feedback}")
+```
+
+### human_feedback_history
+
+A list of all `HumanFeedbackResult` objects collected during the flow:
+
+```python Code
+@listen(final_step)
+def summarize(self):
+    print(f"Total feedback collected: {len(self.human_feedback_history)}")
+    for i, fb in enumerate(self.human_feedback_history):
+        print(f"{i+1}. {fb.method_name}: {fb.outcome or 'no routing'}")
+```
+
+<Warning>
+Each `HumanFeedbackResult` is appended to `human_feedback_history`, so multiple feedback steps won't overwrite each other. Use this list to access all feedback collected during the flow.
+</Warning>
+
+## Complete Example: Content Approval Workflow
+
+Here's a full example implementing a content review and approval workflow:
+
+<CodeGroup>
+
+```python Code
+from crewai.flow.flow import Flow, start, listen
+from crewai.flow.human_feedback import human_feedback, HumanFeedbackResult
+from pydantic import BaseModel
+
+
+class ContentState(BaseModel):
+    topic: str = ""
+    draft: str = ""
+    final_content: str = ""
+    revision_count: int = 0
+
+
+class ContentApprovalFlow(Flow[ContentState]):
+    """A flow that generates content and gets human approval."""
+
+    @start()
+    def get_topic(self):
+        self.state.topic = input("What topic should I write about? ")
+        return self.state.topic
+
+    @listen(get_topic)
+    def generate_draft(self, topic):
+        # In real use, this would call an LLM
+        self.state.draft = f"# {topic}\n\nThis is a draft about {topic}..."
+        return self.state.draft
+
+    @listen(generate_draft)
+    @human_feedback(
+        message="Please review this draft. Reply 'approved', 'rejected', or provide revision feedback:",
+        emit=["approved", "rejected", "needs_revision"],
+        llm="gpt-4o-mini",
+        default_outcome="needs_revision",
+    )
+    def review_draft(self, draft):
+        return draft
+
+    @listen("approved")
+    def publish_content(self, result: HumanFeedbackResult):
+        self.state.final_content = result.output
+        print("\n✅ Content approved and published!")
+        print(f"Reviewer comment: {result.feedback}")
+        return "published"
+
+    @listen("rejected")
+    def handle_rejection(self, result: HumanFeedbackResult):
+        print("\n❌ Content rejected")
+        print(f"Reason: {result.feedback}")
+        return "rejected"
+
+    @listen("needs_revision")
+    def revise_content(self, result: HumanFeedbackResult):
+        self.state.revision_count += 1
+        print(f"\n📝 Revision #{self.state.revision_count} requested")
+        print(f"Feedback: {result.feedback}")
+
+        # In a real flow, you might loop back to generate_draft
+        # For this example, we just acknowledge
+        return "revision_requested"
+
+
+# Run the flow
+flow = ContentApprovalFlow()
+result = flow.kickoff()
+print(f"\nFlow completed. Revisions requested: {flow.state.revision_count}")
+```
+
+```text Output
+What topic should I write about? AI Safety
+
+==================================================
+OUTPUT FOR REVIEW:
+==================================================
+# AI Safety
+
+This is a draft about AI Safety...
+==================================================
+
+Please review this draft. Reply 'approved', 'rejected', or provide revision feedback:
+(Press Enter to skip, or type your feedback)
+
+Your feedback: Looks good, approved!
+
+✅ Content approved and published!
+Reviewer comment: Looks good, approved!
+
+Flow completed. Revisions requested: 0
+```
+
+</CodeGroup>
+
+## Combining with Other Decorators
+
+The `@human_feedback` decorator works with other flow decorators. Place it as the innermost decorator (closest to the function):
+
+```python Code
+# Correct: @human_feedback is innermost (closest to the function)
+@start()
+@human_feedback(message="Review this:")
+def my_start_method(self):
+    return "content"
+
+@listen(other_method)
+@human_feedback(message="Review this too:")
+def my_listener(self, data):
+    return f"processed: {data}"
+```
+
+<Tip>
+Place `@human_feedback` as the innermost decorator (last/closest to the function) so it wraps the method directly and can capture the return value before passing to the flow system.
+</Tip>
+
+## Best Practices
+
+### 1. Write Clear Request Messages
+
+The `request` parameter is what the human sees. Make it actionable:
+
+```python Code
+# ✅ Good - clear and actionable
+@human_feedback(message="Does this summary accurately capture the key points? Reply 'yes' or explain what's missing:")
+
+# ❌ Bad - vague
+@human_feedback(message="Review this:")
+```
+
+### 2. Choose Meaningful Outcomes
+
+When using `emit`, pick outcomes that map naturally to human responses:
+
+```python Code
+# ✅ Good - natural language outcomes
+emit=["approved", "rejected", "needs_more_detail"]
+
+# ❌ Bad - technical or unclear
+emit=["state_1", "state_2", "state_3"]
+```
+
+### 3. Always Provide a Default Outcome
+
+Use `default_outcome` to handle cases where users press Enter without typing:
+
+```python Code
+@human_feedback(
+    message="Approve? (press Enter to request revision)",
+    emit=["approved", "needs_revision"],
+    llm="gpt-4o-mini",
+    default_outcome="needs_revision",  # Safe default
+)
+```
+
+### 4. Use Feedback History for Audit Trails
+
+Access `human_feedback_history` to create audit logs:
+
+```python Code
+@listen(final_step)
+def create_audit_log(self):
+    log = []
+    for fb in self.human_feedback_history:
+        log.append({
+            "step": fb.method_name,
+            "outcome": fb.outcome,
+            "feedback": fb.feedback,
+            "timestamp": fb.timestamp.isoformat(),
+        })
+    return log
+```
+
+### 5. Handle Both Routed and Non-Routed Feedback
+
+When designing flows, consider whether you need routing:
+
+| Scenario | Use |
+|----------|-----|
+| Simple review, just need the feedback text | No `emit` |
+| Need to branch to different paths based on response | Use `emit` |
+| Approval gates with approve/reject/revise | Use `emit` |
+| Collecting comments for logging only | No `emit` |
+
+## Async Human Feedback (Non-Blocking)
+
+By default, `@human_feedback` blocks execution waiting for console input. For production applications, you may need **async/non-blocking** feedback that integrates with external systems like Slack, email, webhooks, or APIs.
+
+### The Provider Abstraction
+
+Use the `provider` parameter to specify a custom feedback collection strategy:
+
+```python Code
+from crewai.flow import Flow, start, human_feedback, HumanFeedbackProvider, HumanFeedbackPending, PendingFeedbackContext
+
+class WebhookProvider(HumanFeedbackProvider):
+    """Provider that pauses flow and waits for webhook callback."""
+
+    def __init__(self, webhook_url: str):
+        self.webhook_url = webhook_url
+
+    def request_feedback(self, context: PendingFeedbackContext, flow: Flow) -> str:
+        # Notify external system (e.g., send Slack message, create ticket)
+        self.send_notification(context)
+
+        # Pause execution - framework handles persistence automatically
+        raise HumanFeedbackPending(
+            context=context,
+            callback_info={"webhook_url": f"{self.webhook_url}/{context.flow_id}"}
+        )
+
+class ReviewFlow(Flow):
+    @start()
+    @human_feedback(
+        message="Review this content:",
+        emit=["approved", "rejected"],
+        llm="gpt-4o-mini",
+        provider=WebhookProvider("https://myapp.com/api"),
+    )
+    def generate_content(self):
+        return "AI-generated content..."
+
+    @listen("approved")
+    def publish(self, result):
+        return "Published!"
+```
+
+<Tip>
+The flow framework **automatically persists state** when `HumanFeedbackPending` is raised. Your provider only needs to notify the external system and raise the exception—no manual persistence calls required.
+</Tip>
+
+### Handling Paused Flows
+
+When using an async provider, `kickoff()` returns a `HumanFeedbackPending` object instead of raising an exception:
+
+```python Code
+flow = ReviewFlow()
+result = flow.kickoff()
+
+if isinstance(result, HumanFeedbackPending):
+    # Flow is paused, state is automatically persisted
+    print(f"Waiting for feedback at: {result.callback_info['webhook_url']}")
+    print(f"Flow ID: {result.context.flow_id}")
+else:
+    # Normal completion
+    print(f"Flow completed: {result}")
+```
+
+### Resuming a Paused Flow
+
+When feedback arrives (e.g., via webhook), resume the flow:
+
+```python Code
+# Sync handler:
+def handle_feedback_webhook(flow_id: str, feedback: str):
+    flow = ReviewFlow.from_pending(flow_id)
+    result = flow.resume(feedback)
+    return result
+
+# Async handler (FastAPI, aiohttp, etc.):
+async def handle_feedback_webhook(flow_id: str, feedback: str):
+    flow = ReviewFlow.from_pending(flow_id)
+    result = await flow.resume_async(feedback)
+    return result
+```
+
+### Key Types
+
+| Type | Description |
+|------|-------------|
+| `HumanFeedbackProvider` | Protocol for custom feedback providers |
+| `PendingFeedbackContext` | Contains all info needed to resume a paused flow |
+| `HumanFeedbackPending` | Returned by `kickoff()` when flow is paused for feedback |
+| `ConsoleProvider` | Default blocking console input provider |
+
+### PendingFeedbackContext
+
+The context contains everything needed to resume:
+
+```python Code
+@dataclass
+class PendingFeedbackContext:
+    flow_id: str           # Unique identifier for this flow execution
+    flow_class: str        # Fully qualified class name
+    method_name: str       # Method that triggered feedback
+    method_output: Any     # Output shown to the human
+    message: str           # The request message
+    emit: list[str] | None # Possible outcomes for routing
+    default_outcome: str | None
+    metadata: dict         # Custom metadata
+    llm: str | None        # LLM for outcome collapsing
+    requested_at: datetime
+```
+
+### Complete Async Flow Example
+
+```python Code
+from crewai.flow import (
+    Flow, start, listen, human_feedback,
+    HumanFeedbackProvider, HumanFeedbackPending, PendingFeedbackContext
+)
+
+class SlackNotificationProvider(HumanFeedbackProvider):
+    """Provider that sends Slack notifications and pauses for async feedback."""
+
+    def __init__(self, channel: str):
+        self.channel = channel
+
+    def request_feedback(self, context: PendingFeedbackContext, flow: Flow) -> str:
+        # Send Slack notification (implement your own)
+        slack_thread_id = self.post_to_slack(
+            channel=self.channel,
+            message=f"Review needed:\n\n{context.method_output}\n\n{context.message}",
+        )
+
+        # Pause execution - framework handles persistence automatically
+        raise HumanFeedbackPending(
+            context=context,
+            callback_info={
+                "slack_channel": self.channel,
+                "thread_id": slack_thread_id,
+            }
+        )
+
+class ContentPipeline(Flow):
+    @start()
+    @human_feedback(
+        message="Approve this content for publication?",
+        emit=["approved", "rejected", "needs_revision"],
+        llm="gpt-4o-mini",
+        default_outcome="needs_revision",
+        provider=SlackNotificationProvider("#content-reviews"),
+    )
+    def generate_content(self):
+        return "AI-generated blog post content..."
+
+    @listen("approved")
+    def publish(self, result):
+        print(f"Publishing! Reviewer said: {result.feedback}")
+        return {"status": "published"}
+
+    @listen("rejected")
+    def archive(self, result):
+        print(f"Archived. Reason: {result.feedback}")
+        return {"status": "archived"}
+
+    @listen("needs_revision")
+    def queue_revision(self, result):
+        print(f"Queued for revision: {result.feedback}")
+        return {"status": "revision_needed"}
+
+
+# Starting the flow (will pause and wait for Slack response)
+def start_content_pipeline():
+    flow = ContentPipeline()
+    result = flow.kickoff()
+
+    if isinstance(result, HumanFeedbackPending):
+        return {"status": "pending", "flow_id": result.context.flow_id}
+
+    return result
+
+
+# Resuming when Slack webhook fires (sync handler)
+def on_slack_feedback(flow_id: str, slack_message: str):
+    flow = ContentPipeline.from_pending(flow_id)
+    result = flow.resume(slack_message)
+    return result
+
+
+# If your handler is async (FastAPI, aiohttp, Slack Bolt async, etc.)
+async def on_slack_feedback_async(flow_id: str, slack_message: str):
+    flow = ContentPipeline.from_pending(flow_id)
+    result = await flow.resume_async(slack_message)
+    return result
+```
+
+<Warning>
+If you're using an async web framework (FastAPI, aiohttp, Slack Bolt async mode), use `await flow.resume_async()` instead of `flow.resume()`. Calling `resume()` from within a running event loop will raise a `RuntimeError`.
+</Warning>
+
+### Best Practices for Async Feedback
+
+1. **Check the return type**: `kickoff()` returns `HumanFeedbackPending` when paused—no try/except needed
+2. **Use the right resume method**: Use `resume()` in sync code, `await resume_async()` in async code
+3. **Store callback info**: Use `callback_info` to store webhook URLs, ticket IDs, etc.
+4. **Implement idempotency**: Your resume handler should be idempotent for safety
+5. **Automatic persistence**: State is automatically saved when `HumanFeedbackPending` is raised and uses `SQLiteFlowPersistence` by default
+6. **Custom persistence**: Pass a custom persistence instance to `from_pending()` if needed
+
+## Related Documentation
+
+- [Flows Overview](/en/concepts/flows) - Learn about CrewAI Flows
+- [Flow State Management](/en/guides/flows/mastering-flow-state) - Managing state in flows
+- [Flow Persistence](/en/concepts/flows#persistence) - Persisting flow state
+- [Routing with @router](/en/concepts/flows#router) - More about conditional routing
+- [Human Input on Execution](/en/learn/human-input-on-execution) - Task-level human input

docs/en/learn/human-in-the-loop.mdx

@@ -5,9 +5,22 @@ icon: "user-check"
 mode: "wide"
 ---
 
-Human-in-the-Loop (HITL) is a powerful approach that combines artificial intelligence with human expertise to enhance decision-making and improve task outcomes. This guide shows you how to implement HITL within CrewAI.
+Human-in-the-Loop (HITL) is a powerful approach that combines artificial intelligence with human expertise to enhance decision-making and improve task outcomes. CrewAI provides multiple ways to implement HITL depending on your needs.
 
-## Setting Up HITL Workflows
+## Choosing Your HITL Approach
+
+CrewAI offers two main approaches for implementing human-in-the-loop workflows:
+
+| Approach | Best For | Integration |
+|----------|----------|-------------|
+| **Flow-based** (`@human_feedback` decorator) | Local development, console-based review, synchronous workflows | [Human Feedback in Flows](/en/learn/human-feedback-in-flows) |
+| **Webhook-based** (Enterprise) | Production deployments, async workflows, external integrations (Slack, Teams, etc.) | This guide |
+
+<Tip>
+If you're building flows and want to add human review steps with routing based on feedback, check out the [Human Feedback in Flows](/en/learn/human-feedback-in-flows) guide for the `@human_feedback` decorator.
+</Tip>
+
+## Setting Up Webhook-Based HITL Workflows
 
 <Steps>
     <Step title="Configure Your Task">

docs/en/learn/llm-selection-guide.mdx

@@ -1,7 +1,7 @@
 ---
-title: 'Strategic LLM Selection Guide'
-description: 'Strategic framework for choosing the right LLM for your CrewAI AI agents and writing effective task and agent definitions'
-icon: 'brain-circuit'
+title: "Strategic LLM Selection Guide"
+description: "Strategic framework for choosing the right LLM for your CrewAI AI agents and writing effective task and agent definitions"
+icon: "brain-circuit"
 mode: "wide"
 ---
 
@@ -10,23 +10,35 @@ mode: "wide"
 Rather than prescriptive model recommendations, we advocate for a **thinking framework** that helps you make informed decisions based on your specific use case, constraints, and requirements. The LLM landscape evolves rapidly, with new models emerging regularly and existing ones being updated frequently. What matters most is developing a systematic approach to evaluation that remains relevant regardless of which specific models are available.
 
 <Note>
-This guide focuses on strategic thinking rather than specific model recommendations, as the LLM landscape evolves rapidly.
+  This guide focuses on strategic thinking rather than specific model
+  recommendations, as the LLM landscape evolves rapidly.
 </Note>
 
 ## Quick Decision Framework
 
 <Steps>
   <Step title="Analyze Your Tasks">
-    Begin by deeply understanding what your tasks actually require. Consider the cognitive complexity involved, the depth of reasoning needed, the format of expected outputs, and the amount of context the model will need to process. This foundational analysis will guide every subsequent decision.
+    Begin by deeply understanding what your tasks actually require. Consider the
+    cognitive complexity involved, the depth of reasoning needed, the format of
+    expected outputs, and the amount of context the model will need to process.
+    This foundational analysis will guide every subsequent decision.
   </Step>
   <Step title="Map Model Capabilities">
-    Once you understand your requirements, map them to model strengths. Different model families excel at different types of work; some are optimized for reasoning and analysis, others for creativity and content generation, and others for speed and efficiency.
+    Once you understand your requirements, map them to model strengths.
+    Different model families excel at different types of work; some are
+    optimized for reasoning and analysis, others for creativity and content
+    generation, and others for speed and efficiency.
   </Step>
   <Step title="Consider Constraints">
-    Factor in your real-world operational constraints including budget limitations, latency requirements, data privacy needs, and infrastructure capabilities. The theoretically best model may not be the practically best choice for your situation.
+    Factor in your real-world operational constraints including budget
+    limitations, latency requirements, data privacy needs, and infrastructure
+    capabilities. The theoretically best model may not be the practically best
+    choice for your situation.
   </Step>
   <Step title="Test and Iterate">
-    Start with reliable, well-understood models and optimize based on actual performance in your specific use case. Real-world results often differ from theoretical benchmarks, so empirical testing is crucial.
+    Start with reliable, well-understood models and optimize based on actual
+    performance in your specific use case. Real-world results often differ from
+    theoretical benchmarks, so empirical testing is crucial.
   </Step>
 </Steps>
 
@@ -43,6 +55,7 @@ The most critical step in LLM selection is understanding what your task actually
     - **Complex Tasks** require multi-step reasoning, strategic thinking, and the ability to handle ambiguous or incomplete information. These might involve analyzing multiple data sources, developing comprehensive strategies, or solving problems that require breaking down into smaller components. The model needs to maintain context across multiple reasoning steps and often must make inferences that aren't explicitly stated.
 
     - **Creative Tasks** demand a different type of cognitive capability focused on generating novel, engaging, and contextually appropriate content. This includes storytelling, marketing copy creation, and creative problem-solving. The model needs to understand nuance, tone, and audience while producing content that feels authentic and engaging rather than formulaic.
+
   </Tab>
 
   <Tab title="Output Requirements">
@@ -51,6 +64,7 @@ The most critical step in LLM selection is understanding what your task actually
     - **Creative Content** outputs demand a balance of technical competence and creative flair. The model needs to understand audience, tone, and brand voice while producing content that engages readers and achieves specific communication goals. Quality here is often subjective and requires models that can adapt their writing style to different contexts and purposes.
 
     - **Technical Content** sits between structured data and creative content, requiring both precision and clarity. Documentation, code generation, and technical analysis need to be accurate and comprehensive while remaining accessible to the intended audience. The model must understand complex technical concepts and communicate them effectively.
+
   </Tab>
 
   <Tab title="Context Needs">
@@ -59,6 +73,7 @@ The most critical step in LLM selection is understanding what your task actually
     - **Long Context** requirements emerge when working with substantial documents, extended conversations, or complex multi-part tasks. The model needs to maintain coherence across thousands of tokens while referencing earlier information accurately. This capability becomes crucial for document analysis, comprehensive research, and sophisticated dialogue systems.
 
     - **Very Long Context** scenarios push the boundaries of what's currently possible, involving massive document processing, extensive research synthesis, or complex multi-session interactions. These use cases require models specifically designed for extended context handling and often involve trade-offs between context length and processing speed.
+
   </Tab>
 </Tabs>
 
@@ -73,6 +88,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
     The strength of reasoning models lies in their ability to maintain logical consistency across extended reasoning chains and to break down complex problems into manageable components. They're particularly valuable for strategic planning, complex analysis, and situations where the quality of reasoning matters more than speed of response.
 
     However, reasoning models often come with trade-offs in terms of speed and cost. They may also be less suitable for creative tasks or simple operations where their sophisticated reasoning capabilities aren't needed. Consider these models when your tasks involve genuine complexity that benefits from systematic, step-by-step analysis.
+
   </Accordion>
 
   <Accordion title="General Purpose Models" icon="microchip">
@@ -81,6 +97,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
     The primary advantage of general purpose models is their reliability and predictability across different types of work. They handle most standard business tasks competently, from research and analysis to content creation and data processing. This makes them excellent choices for teams that need consistent performance across varied workflows.
 
     While general purpose models may not achieve the peak performance of specialized alternatives in specific domains, they offer operational simplicity and reduced complexity in model management. They're often the best starting point for new projects, allowing teams to understand their specific needs before potentially optimizing with more specialized models.
+
   </Accordion>
 
   <Accordion title="Fast & Efficient Models" icon="bolt">
@@ -89,6 +106,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
     These models excel in scenarios involving routine operations, simple data processing, function calling, and high-volume tasks where the cognitive requirements are relatively straightforward. They're particularly valuable for applications that need to process many requests quickly or operate within tight budget constraints.
 
     The key consideration with efficient models is ensuring that their capabilities align with your task requirements. While they can handle many routine operations effectively, they may struggle with tasks requiring nuanced understanding, complex reasoning, or sophisticated content generation. They're best used for well-defined, routine operations where speed and cost matter more than sophistication.
+
   </Accordion>
 
   <Accordion title="Creative Models" icon="pen">
@@ -97,6 +115,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
     The strength of creative models lies in their ability to adapt writing style to different audiences, maintain consistent voice and tone, and generate content that engages readers effectively. They often perform better on tasks involving storytelling, marketing copy, brand communications, and other content where creativity and engagement are primary goals.
 
     When selecting creative models, consider not just their ability to generate text, but their understanding of audience, context, and purpose. The best creative models can adapt their output to match specific brand voices, target different audience segments, and maintain consistency across extended content pieces.
+
   </Accordion>
 
   <Accordion title="Open Source Models" icon="code">
@@ -105,6 +124,7 @@ Understanding model capabilities requires looking beyond marketing claims and be
     The primary benefits of open source models include elimination of per-token costs, ability to fine-tune for specific use cases, complete data privacy, and independence from external API providers. They're particularly valuable for organizations with strict data privacy requirements, budget constraints, or specific customization needs.
 
     However, open source models require more technical expertise to deploy and maintain effectively. Teams need to consider infrastructure costs, model management complexity, and the ongoing effort required to keep models updated and optimized. The total cost of ownership may be higher than cloud-based alternatives when factoring in technical overhead.
+
   </Accordion>
 </AccordionGroup>
 
@@ -113,7 +133,8 @@ Understanding model capabilities requires looking beyond marketing claims and be
 ### a. Multi-Model Approach
 
 <Tip>
-Use different models for different purposes within the same crew to optimize both performance and cost.
+  Use different models for different purposes within the same crew to optimize
+  both performance and cost.
 </Tip>
 
 The most sophisticated CrewAI implementations often employ multiple models strategically, assigning different models to different agents based on their specific roles and requirements. This approach allows teams to optimize for both performance and cost by using the most appropriate model for each type of work.
@@ -177,6 +198,7 @@ The key to successful multi-model implementation is understanding how different
     Effective manager LLMs require strong reasoning capabilities to make good delegation decisions, consistent performance to ensure predictable coordination, and excellent context management to track the state of multiple agents simultaneously. The model needs to understand the capabilities and limitations of different agents while optimizing task allocation for efficiency and quality.
 
     Cost considerations are particularly important for manager LLMs since they're involved in every operation. The model needs to provide sufficient capability for effective coordination while remaining cost-effective for frequent use. This often means finding models that offer good reasoning capabilities without the premium pricing of the most sophisticated options.
+
   </Tab>
 
   <Tab title="Function Calling LLM">
@@ -185,6 +207,7 @@ The key to successful multi-model implementation is understanding how different
     The most important characteristics for function calling LLMs are precision and reliability rather than creativity or sophisticated reasoning. The model needs to consistently extract the correct parameters from natural language requests and handle tool responses appropriately. Speed is also important since tool usage often involves multiple round trips that can impact overall performance.
 
     Many teams find that specialized function calling models or general purpose models with strong tool support work better than creative or reasoning-focused models for this role. The key is ensuring that the model can reliably bridge the gap between natural language instructions and structured tool calls.
+
   </Tab>
 
   <Tab title="Agent-Specific Overrides">
@@ -193,6 +216,7 @@ The key to successful multi-model implementation is understanding how different
     Consider agent-specific overrides when an agent's role requires capabilities that differ substantially from other crew members. For example, a creative writing agent might benefit from a model optimized for content generation, while a data analysis agent might perform better with a reasoning-focused model.
 
     The challenge with agent-specific overrides is balancing optimization with operational complexity. Each additional model adds complexity to deployment, monitoring, and cost management. Teams should focus overrides on agents where the performance improvement justifies the additional complexity.
+
   </Tab>
 </Tabs>
 
@@ -209,6 +233,7 @@ Effective task definition is often more important than model selection in determ
     Effective task descriptions include relevant context and constraints that help the agent understand the broader purpose and any limitations they need to work within. They break complex work into focused steps that can be executed systematically, rather than presenting overwhelming, multi-faceted objectives that are difficult to approach systematically.
 
     Common mistakes include being too vague about objectives, failing to provide necessary context, setting unclear success criteria, or combining multiple unrelated tasks into a single description. The goal is to provide enough information for the agent to succeed while maintaining focus on a single, clear objective.
+
   </Accordion>
 
   <Accordion title="Expected Output Guidelines" icon="bullseye">
@@ -217,6 +242,7 @@ Effective task definition is often more important than model selection in determ
     The best output guidelines provide concrete examples of quality indicators and define completion criteria clearly enough that both the agent and human reviewers can assess whether the task has been completed successfully. This reduces ambiguity and helps ensure consistent results across multiple task executions.
 
     Avoid generic output descriptions that could apply to any task, missing format specifications that leave agents guessing about structure, unclear quality standards that make evaluation difficult, or failing to provide examples or templates that help agents understand expectations.
+
   </Accordion>
 </AccordionGroup>
 
@@ -229,6 +255,7 @@ Effective task definition is often more important than model selection in determ
     Implementing sequential dependencies effectively requires using the context parameter to chain related tasks, building complexity gradually through task progression, and ensuring that each task produces outputs that serve as meaningful inputs for subsequent tasks. The goal is to maintain logical flow between dependent tasks while avoiding unnecessary bottlenecks.
 
     Sequential dependencies work best when there's a clear logical progression from one task to another and when the output of one task genuinely improves the quality or feasibility of subsequent tasks. However, they can create bottlenecks if not managed carefully, so it's important to identify which dependencies are truly necessary versus those that are merely convenient.
+
   </Tab>
 
   <Tab title="Parallel Execution">
@@ -237,6 +264,7 @@ Effective task definition is often more important than model selection in determ
     Successful parallel execution requires identifying tasks that can truly run independently, grouping related but separate work streams effectively, and planning for result integration when parallel tasks need to be combined into a final deliverable. The key is ensuring that parallel tasks don't create conflicts or redundancies that reduce overall quality.
 
     Consider parallel execution when you have multiple independent research streams, different types of analysis that don't depend on each other, or content creation tasks that can be developed simultaneously. However, be mindful of resource allocation and ensure that parallel execution doesn't overwhelm your available model capacity or budget.
+
   </Tab>
 </Tabs>
 
@@ -245,7 +273,8 @@ Effective task definition is often more important than model selection in determ
 ### a. Role-Driven LLM Selection
 
 <Warning>
-Generic agent roles make it impossible to select the right LLM. Specific roles enable targeted model optimization.
+  Generic agent roles make it impossible to select the right LLM. Specific roles
+  enable targeted model optimization.
 </Warning>
 
 The specificity of your agent roles directly determines which LLM capabilities matter most for optimal performance. This creates a strategic opportunity to match precise model strengths with agent responsibilities.
@@ -253,6 +282,7 @@ The specificity of your agent roles directly determines which LLM capabilities m
 **Generic vs. Specific Role Impact on LLM Choice:**
 
 When defining roles, think about the specific domain knowledge, working style, and decision-making frameworks that would be most valuable for the tasks the agent will handle. The more specific and contextual the role definition, the better the model can embody that role effectively.
+
 ```python
 # ✅ Specific role - clear LLM requirements
 specific_agent = Agent(
@@ -273,7 +303,8 @@ specific_agent = Agent(
 ### b. Backstory as Model Context Amplifier
 
 <Info>
-Strategic backstories multiply your chosen LLM's effectiveness by providing domain-specific context that generic prompting cannot achieve.
+  Strategic backstories multiply your chosen LLM's effectiveness by providing
+  domain-specific context that generic prompting cannot achieve.
 </Info>
 
 A well-crafted backstory transforms your LLM choice from generic capability to specialized expertise. This is especially crucial for cost optimization - a well-contextualized efficient model can outperform a premium model without proper context.
@@ -300,6 +331,7 @@ domain_expert = Agent(
 ```
 
 **Backstory Elements That Enhance LLM Performance:**
+
 - **Domain Experience**: "10+ years in enterprise SaaS sales"
 - **Specific Expertise**: "Specializes in technical due diligence for Series B+ rounds"
 - **Working Style**: "Prefers data-driven decisions with clear documentation"
@@ -332,6 +364,7 @@ tech_writer = Agent(
 ```
 
 **Alignment Checklist:**
+
 - ✅ **Role Specificity**: Clear domain and responsibilities
 - ✅ **LLM Match**: Model strengths align with role requirements
 - ✅ **Backstory Depth**: Provides domain context the LLM can leverage
@@ -353,6 +386,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     - Are any agents heavily tool-dependent?
 
     **Action**: Document current agent roles and identify optimization opportunities.
+
   </Step>
 
   <Step title="Implement Crew-Level Strategy" icon="users-gear">
@@ -369,6 +403,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     ```
 
     **Action**: Establish your crew's default LLM before optimizing individual agents.
+
   </Step>
 
   <Step title="Optimize High-Impact Agents" icon="star">
@@ -390,16 +425,18 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     ```
 
     **Action**: Upgrade 20% of your agents that handle 80% of the complexity.
+
   </Step>
 
   <Step title="Validate with Enterprise Testing" icon="test-tube">
     **Once you deploy your agents to production:**
-    - Use [CrewAI AOP platform](https://app.crewai.com) to A/B test your model selections
+    - Use [CrewAI AMP platform](https://app.crewai.com) to A/B test your model selections
     - Run multiple iterations with real inputs to measure consistency and performance
     - Compare cost vs. performance across your optimized setup
     - Share results with your team for collaborative decision-making
 
     **Action**: Replace guesswork with data-driven validation using the testing platform.
+
   </Step>
 </Steps>
 
@@ -412,6 +449,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     Consider reasoning models for business strategy development, complex data analysis that requires drawing insights from multiple sources, multi-step problem solving where each step depends on previous analysis, and strategic planning tasks that require considering multiple variables and their interactions.
 
     However, reasoning models often come with higher costs and slower response times, so they're best reserved for tasks where their sophisticated capabilities provide genuine value rather than being used for simple operations that don't require complex reasoning.
+
   </Tab>
 
   <Tab title="Creative Models">
@@ -420,6 +458,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     Use creative models for blog post writing and article creation, marketing copy that needs to engage and persuade, creative storytelling and narrative development, and brand communications where voice and tone are crucial. These models often understand nuance and context better than general purpose alternatives.
 
     Creative models may be less suitable for technical or analytical tasks where precision and factual accuracy are more important than engagement and style. They're best used when the creative and communicative aspects of the output are primary success factors.
+
   </Tab>
 
   <Tab title="Efficient Models">
@@ -428,6 +467,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     Consider efficient models for data processing and transformation tasks, simple formatting and organization operations, function calling and tool usage where precision matters more than sophistication, and high-volume operations where cost per operation is a significant factor.
 
     The key with efficient models is ensuring that their capabilities align with task requirements. They can handle many routine operations effectively but may struggle with tasks requiring nuanced understanding, complex reasoning, or sophisticated content generation.
+
   </Tab>
 
   <Tab title="Open Source Models">
@@ -436,6 +476,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     Consider open source models for internal company tools where data privacy is paramount, privacy-sensitive applications that can't use external APIs, cost-optimized deployments where per-token pricing is prohibitive, and situations requiring custom model modifications or fine-tuning.
 
     However, open source models require more technical expertise to deploy and maintain effectively. Consider the total cost of ownership including infrastructure, technical overhead, and ongoing maintenance when evaluating open source options.
+
   </Tab>
 </Tabs>
 
@@ -455,6 +496,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     # Processing agent gets efficient model
     processor = Agent(role="Data Processor", llm=LLM(model="gpt-4o-mini"))
     ```
+
   </Accordion>
 
   <Accordion title="Ignoring Crew-Level vs Agent-Level LLM Hierarchy" icon="shuffle">
@@ -474,6 +516,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     # Agents inherit crew LLM unless specifically overridden
     agent1 = Agent(llm=LLM(model="claude-3-5-sonnet"))  # Override for specific needs
     ```
+
   </Accordion>
 
   <Accordion title="Function Calling Model Mismatch" icon="screwdriver-wrench">
@@ -492,6 +535,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
         llm=LLM(model="claude-3-5-sonnet")  # Also strong with tools
     )
     ```
+
   </Accordion>
 
   <Accordion title="Premature Optimization Without Testing" icon="gear">
@@ -507,6 +551,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     # Test performance, then optimize specific agents as needed
     # Use Enterprise platform testing to validate improvements
     ```
+
   </Accordion>
 
   <Accordion title="Overlooking Context and Memory Limitations" icon="brain">
@@ -515,6 +560,7 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
     **Real Example**: Using a short-context model for agents that need to maintain conversation history across multiple task iterations, or in crews with extensive agent-to-agent communication.
 
     **CrewAI Solution**: Match context capabilities to crew communication patterns.
+
   </Accordion>
 </AccordionGroup>
 
@@ -522,26 +568,40 @@ Rather than repeating the strategic framework, here's a tactical checklist for i
 
 <Steps>
   <Step title="Start Simple" icon="play">
-    Begin with reliable, general-purpose models that are well-understood and widely supported. This provides a stable foundation for understanding your specific requirements and performance expectations before optimizing for specialized needs.
+    Begin with reliable, general-purpose models that are well-understood and
+    widely supported. This provides a stable foundation for understanding your
+    specific requirements and performance expectations before optimizing for
+    specialized needs.
   </Step>
   <Step title="Measure What Matters" icon="chart-line">
-    Develop metrics that align with your specific use case and business requirements rather than relying solely on general benchmarks. Focus on measuring outcomes that directly impact your success rather than theoretical performance indicators.
+    Develop metrics that align with your specific use case and business
+    requirements rather than relying solely on general benchmarks. Focus on
+    measuring outcomes that directly impact your success rather than theoretical
+    performance indicators.
   </Step>
   <Step title="Iterate Based on Results" icon="arrows-rotate">
-    Make model changes based on observed performance in your specific context rather than theoretical considerations or general recommendations. Real-world performance often differs significantly from benchmark results or general reputation.
+    Make model changes based on observed performance in your specific context
+    rather than theoretical considerations or general recommendations.
+    Real-world performance often differs significantly from benchmark results or
+    general reputation.
   </Step>
   <Step title="Consider Total Cost" icon="calculator">
-    Evaluate the complete cost of ownership including model costs, development time, maintenance overhead, and operational complexity. The cheapest model per token may not be the most cost-effective choice when considering all factors.
+    Evaluate the complete cost of ownership including model costs, development
+    time, maintenance overhead, and operational complexity. The cheapest model
+    per token may not be the most cost-effective choice when considering all
+    factors.
   </Step>
 </Steps>
 
 <Tip>
-Focus on understanding your requirements first, then select models that best match those needs. The best LLM choice is the one that consistently delivers the results you need within your operational constraints.
+  Focus on understanding your requirements first, then select models that best
+  match those needs. The best LLM choice is the one that consistently delivers
+  the results you need within your operational constraints.
 </Tip>
 
 ### Enterprise-Grade Model Validation
 
-For teams serious about optimizing their LLM selection, the **CrewAI AOP platform** provides sophisticated testing capabilities that go far beyond basic CLI testing. The platform enables comprehensive model evaluation that helps you make data-driven decisions about your LLM strategy.
+For teams serious about optimizing their LLM selection, the **CrewAI AMP platform** provides sophisticated testing capabilities that go far beyond basic CLI testing. The platform enables comprehensive model evaluation that helps you make data-driven decisions about your LLM strategy.
 
 <Frame>
   ![Enterprise Testing Interface](/images/enterprise/enterprise-testing.png)
@@ -562,7 +622,9 @@ For teams serious about optimizing their LLM selection, the **CrewAI AOP platfor
 Go to [app.crewai.com](https://app.crewai.com) to get started!
 
 <Info>
-The Enterprise platform transforms model selection from guesswork into a data-driven process, enabling you to validate the principles in this guide with your actual use cases and requirements.
+  The Enterprise platform transforms model selection from guesswork into a
+  data-driven process, enabling you to validate the principles in this guide
+  with your actual use cases and requirements.
 </Info>
 
 ## Key Principles Summary
@@ -572,21 +634,27 @@ The Enterprise platform transforms model selection from guesswork into a data-dr
     Choose models based on what the task actually requires, not theoretical capabilities or general reputation.
   </Card>
 
-  <Card title="Capability Matching" icon="puzzle-piece">
-    Align model strengths with agent roles and responsibilities for optimal performance.
-  </Card>
+{" "}
+<Card title="Capability Matching" icon="puzzle-piece">
+  Align model strengths with agent roles and responsibilities for optimal
+  performance.
+</Card>
 
-  <Card title="Strategic Consistency" icon="link">
-    Maintain coherent model selection strategy across related components and workflows.
-  </Card>
+{" "}
+<Card title="Strategic Consistency" icon="link">
+  Maintain coherent model selection strategy across related components and
+  workflows.
+</Card>
 
-  <Card title="Practical Testing" icon="flask">
-    Validate choices through real-world usage rather than benchmarks alone.
-  </Card>
+{" "}
+<Card title="Practical Testing" icon="flask">
+  Validate choices through real-world usage rather than benchmarks alone.
+</Card>
 
-  <Card title="Iterative Improvement" icon="arrow-up">
-    Start simple and optimize based on actual performance and needs.
-  </Card>
+{" "}
+<Card title="Iterative Improvement" icon="arrow-up">
+  Start simple and optimize based on actual performance and needs.
+</Card>
 
   <Card title="Operational Balance" icon="scale-balanced">
     Balance performance requirements with cost and complexity constraints.
@@ -594,13 +662,20 @@ The Enterprise platform transforms model selection from guesswork into a data-dr
 </CardGroup>
 
 <Check>
-Remember: The best LLM choice is the one that consistently delivers the results you need within your operational constraints. Focus on understanding your requirements first, then select models that best match those needs.
+  Remember: The best LLM choice is the one that consistently delivers the
+  results you need within your operational constraints. Focus on understanding
+  your requirements first, then select models that best match those needs.
 </Check>
 
 ## Current Model Landscape (June 2025)
 
 <Warning>
-**Snapshot in Time**: The following model rankings represent current leaderboard standings as of June 2025, compiled from [LMSys Arena](https://arena.lmsys.org/), [Artificial Analysis](https://artificialanalysis.ai/), and other leading benchmarks. LLM performance, availability, and pricing change rapidly. Always conduct your own evaluations with your specific use cases and data.
+  **Snapshot in Time**: The following model rankings represent current
+  leaderboard standings as of June 2025, compiled from [LMSys
+  Arena](https://arena.lmsys.org/), [Artificial
+  Analysis](https://artificialanalysis.ai/), and other leading benchmarks. LLM
+  performance, availability, and pricing change rapidly. Always conduct your own
+  evaluations with your specific use cases and data.
 </Warning>
 
 ### Leading Models by Category
@@ -608,7 +683,10 @@ Remember: The best LLM choice is the one that consistently delivers the results
 The tables below show a representative sample of current top-performing models across different categories, with guidance on their suitability for CrewAI agents:
 
 <Note>
-These tables/metrics showcase selected leading models in each category and are not exhaustive. Many excellent models exist beyond those listed here. The goal is to illustrate the types of capabilities to look for rather than provide a complete catalog.
+  These tables/metrics showcase selected leading models in each category and are
+  not exhaustive. Many excellent models exist beyond those listed here. The goal
+  is to illustrate the types of capabilities to look for rather than provide a
+  complete catalog.
 </Note>
 
 <Tabs>
@@ -624,6 +702,7 @@ These tables/metrics showcase selected leading models in each category and are n
     | **Qwen3 235B (Reasoning)** | 62 | $2.63 | Moderate | Open-source alternative for reasoning tasks |
 
     These models excel at multi-step reasoning and are ideal for agents that need to develop strategies, coordinate other agents, or analyze complex information.
+
   </Tab>
 
   <Tab title="Coding & Technical">
@@ -638,6 +717,7 @@ These tables/metrics showcase selected leading models in each category and are n
     | **Llama 3.1 405B** | Good | 81.1% | $3.50 | Function calling LLM for tool-heavy workflows |
 
     These models are optimized for code generation, debugging, and technical problem-solving, making them ideal for development-focused crews.
+
   </Tab>
 
   <Tab title="Speed & Efficiency">
@@ -652,6 +732,7 @@ These tables/metrics showcase selected leading models in each category and are n
     | **Nova Micro** | High | 0.30s | $0.04 | Simple, fast task execution |
 
     These models prioritize speed and efficiency, perfect for agents handling routine operations or requiring quick responses. **Pro tip**: Pairing these models with fast inference providers like Groq can achieve even better performance, especially for open-source models like Llama.
+
   </Tab>
 
   <Tab title="Balanced Performance">
@@ -666,6 +747,7 @@ These tables/metrics showcase selected leading models in each category and are n
     | **Qwen3 32B** | 44 | Good | $1.23 | Budget-friendly versatility |
 
     These models offer good performance across multiple dimensions, suitable for crews with diverse task requirements.
+
   </Tab>
 </Tabs>
 
@@ -676,24 +758,28 @@ These tables/metrics showcase selected leading models in each category and are n
     **When performance is the priority**: Use top-tier models like **o3**, **Gemini 2.5 Pro**, or **Claude 4 Sonnet** for manager LLMs and critical agents. These models excel at complex reasoning and coordination but come with higher costs.
 
     **Strategy**: Implement a multi-model approach where premium models handle strategic thinking while efficient models handle routine operations.
+
   </Accordion>
 
   <Accordion title="Cost-Conscious Crews" icon="dollar-sign">
     **When budget is a primary constraint**: Focus on models like **DeepSeek R1**, **Llama 4 Scout**, or **Gemini 2.0 Flash**. These provide strong performance at significantly lower costs.
 
     **Strategy**: Use cost-effective models for most agents, reserving premium models only for the most critical decision-making roles.
+
   </Accordion>
 
   <Accordion title="Specialized Workflows" icon="screwdriver-wrench">
     **For specific domain expertise**: Choose models optimized for your primary use case. **Claude 4** series for coding, **Gemini 2.5 Pro** for research, **Llama 405B** for function calling.
 
     **Strategy**: Select models based on your crew's primary function, ensuring the core capability aligns with model strengths.
+
   </Accordion>
 
   <Accordion title="Enterprise & Privacy" icon="shield">
     **For data-sensitive operations**: Consider open-source models like **Llama 4** series, **DeepSeek V3**, or **Qwen3** that can be deployed locally while maintaining competitive performance.
 
     **Strategy**: Deploy open-source models on private infrastructure, accepting potential performance trade-offs for data control.
+
   </Accordion>
   </AccordionGroup>
 
@@ -706,7 +792,10 @@ These tables/metrics showcase selected leading models in each category and are n
 - **Open Source Viability**: The gap between open-source and proprietary models continues to narrow, with models like Llama 4 Maverick and DeepSeek V3 offering competitive performance at attractive price points. Fast inference providers particularly shine with open-source models, often delivering better speed-to-cost ratios than proprietary alternatives.
 
 <Info>
-**Testing is Essential**: Leaderboard rankings provide general guidance, but your specific use case, prompting style, and evaluation criteria may produce different results. Always test candidate models with your actual tasks and data before making final decisions.
+  **Testing is Essential**: Leaderboard rankings provide general guidance, but
+  your specific use case, prompting style, and evaluation criteria may produce
+  different results. Always test candidate models with your actual tasks and
+  data before making final decisions.
 </Info>
 
 ### Practical Implementation Strategy
@@ -716,13 +805,20 @@ These tables/metrics showcase selected leading models in each category and are n
     Begin with well-established models like **GPT-4.1**, **Claude 3.7 Sonnet**, or **Gemini 2.0 Flash** that offer good performance across multiple dimensions and have extensive real-world validation.
   </Step>
 
-  <Step title="Identify Specialized Needs">
-    Determine if your crew has specific requirements (coding, reasoning, speed) that would benefit from specialized models like **Claude 4 Sonnet** for development or **o3** for complex analysis. For speed-critical applications, consider fast inference providers like **Groq** alongside model selection.
-  </Step>
+{" "}
+<Step title="Identify Specialized Needs">
+  Determine if your crew has specific requirements (coding, reasoning, speed)
+  that would benefit from specialized models like **Claude 4 Sonnet** for
+  development or **o3** for complex analysis. For speed-critical applications,
+  consider fast inference providers like **Groq** alongside model selection.
+</Step>
 
-  <Step title="Implement Multi-Model Strategy">
-    Use different models for different agents based on their roles. High-capability models for managers and complex tasks, efficient models for routine operations.
-  </Step>
+{" "}
+<Step title="Implement Multi-Model Strategy">
+  Use different models for different agents based on their roles.
+  High-capability models for managers and complex tasks, efficient models for
+  routine operations.
+</Step>
 
   <Step title="Monitor and Optimize">
     Track performance metrics relevant to your use case and be prepared to adjust model selections as new models are released or pricing changes.

docs/en/mcp/dsl-integration.mdx

@@ -10,7 +10,9 @@ mode: "wide"
 CrewAI's MCP DSL (Domain Specific Language) integration provides the **simplest way** to connect your agents to MCP (Model Context Protocol) servers. Just add an `mcps` field to your agent and CrewAI handles all the complexity automatically.
 
 <Info>
-This is the **recommended approach** for most MCP use cases. For advanced scenarios requiring manual connection management, see [MCPServerAdapter](/en/mcp/overview#advanced-mcpserveradapter).
+  This is the **recommended approach** for most MCP use cases. For advanced
+  scenarios requiring manual connection management, see
+  [MCPServerAdapter](/en/mcp/overview#advanced-mcpserveradapter).
 </Info>
 
 ## Basic Usage
@@ -60,9 +62,9 @@ Use the `#` syntax to select specific tools from a server:
 "https://mcp.exa.ai/mcp?api_key=your_key#web_search_exa"
 ```
 
-### CrewAI AOP Marketplace
+### CrewAI AMP Marketplace
 
-Access tools from the CrewAI AOP marketplace:
+Access tools from the CrewAI AMP marketplace:
 
 ```python
 # Full service with all tools
@@ -97,7 +99,7 @@ multi_source_agent = Agent(
         "https://mcp.exa.ai/mcp?api_key=your_exa_key&profile=research",
         "https://weather.api.com/mcp#get_current_conditions",
 
-        # CrewAI AOP marketplace
+        # CrewAI AMP marketplace
         "crewai-amp:financial-insights",
         "crewai-amp:academic-research#pubmed_search",
         "crewai-amp:market-intelligence#competitor_analysis"
@@ -319,6 +321,7 @@ agent = Agent(
 ### Common Issues
 
 **No tools discovered:**
+
 ```python
 # Check your MCP server URL and authentication
 # Verify the server is running and accessible
@@ -326,6 +329,7 @@ mcps=["https://mcp.example.com/mcp?api_key=valid_key"]
 ```
 
 **Connection timeouts:**
+
 ```python
 # Server may be slow or overloaded
 # CrewAI will log warnings and continue with other servers
@@ -333,6 +337,7 @@ mcps=["https://mcp.example.com/mcp?api_key=valid_key"]
 ```
 
 **Authentication failures:**
+
 ```python
 # Verify API keys and credentials
 # Check server documentation for required parameters

docs/en/mcp/overview.mdx

@@ -1,6 +1,6 @@
 ---
-title: 'MCP Servers as Tools in CrewAI'
-description: 'Learn how to integrate MCP servers as tools in your CrewAI agents using the `crewai-tools` library.'
+title: "MCP Servers as Tools in CrewAI"
+description: "Learn how to integrate MCP servers as tools in your CrewAI agents using the `crewai-tools` library."
 icon: plug
 mode: "wide"
 ---
@@ -17,7 +17,7 @@ Use the `mcps` field directly on agents for seamless MCP tool integration. The D
 
 #### String-Based References (Quick Setup)
 
-Perfect for remote HTTPS servers and CrewAI AOP marketplace:
+Perfect for remote HTTPS servers and CrewAI AMP marketplace:
 
 ```python
 from crewai import Agent
@@ -29,7 +29,7 @@ agent = Agent(
     mcps=[
         "https://mcp.exa.ai/mcp?api_key=your_key",           # External MCP server
         "https://api.weather.com/mcp#get_forecast",          # Specific tool from server
-        "crewai-amp:financial-data",                         # CrewAI AOP marketplace
+        "crewai-amp:financial-data",                         # CrewAI AMP marketplace
         "crewai-amp:research-tools#pubmed_search"            # Specific AMP tool
     ]
 )
@@ -87,6 +87,7 @@ We currently support the following transport mechanisms:
 - **Streamable HTTPS**: for remote servers (flexible, potentially bi-directional communication over HTTPS, often utilizing SSE for server-to-client streams)
 
 ## Video Tutorial
+
 Watch this video tutorial for a comprehensive guide on MCP integration with CrewAI:
 
 <iframe
@@ -203,7 +204,7 @@ mcps=[
 ]
 ```
 
-#### CrewAI AOP Marketplace
+#### CrewAI AMP Marketplace
 
 ```python
 mcps=[
@@ -373,6 +374,7 @@ Each transport type supports specific configuration options:
 ### Common Parameters
 
 All transport types support:
+
 - **`tool_filter`**: Filter function to control which tools are available. Can be:
   - `None` (default): All tools are available
   - Static filter: Created with `create_static_tool_filter()` for allow/block lists
@@ -423,6 +425,7 @@ agent = Agent(
 ```
 
 All connection errors are handled gracefully:
+
 - **Connection failures**: Logged as warnings, agent continues with available tools
 - **Timeout errors**: Connections timeout after 30 seconds (configurable)
 - **Authentication errors**: Logged clearly for debugging
@@ -484,6 +487,7 @@ with MCPServerAdapter(server_params, connect_timeout=60) as mcp_tools:
     )
     # ... rest of your crew setup ...
 ```
+
 This general pattern shows how to integrate tools. For specific examples tailored to each transport, refer to the detailed guides below.
 
 ## Filtering Tools
@@ -570,6 +574,7 @@ When a crew class is decorated with `@CrewBase`, the adapter lifecycle is manage
 - If `mcp_server_params` is not defined, `get_mcp_tools()` simply returns an empty list, allowing the same code paths to run with or without MCP configured.
 
 This makes it safe to call `get_mcp_tools()` from multiple agent methods or selectively enable MCP per environment.
+
 </Tip>
 
 ### Connection Timeout Configuration
@@ -636,7 +641,8 @@ class CrewWithCustomTimeout:
     href="/en/mcp/dsl-integration"
     color="#3B82F6"
   >
-    **Recommended**: Use the simple `mcps=[]` field syntax for effortless MCP integration.
+    **Recommended**: Use the simple `mcps=[]` field syntax for effortless MCP
+    integration.
   </Card>
   <Card
     title="Stdio Transport"
@@ -644,15 +650,12 @@ class CrewWithCustomTimeout:
     href="/en/mcp/stdio"
     color="#10B981"
   >
-    Connect to local MCP servers via standard input/output. Ideal for scripts and local executables.
+    Connect to local MCP servers via standard input/output. Ideal for scripts
+    and local executables.
   </Card>
-  <Card
-    title="SSE Transport"
-    icon="wifi"
-    href="/en/mcp/sse"
-    color="#F59E0B"
-  >
-    Integrate with remote MCP servers using Server-Sent Events for real-time data streaming.
+  <Card title="SSE Transport" icon="wifi" href="/en/mcp/sse" color="#F59E0B">
+    Integrate with remote MCP servers using Server-Sent Events for real-time
+    data streaming.
   </Card>
   <Card
     title="Streamable HTTP Transport"
@@ -660,7 +663,8 @@ class CrewWithCustomTimeout:
     href="/en/mcp/streamable-http"
     color="#8B5CF6"
   >
-    Utilize flexible Streamable HTTP for robust communication with remote MCP servers.
+    Utilize flexible Streamable HTTP for robust communication with remote MCP
+    servers.
   </Card>
   <Card
     title="Connecting to Multiple Servers"
@@ -668,7 +672,8 @@ class CrewWithCustomTimeout:
     href="/en/mcp/multiple-servers"
     color="#EF4444"
   >
-    Aggregate tools from several MCP servers simultaneously using a single adapter.
+    Aggregate tools from several MCP servers simultaneously using a single
+    adapter.
   </Card>
   <Card
     title="Security Considerations"
@@ -676,27 +681,28 @@ class CrewWithCustomTimeout:
     href="/en/mcp/security"
     color="#DC2626"
   >
-    Review important security best practices for MCP integration to keep your agents safe.
+    Review important security best practices for MCP integration to keep your
+    agents safe.
   </Card>
 </CardGroup>
 
 Checkout this repository for full demos and examples of MCP integration with CrewAI! 👇
 
 <Card
-title="GitHub Repository"
-icon="github"
-href="https://github.com/tonykipkemboi/crewai-mcp-demo"
-target="_blank"
+  title="GitHub Repository"
+  icon="github"
+  href="https://github.com/tonykipkemboi/crewai-mcp-demo"
+  target="_blank"
 >
-CrewAI MCP Demo
+  CrewAI MCP Demo
 </Card>
 
 ## Staying Safe with MCP
-<Warning>
-Always ensure that you trust an MCP Server before using it.
-</Warning>
+
+<Warning>Always ensure that you trust an MCP Server before using it.</Warning>
 
 #### Security Warning: DNS Rebinding Attacks
+
 SSE transports can be vulnerable to DNS rebinding attacks if not properly secured.
 To prevent this:
 
@@ -709,6 +715,7 @@ Without these protections, attackers could use DNS rebinding to interact with lo
 For more details, see the [Anthropic's MCP Transport Security docs](https://modelcontextprotocol.io/docs/concepts/transports#security-considerations).
 
 ### Limitations
-*   **Supported Primitives**: Currently, `MCPServerAdapter` primarily supports adapting MCP `tools`.
-Other MCP primitives like `prompts` or `resources` are not directly integrated as CrewAI components through this adapter at this time.
-*   **Output Handling**: The adapter typically processes the primary text output from an MCP tool (e.g., `.content[0].text`). Complex or multi-modal outputs might require custom handling if not fitting this pattern.
+
+- **Supported Primitives**: Currently, `MCPServerAdapter` primarily supports adapting MCP `tools`.
+  Other MCP primitives like `prompts` or `resources` are not directly integrated as CrewAI components through this adapter at this time.
+- **Output Handling**: The adapter typically processes the primary text output from an MCP tool (e.g., `.content[0].text`). Complex or multi-modal outputs might require custom handling if not fitting this pattern.

docs/en/observability/tracing.mdx

@@ -1,6 +1,6 @@
 ---
 title: CrewAI Tracing
-description: Built-in tracing for CrewAI Crews and Flows with the CrewAI AOP platform
+description: Built-in tracing for CrewAI Crews and Flows with the CrewAI AMP platform
 icon: magnifying-glass-chart
 mode: "wide"
 ---
@@ -9,7 +9,7 @@ mode: "wide"
 
 CrewAI provides built-in tracing capabilities that allow you to monitor and debug your Crews and Flows in real-time. This guide demonstrates how to enable tracing for both **Crews** and **Flows** using CrewAI's integrated observability platform.
 
-> **What is CrewAI Tracing?** CrewAI's built-in tracing provides comprehensive observability for your AI agents, including agent decisions, task execution timelines, tool usage, and LLM calls - all accessible through the [CrewAI AOP platform](https://app.crewai.com).
+> **What is CrewAI Tracing?** CrewAI's built-in tracing provides comprehensive observability for your AI agents, including agent decisions, task execution timelines, tool usage, and LLM calls - all accessible through the [CrewAI AMP platform](https://app.crewai.com).
 
 ![CrewAI Tracing Interface](/images/crewai-tracing.png)
 
@@ -17,7 +17,7 @@ CrewAI provides built-in tracing capabilities that allow you to monitor and debu
 
 Before you can use CrewAI tracing, you need:
 
-1. **CrewAI AOP Account**: Sign up for a free account at [app.crewai.com](https://app.crewai.com)
+1. **CrewAI AMP Account**: Sign up for a free account at [app.crewai.com](https://app.crewai.com)
 2. **CLI Authentication**: Use the CrewAI CLI to authenticate your local environment
 
 ```bash
@@ -26,9 +26,9 @@ crewai login
 
 ## Setup Instructions
 
-### Step 1: Create Your CrewAI AOP Account
+### Step 1: Create Your CrewAI AMP Account
 
-Visit [app.crewai.com](https://app.crewai.com) and create your free account. This will give you access to the CrewAI AOP platform where you can view traces, metrics, and manage your crews.
+Visit [app.crewai.com](https://app.crewai.com) and create your free account. This will give you access to the CrewAI AMP platform where you can view traces, metrics, and manage your crews.
 
 ### Step 2: Install CrewAI CLI and Authenticate
 
@@ -38,16 +38,17 @@ If you haven't already, install CrewAI with the CLI tools:
 uv add crewai[tools]
 ```
 
-Then authenticate your CLI with your CrewAI AOP account:
+Then authenticate your CLI with your CrewAI AMP account:
 
 ```bash
 crewai login
 ```
 
 This command will:
+
 1. Open your browser to the authentication page
 2. Prompt you to enter a device code
-3. Authenticate your local environment with your CrewAI AOP account
+3. Authenticate your local environment with your CrewAI AMP account
 4. Enable tracing capabilities for your local development
 
 ### Step 3: Enable Tracing in Your Crew
@@ -147,13 +148,12 @@ flow = ExampleFlow(tracing=True)
 result = flow.kickoff()
 ```
 
-### Step 5: View Traces in the CrewAI AOP Dashboard
+### Step 5: View Traces in the CrewAI AMP Dashboard
 
-After running the crew or flow, you can view the traces generated by your CrewAI application in the CrewAI AOP dashboard. You should see detailed steps of the agent interactions, tool usages, and LLM calls.
+After running the crew or flow, you can view the traces generated by your CrewAI application in the CrewAI AMP dashboard. You should see detailed steps of the agent interactions, tool usages, and LLM calls.
 Just click on the link below to view the traces or head over to the traces tab in the dashboard [here](https://app.crewai.com/crewai_plus/trace_batches)
 ![CrewAI Tracing Interface](/images/view-traces.png)
 
-
 ### Alternative: Environment Variable Configuration
 
 You can also enable tracing globally by setting an environment variable:
@@ -172,7 +172,7 @@ When this environment variable is set, all Crews and Flows will automatically ha
 
 ## Viewing Your Traces
 
-### Access the CrewAI AOP Dashboard
+### Access the CrewAI AMP Dashboard
 
 1. Visit [app.crewai.com](https://app.crewai.com) and log in to your account
 2. Navigate to your project dashboard
@@ -190,6 +190,7 @@ CrewAI tracing provides comprehensive visibility into:
 - **Error Tracking**: Detailed error information and stack traces
 
 ### Trace Features
+
 - **Execution Timeline**: Click through different stages of execution
 - **Detailed Logs**: Access comprehensive logs for debugging
 - **Performance Analytics**: Analyze execution patterns and optimize performance

docs/en/quickstart.mdx

@@ -58,6 +58,7 @@ Follow the steps below to get Crewing! 🚣‍♂️
         your ability to turn complex data into clear and concise reports, making
         it easy for others to understand and act on the information you provide.
     ```
+
   </Step>
   <Step title="Modify your `tasks.yaml` file">
     ```yaml tasks.yaml
@@ -81,6 +82,7 @@ Follow the steps below to get Crewing! 🚣‍♂️
       agent: reporting_analyst
       output_file: report.md
     ```
+
   </Step>
   <Step title="Modify your `crew.py` file">
     ```python crew.py
@@ -136,6 +138,7 @@ Follow the steps below to get Crewing! 🚣‍♂️
           verbose=True,
         )
     ```
+
   </Step>
   <Step title="[Optional] Add before and after crew functions">
     ```python crew.py
@@ -160,6 +163,7 @@ Follow the steps below to get Crewing! 🚣‍♂️
 
       # ... remaining code
     ```
+
   </Step>
   <Step title="Feel free to pass custom inputs to your crew">
   For example, you can pass the `topic` input to your crew to customize the research and reporting.
@@ -178,6 +182,7 @@ Follow the steps below to get Crewing! 🚣‍♂️
       }
       LatestAiDevelopmentCrew().crew().kickoff(inputs=inputs)
     ```
+
   </Step>
   <Step title="Set your environment variables">
   Before running your crew, make sure you have the following keys set as environment variables in your `.env` file:
@@ -209,24 +214,24 @@ Follow the steps below to get Crewing! 🚣‍♂️
   </Step>
 
   <Step title="Enterprise Alternative: Create in Crew Studio">
-  For CrewAI AOP users, you can create the same crew without writing code:
+  For CrewAI AMP users, you can create the same crew without writing code:
 
-  1. Log in to your CrewAI AOP account (create a free account at [app.crewai.com](https://app.crewai.com))
-  2. Open Crew Studio
-  3. Type what is the automation you're trying to build
-  4. Create your tasks visually and connect them in sequence
-  5. Configure your inputs and click "Download Code" or "Deploy"
+1. Log in to your CrewAI AMP account (create a free account at [app.crewai.com](https://app.crewai.com))
+2. Open Crew Studio
+3. Type what is the automation you're trying to build
+4. Create your tasks visually and connect them in sequence
+5. Configure your inputs and click "Download Code" or "Deploy"
 
-  ![Crew Studio Quickstart](/images/enterprise/crew-studio-interface.png)
+![Crew Studio Quickstart](/images/enterprise/crew-studio-interface.png)
 
-  <Card title="Try CrewAI AOP" icon="rocket" href="https://app.crewai.com">
-    Start your free account at CrewAI AOP
+  <Card title="Try CrewAI AMP" icon="rocket" href="https://app.crewai.com">
+    Start your free account at CrewAI AMP
   </Card>
   </Step>
   <Step title="View your final report">
   You should see the output in the console and the `report.md` file should be created in the root of your project with the final report.
 
-  Here's an example of what the report should look like:
+Here's an example of what the report should look like:
 
   <CodeGroup>
     ```markdown output/report.md
@@ -289,6 +294,7 @@ Follow the steps below to get Crewing! 🚣‍♂️
     ## 8. Conclusion
     The emergence of AI agents is undeniably reshaping the workplace landscape in 5. With their ability to automate tasks, enhance efficiency, and improve decision-making, AI agents are critical in driving operational success. Organizations must embrace and adapt to AI developments to thrive in an increasingly digital business environment.
     ```
+
   </CodeGroup>
   </Step>
 </Steps>
@@ -297,6 +303,7 @@ Follow the steps below to get Crewing! 🚣‍♂️
 Congratulations!
 
 You have successfully set up your crew project and are ready to start building your own agentic workflows!
+
 </Check>
 
 ### Note on Consistency in Naming
@@ -308,41 +315,45 @@ This naming consistency allows CrewAI to automatically link your configurations
 #### Example References
 
 <Tip>
-  Note how we use the same name for the agent in the `agents.yaml` (`email_summarizer`) file as the method name in the `crew.py` (`email_summarizer`) file.
+  Note how we use the same name for the agent in the `agents.yaml`
+  (`email_summarizer`) file as the method name in the `crew.py`
+  (`email_summarizer`) file.
 </Tip>
 
 ```yaml agents.yaml
 email_summarizer:
-    role: >
-      Email Summarizer
-    goal: >
-      Summarize emails into a concise and clear summary
-    backstory: >
-      You will create a 5 bullet point summary of the report
-    llm: provider/model-id  # Add your choice of model here
+  role: >
+    Email Summarizer
+  goal: >
+    Summarize emails into a concise and clear summary
+  backstory: >
+    You will create a 5 bullet point summary of the report
+  llm: provider/model-id # Add your choice of model here
 ```
 
 <Tip>
-  Note how we use the same name for the task in the `tasks.yaml` (`email_summarizer_task`) file as the method name in the `crew.py` (`email_summarizer_task`) file.
+  Note how we use the same name for the task in the `tasks.yaml`
+  (`email_summarizer_task`) file as the method name in the `crew.py`
+  (`email_summarizer_task`) file.
 </Tip>
 
 ```yaml tasks.yaml
 email_summarizer_task:
-    description: >
-      Summarize the email into a 5 bullet point summary
-    expected_output: >
-      A 5 bullet point summary of the email
-    agent: email_summarizer
-    context:
-      - reporting_task
-      - research_task
+  description: >
+    Summarize the email into a 5 bullet point summary
+  expected_output: >
+    A 5 bullet point summary of the email
+  agent: email_summarizer
+  context:
+    - reporting_task
+    - research_task
 ```
 
 ## Deploying Your Crew
 
-The easiest way to deploy your crew to production is through [CrewAI AOP](http://app.crewai.com).
+The easiest way to deploy your crew to production is through [CrewAI AMP](http://app.crewai.com).
 
-Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI AOP](http://app.crewai.com) using the CLI.
+Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI AMP](http://app.crewai.com) using the CLI.
 
 <iframe
   className="w-full aspect-video rounded-xl"
@@ -354,18 +365,16 @@ Watch this video tutorial for a step-by-step demonstration of deploying your cre
 ></iframe>
 
 <CardGroup cols={2}>
-  <Card
-    title="Deploy on Enterprise"
-    icon="rocket"
-    href="http://app.crewai.com"
-  >
-    Get started with CrewAI AOP and deploy your crew in a production environment with just a few clicks.
+  <Card title="Deploy on Enterprise" icon="rocket" href="http://app.crewai.com">
+    Get started with CrewAI AMP and deploy your crew in a production environment
+    with just a few clicks.
   </Card>
   <Card
     title="Join the Community"
     icon="comments"
     href="https://community.crewai.com"
   >
-    Join our open source community to discuss ideas, share your projects, and connect with other CrewAI developers.
+    Join our open source community to discuss ideas, share your projects, and
+    connect with other CrewAI developers.
   </Card>
 </CardGroup>

docs/enterprise-api.base.yaml

@@ -1,12 +1,12 @@
 openapi: 3.0.3
 info:
-  title: CrewAI AOP API
+  title: CrewAI AMP API
   description: |
-    REST API for interacting with your deployed CrewAI crews on CrewAI AOP.
+    REST API for interacting with your deployed CrewAI crews on CrewAI AMP.
 
     ## Getting Started
 
-    1. **Find your crew URL**: Get your unique crew URL from the CrewAI AOP dashboard
+    1. **Find your crew URL**: Get your unique crew URL from the CrewAI AMP dashboard
     2. **Copy examples**: Use the code examples from each endpoint page as templates
     3. **Replace placeholders**: Update URLs and tokens with your actual values
     4. **Test with your tools**: Use cURL, Postman, or your preferred API client
@@ -18,7 +18,7 @@ info:
     - **Bearer Token**: Organization-level token for full crew operations
     - **User Bearer Token**: User-scoped token for individual access with limited permissions
 
-    You can find your bearer tokens in the Status tab of your crew's detail page in the CrewAI AOP dashboard.
+    You can find your bearer tokens in the Status tab of your crew's detail page in the CrewAI AMP dashboard.
 
     ## Reference Documentation
 
@@ -43,7 +43,7 @@ info:
     url: https://crewai.com
 servers:
   - url: https://your-actual-crew-name.crewai.com
-    description: Replace with your actual deployed crew URL from the CrewAI AOP dashboard
+    description: Replace with your actual deployed crew URL from the CrewAI AMP dashboard
   - url: https://my-travel-crew.crewai.com
     description: Example travel planning crew (replace with your URL)
   - url: https://content-creation-crew.crewai.com
@@ -420,7 +420,7 @@ components:
       description: |
         **📋 Reference Documentation** - *The tokens shown in examples are placeholders for reference only.*
 
-        Use your actual Bearer Token or User Bearer Token from the CrewAI AOP dashboard for real API calls.
+        Use your actual Bearer Token or User Bearer Token from the CrewAI AMP dashboard for real API calls.
 
         **Bearer Token**: Organization-level access for full crew operations
         **User Bearer Token**: User-scoped access with limited permissions

docs/enterprise-api.en.yaml

@@ -1,12 +1,12 @@
 openapi: 3.0.3
 info:
-  title: CrewAI AOP API
+  title: CrewAI AMP API
   description: |
-    REST API for interacting with your deployed CrewAI crews on CrewAI AOP.
+    REST API for interacting with your deployed CrewAI crews on CrewAI AMP.
 
     ## Getting Started
 
-    1. **Find your crew URL**: Get your unique crew URL from the CrewAI AOP dashboard
+    1. **Find your crew URL**: Get your unique crew URL from the CrewAI AMP dashboard
     2. **Copy examples**: Use the code examples from each endpoint page as templates
     3. **Replace placeholders**: Update URLs and tokens with your actual values
     4. **Test with your tools**: Use cURL, Postman, or your preferred API client
@@ -18,7 +18,7 @@ info:
     - **Bearer Token**: Organization-level token for full crew operations
     - **User Bearer Token**: User-scoped token for individual access with limited permissions
 
-    You can find your bearer tokens in the Status tab of your crew's detail page in the CrewAI AOP dashboard.
+    You can find your bearer tokens in the Status tab of your crew's detail page in the CrewAI AMP dashboard.
 
     ## Reference Documentation
 
@@ -43,7 +43,7 @@ info:
     url: https://crewai.com
 servers:
   - url: https://your-actual-crew-name.crewai.com
-    description: Replace with your actual deployed crew URL from the CrewAI AOP dashboard
+    description: Replace with your actual deployed crew URL from the CrewAI AMP dashboard
   - url: https://my-travel-crew.crewai.com
     description: Example travel planning crew (replace with your URL)
   - url: https://content-creation-crew.crewai.com
@@ -420,7 +420,7 @@ components:
       description: |
         **📋 Reference Documentation** - *The tokens shown in examples are placeholders for reference only.*
 
-        Use your actual Bearer Token or User Bearer Token from the CrewAI AOP dashboard for real API calls.
+        Use your actual Bearer Token or User Bearer Token from the CrewAI AMP dashboard for real API calls.
 
         **Bearer Token**: Organization-level access for full crew operations
         **User Bearer Token**: User-scoped access with limited permissions

docs/enterprise-api.pt-BR.yaml

@@ -1,12 +1,12 @@
 openapi: 3.0.3
 info:
-  title: CrewAI AOP API
+  title: CrewAI AMP API
   description: |
-    REST API para interagir com suas crews implantadas no CrewAI AOP.
+    REST API para interagir com suas crews implantadas no CrewAI AMP.
 
     ## Introdução
 
-    1. **Encontre a URL da sua crew**: Obtenha sua URL única no painel do CrewAI AOP
+    1. **Encontre a URL da sua crew**: Obtenha sua URL única no painel do CrewAI AMP
     2. **Copie os exemplos**: Use os exemplos de cada endpoint como modelo
     3. **Substitua os placeholders**: Atualize URLs e tokens com seus valores reais
     4. **Teste com suas ferramentas**: Use cURL, Postman ou seu cliente preferido
@@ -18,7 +18,7 @@ info:
     - **Bearer Token**: Token em nível de organização para operações completas
     - **User Bearer Token**: Token com escopo de usuário com permissões limitadas
 
-    Você encontra os tokens na aba Status da sua crew no painel do CrewAI AOP.
+    Você encontra os tokens na aba Status da sua crew no painel do CrewAI AMP.
 
     ## Documentação de Referência
 
@@ -43,7 +43,7 @@ info:
     url: https://crewai.com
 servers:
   - url: https://your-actual-crew-name.crewai.com
-    description: Substitua pela URL real da sua crew no painel do CrewAI AOP
+    description: Substitua pela URL real da sua crew no painel do CrewAI AMP
 security:
   - BearerAuth: []
 paths:
@@ -291,7 +291,7 @@ components:
       scheme: bearer
       description: |
         **📋 Referência** - *Os tokens mostrados são apenas exemplos.*
-        Use seus tokens reais do painel do CrewAI AOP.
+        Use seus tokens reais do painel do CrewAI AMP.
 
   schemas:
     ExecutionRunning:

docs/ko/api-reference/introduction.mdx

@@ -1,6 +1,6 @@
 ---
 title: "소개"
-description: "CrewAI AOP REST API에 대한 완벽한 참고 자료"
+description: "CrewAI AMP REST API에 대한 완벽한 참고 자료"
 icon: "code"
 mode: "wide"
 ---
@@ -13,7 +13,7 @@ CrewAI 엔터프라이즈 API 참고 자료에 오신 것을 환영합니다.
 
 <Steps>
   <Step title="API 자격 증명 받기">
-    CrewAI AOP 대시보드에서 자신의 crew 상세 페이지로 이동하여 Status 탭에서 Bearer Token을 복사하세요.
+    CrewAI AMP 대시보드에서 자신의 crew 상세 페이지로 이동하여 Status 탭에서 Bearer Token을 복사하세요.
   </Step>
 
 <Step title="필수 입력값 확인하기">
@@ -47,7 +47,7 @@ curl -H "Authorization: Bearer YOUR_CREW_TOKEN" \
 | **User Bearer Token** | 사용자 범위 접근 | 제한된 권한, 사용자별 작업에 적합     |
 
 <Tip>
-  두 토큰 유형 모두 CrewAI AOP 대시보드의 crew 상세 페이지 Status 탭에서 확인할
+  두 토큰 유형 모두 CrewAI AMP 대시보드의 crew 상세 페이지 Status 탭에서 확인할
   수 있습니다.
 </Tip>
 
@@ -84,7 +84,7 @@ API는 표준 HTTP 상태 코드를 사용합니다:
 ## 인터랙티브 테스트
 
 <Info>
-  **왜 "전송" 버튼이 없나요?** 각 CrewAI AOP 사용자는 고유한 crew URL을
+  **왜 "전송" 버튼이 없나요?** 각 CrewAI AMP 사용자는 고유한 crew URL을
   가지므로, 혼동을 피하기 위해 인터랙티브 플레이그라운드 대신 **참조 모드**를
   사용합니다. 이를 통해 비작동 전송 버튼 없이 요청이 어떻게 생겼는지 정확히
   보여줍니다.

docs/ko/concepts/cli.mdx

@@ -5,7 +5,12 @@ icon: terminal
 mode: "wide"
 ---
 
-<Warning>릴리즈 0.140.0부터 CrewAI AOP는 로그인 제공자 마이그레이션 프로세스를 시작했습니다. 이에 따라 CLI를 통한 인증 흐름이 업데이트되었습니다. Google을 통해 로그인하거나 2025년 7월 3일 이후에 계정을 생성한 사용자는 이전 버전의 `crewai` 라이브러리로는 로그인할 수 없습니다.</Warning>
+<Warning>
+  릴리즈 0.140.0부터 CrewAI AOP는 로그인 제공자 마이그레이션 프로세스를
+  시작했습니다. 이에 따라 CLI를 통한 인증 흐름이 업데이트되었습니다. Google을
+  통해 로그인하거나 2025년 7월 3일 이후에 계정을 생성한 사용자는 이전 버전의
+  `crewai` 라이브러리로는 로그인할 수 없습니다.
+</Warning>
 
 ## 개요
 
@@ -41,6 +46,7 @@ crewai create [OPTIONS] TYPE NAME
 - `NAME`: crew 또는 flow의 이름
 
 예시:
+
 ```shell Terminal
 crewai create crew my_new_crew
 crewai create flow my_new_flow
@@ -57,6 +63,7 @@ crewai version [OPTIONS]
 - `--tools`: (선택 사항) 설치된 CrewAI tools의 버전을 표시합니다.
 
 예시:
+
 ```shell Terminal
 crewai version
 crewai version --tools
@@ -74,6 +81,7 @@ crewai train [OPTIONS]
 - `-f, --filename TEXT`: 훈련에 사용할 커스텀 파일의 경로 (기본값: "trained_agents_data.pkl")
 
 예시:
+
 ```shell Terminal
 crewai train -n 10 -f my_training_data.pkl
 ```
@@ -89,6 +97,7 @@ crewai replay [OPTIONS]
 - `-t, --task_id TEXT`: 이 task ID에서부터 crew를 다시 재생하며, 이후의 모든 task를 포함합니다.
 
 예시:
+
 ```shell Terminal
 crewai replay -t task_123456
 ```
@@ -118,6 +127,7 @@ crewai reset-memories [OPTIONS]
 - `-a, --all`: 모든 메모리 초기화
 
 예시:
+
 ```shell Terminal
 crewai reset-memories --long --short
 crewai reset-memories --all
@@ -135,6 +145,7 @@ crewai test [OPTIONS]
 - `-m, --model TEXT`: Crew에서 테스트를 실행할 LLM 모델 (기본값: "gpt-4o-mini")
 
 예시:
+
 ```shell Terminal
 crewai test -n 5 -m gpt-3.5-turbo
 ```
@@ -148,12 +159,14 @@ crewai run
 ```
 
 <Note>
-버전 0.103.0부터 `crewai run` 명령은 표준 crew와 flow 모두를 실행하는 데 사용할 수 있습니다. flow의 경우 pyproject.toml에서 유형을 자동으로 감지하여 적절한 명령을 실행합니다. 이제 crew와 flow 모두를 실행하는 권장 방법입니다.
+  버전 0.103.0부터 `crewai run` 명령은 표준 crew와 flow 모두를 실행하는 데
+  사용할 수 있습니다. flow의 경우 pyproject.toml에서 유형을 자동으로 감지하여
+  적절한 명령을 실행합니다. 이제 crew와 flow 모두를 실행하는 권장 방법입니다.
 </Note>
 
 <Note>
-이 명령들은 CrewAI 프로젝트가 설정된 디렉터리에서 실행해야 합니다.
-일부 명령은 프로젝트 구조 내에서 추가 구성 또는 설정이 필요할 수 있습니다.
+  이 명령들은 CrewAI 프로젝트가 설정된 디렉터리에서 실행해야 합니다. 일부 명령은
+  프로젝트 구조 내에서 추가 구성 또는 설정이 필요할 수 있습니다.
 </Note>
 
 ### 9. Chat
@@ -165,6 +178,7 @@ crewai run
 ```shell Terminal
 crewai chat
 ```
+
 <Note>
 이 명령어들은 CrewAI 프로젝트의 루트 디렉터리에서 실행해야 합니다.
 </Note>
@@ -182,28 +196,30 @@ def crew(self) -> Crew:
         chat_llm="gpt-4o",  # LLM for chat orchestration
     )
 ```
+
 </Note>
 
 ### 10. 배포
 
-crew 또는 flow를 [CrewAI AOP](https://app.crewai.com)에 배포하세요.
+crew 또는 flow를 [CrewAI AMP](https://app.crewai.com)에 배포하세요.
 
 - **인증**: CrewAI AOP에 배포하려면 인증이 필요합니다.
-    아래 명령어로 로그인하거나 계정을 생성할 수 있습니다:
-    ```shell Terminal
-    crewai login
-    ```
+  아래 명령어로 로그인하거나 계정을 생성할 수 있습니다:
+
+  ```shell Terminal
+  crewai login
+  ```
 
 - **배포 생성**: 인증이 완료되면, 로컬 프로젝트의 루트에서 crew 또는 flow에 대한 배포를 생성할 수 있습니다.
-    ```shell Terminal
-    crewai deploy create
-    ```
-    - 로컬 프로젝트 구성을 읽어옵니다.
-    - 로컬에서 확인된 환경 변수(`OPENAI_API_KEY`, `SERPER_API_KEY` 등)를 확인하도록 안내합니다. 이 변수들은 Enterprise 플랫폼에 배포할 때 안전하게 저장됩니다. 실행 전에 중요한 키가 로컬(예: `.env` 파일)에 올바르게 구성되어 있는지 확인하세요.
+  ```shell Terminal
+  crewai deploy create
+  ```
+  - 로컬 프로젝트 구성을 읽어옵니다.
+  - 로컬에서 확인된 환경 변수(`OPENAI_API_KEY`, `SERPER_API_KEY` 등)를 확인하도록 안내합니다. 이 변수들은 Enterprise 플랫폼에 배포할 때 안전하게 저장됩니다. 실행 전에 중요한 키가 로컬(예: `.env` 파일)에 올바르게 구성되어 있는지 확인하세요.
 
 ### 11. 조직 관리
 
-CrewAI AOP 조직을 관리합니다.
+CrewAI AMP 조직을 관리합니다.
 
 ```shell Terminal
 crewai org [COMMAND] [OPTIONS]
@@ -212,65 +228,79 @@ crewai org [COMMAND] [OPTIONS]
 #### 명령어:
 
 - `list`: 사용자가 속한 모든 조직을 나열합니다.
+
 ```shell Terminal
 crewai org list
 ```
 
 - `current`: 현재 활성화된 조직을 표시합니다.
+
 ```shell Terminal
 crewai org current
 ```
 
 - `switch`: 특정 조직으로 전환합니다.
+
 ```shell Terminal
 crewai org switch <organization_id>
 ```
 
 <Note>
-이러한 조직 관리 명령어를 사용하려면 CrewAI AOP에 인증되어 있어야 합니다.
+  이러한 조직 관리 명령어를 사용하려면 CrewAI AOP에 인증되어 있어야 합니다.
 </Note>
 
 - **배포 생성** (계속):
-    - 배포를 해당 원격 GitHub 저장소에 연결합니다 (일반적으로 자동으로 감지됩니다).
+
+  - 배포를 해당 원격 GitHub 저장소에 연결합니다 (일반적으로 자동으로 감지됩니다).
 
 - **Crew 배포**: 인증이 완료되면 crew 또는 flow를 CrewAI AOP에 배포할 수 있습니다.
-    ```shell Terminal
-    crewai deploy push
-    ```
-    - CrewAI AOP 플랫폼에서 배포 프로세스를 시작합니다.
-    - 성공적으로 시작되면, Deployment created successfully! 메시지와 함께 Deployment Name 및 고유한 Deployment ID(UUID)가 출력됩니다.
+
+  ```shell Terminal
+  crewai deploy push
+  ```
+
+  - CrewAI AMP 플랫폼에서 배포 프로세스를 시작합니다.
+  - 성공적으로 시작되면, Deployment created successfully! 메시지와 함께 Deployment Name 및 고유한 Deployment ID(UUID)가 출력됩니다.
 
 - **배포 상태**: 배포 상태를 확인하려면 다음을 사용합니다:
-    ```shell Terminal
-    crewai deploy status
-    ```
-    이 명령은 가장 최근의 배포 시도에 대한 최신 배포 상태(예: `Building Images for Crew`, `Deploy Enqueued`, `Online`)를 가져옵니다.
+
+  ```shell Terminal
+  crewai deploy status
+  ```
+
+  이 명령은 가장 최근의 배포 시도에 대한 최신 배포 상태(예: `Building Images for Crew`, `Deploy Enqueued`, `Online`)를 가져옵니다.
 
 - **배포 로그**: 배포 로그를 확인하려면 다음을 사용합니다:
-    ```shell Terminal
-    crewai deploy logs
-    ```
-    이 명령은 배포 로그를 터미널로 스트리밍합니다.
+
+  ```shell Terminal
+  crewai deploy logs
+  ```
+
+  이 명령은 배포 로그를 터미널로 스트리밍합니다.
 
 - **배포 목록**: 모든 배포를 나열하려면 다음을 사용합니다:
-    ```shell Terminal
-    crewai deploy list
-    ```
-    이 명령은 모든 배포를 나열합니다.
+
+  ```shell Terminal
+  crewai deploy list
+  ```
+
+  이 명령은 모든 배포를 나열합니다.
 
 - **배포 삭제**: 배포를 삭제하려면 다음을 사용합니다:
-    ```shell Terminal
-    crewai deploy remove
-    ```
-    이 명령은 CrewAI AOP 플랫폼에서 배포를 삭제합니다.
+
+  ```shell Terminal
+  crewai deploy remove
+  ```
+
+  이 명령은 CrewAI AMP 플랫폼에서 배포를 삭제합니다.
 
 - **도움말 명령어**: CLI에 대한 도움말을 보려면 다음을 사용합니다:
-    ```shell Terminal
-    crewai deploy --help
-    ```
-    이 명령은 CrewAI Deploy CLI에 대한 도움말 메시지를 표시합니다.
+  ```shell Terminal
+  crewai deploy --help
+  ```
+  이 명령은 CrewAI Deploy CLI에 대한 도움말 메시지를 표시합니다.
 
-CLI를 사용하여 [CrewAI AOP](http://app.crewai.com)에 crew를 배포하는 단계별 시연은 아래 비디오 튜토리얼을 참조하십시오.
+CLI를 사용하여 [CrewAI AMP](http://app.crewai.com)에 crew를 배포하는 단계별 시연은 아래 비디오 튜토리얼을 참조하십시오.
 
 <iframe
   className="w-full aspect-video rounded-xl"
@@ -283,7 +313,7 @@ CLI를 사용하여 [CrewAI AOP](http://app.crewai.com)에 crew를 배포하는
 
 ### 11. API 키
 
-```crewai create crew``` 명령어를 실행하면, CLI에서 선택할 수 있는 LLM 제공업체 목록이 표시되고, 그 다음으로 선택한 제공업체에 대한 모델 선택이 이어집니다.
+`crewai create crew` 명령어를 실행하면, CLI에서 선택할 수 있는 LLM 제공업체 목록이 표시되고, 그 다음으로 선택한 제공업체에 대한 모델 선택이 이어집니다.
 
 LLM 제공업체와 모델을 선택하면, API 키를 입력하라는 메시지가 표시됩니다.
 
@@ -291,11 +321,11 @@ LLM 제공업체와 모델을 선택하면, API 키를 입력하라는 메시지
 
 다음은 CLI에서 제안하는 가장 인기 있는 LLM 공급자 목록입니다:
 
-* OpenAI
-* Groq
-* Anthropic
-* Google Gemini
-* SambaNova
+- OpenAI
+- Groq
+- Anthropic
+- Google Gemini
+- SambaNova
 
 공급자를 선택하면, CLI가 해당 공급자에서 사용 가능한 모델을 보여주고 API 키 입력을 요청합니다.
 
@@ -307,7 +337,7 @@ LLM 제공업체와 모델을 선택하면, API 키를 입력하라는 메시지
 
 각 공급자의 Key 이름은 다음 링크에서 확인할 수 있습니다:
 
-* [LiteLLM 공급자](https://docs.litellm.ai/docs/providers)
+- [LiteLLM 공급자](https://docs.litellm.ai/docs/providers)
 
 ### 12. 구성 관리
 
@@ -320,23 +350,26 @@ crewai config [COMMAND] [OPTIONS]
 #### 명령어:
 
 - `list`: 모든 CLI 구성 매개변수 표시
+
 ```shell Terminal
 crewai config list
 ```
 
 - `set`: CLI 구성 매개변수 설정
+
 ```shell Terminal
 crewai config set <key> <value>
 ```
 
 - `reset`: 모든 CLI 구성 매개변수를 기본값으로 초기화
+
 ```shell Terminal
 crewai config reset
 ```
 
 #### 사용 가능한 구성 파라미터
 
-- `enterprise_base_url`: CrewAI AOP 인스턴스의 기본 URL
+- `enterprise_base_url`: CrewAI AMP 인스턴스의 기본 URL
 - `oauth2_provider`: 인증에 사용되는 OAuth2 공급자 (예: workos, okta, auth0)
 - `oauth2_audience`: OAuth2 audience 값으로, 일반적으로 대상 API 또는 리소스를 식별하는 데 사용됨
 - `oauth2_client_id`: 인증 요청 시 사용되는 공급자가 발급한 OAuth2 클라이언트 ID
@@ -345,42 +378,49 @@ crewai config reset
 #### 예시
 
 현재 설정 표시:
+
 ```shell Terminal
 crewai config list
 ```
 
 예시 출력:
 
-| 설정                 | 값                      | 설명                                                                 |
-| :------------------- | :---------------------- | :------------------------------------------------------------------- |
-| enterprise_base_url  | https://app.crewai.com | CrewAI AOP 인스턴스의 기본 URL                                |
-| org_name             | Not set                 | 현재 활성화된 조직의 이름                                            |
-| org_uuid             | Not set                 | 현재 활성화된 조직의 UUID                                            |
-| oauth2_provider      | workos                  | 인증에 사용되는 OAuth2 제공자 (예: workos, okta, auth0)              |
-| oauth2_audience      | client_01YYY            | 일반적으로 대상 API/리소스를 식별하는 데 사용되는 OAuth2 audience 값 |
-| oauth2_client_id     | client_01XXX            | 제공자로부터 발급된 OAuth2 client ID (인증 요청 시 사용)             |
-| oauth2_domain        | login.crewai.com        | OAuth2 제공자의 도메인 (예: your-org.auth0.com)                      |
+| 설정                | 값                     | 설명                                                                 |
+| :------------------ | :--------------------- | :------------------------------------------------------------------- |
+| enterprise_base_url | https://app.crewai.com | CrewAI AMP 인스턴스의 기본 URL                                       |
+| org_name            | Not set                | 현재 활성화된 조직의 이름                                            |
+| org_uuid            | Not set                | 현재 활성화된 조직의 UUID                                            |
+| oauth2_provider     | workos                 | 인증에 사용되는 OAuth2 제공자 (예: workos, okta, auth0)              |
+| oauth2_audience     | client_01YYY           | 일반적으로 대상 API/리소스를 식별하는 데 사용되는 OAuth2 audience 값 |
+| oauth2_client_id    | client_01XXX           | 제공자로부터 발급된 OAuth2 client ID (인증 요청 시 사용)             |
+| oauth2_domain       | login.crewai.com       | OAuth2 제공자의 도메인 (예: your-org.auth0.com)                      |
 
 엔터프라이즈 기본 URL 설정:
+
 ```shell Terminal
 crewai config set enterprise_base_url https://my-enterprise.crewai.com
 ```
 
 OAuth2 제공자 설정:
+
 ```shell Terminal
 crewai config set oauth2_provider auth0
 ```
 
 OAuth2 도메인 설정:
+
 ```shell Terminal
 crewai config set oauth2_domain my-company.auth0.com
 ```
 
 모든 설정을 기본값으로 재설정:
+
 ```shell Terminal
 crewai config reset
 ```
 
 <Note>
-설정 값은 `~/.config/crewai/settings.json`에 저장됩니다. 조직 이름과 UUID와 같은 일부 설정 값은 읽기 전용이며 인증 및 조직 명령을 통해 관리됩니다. 도구 저장소 관련 설정은 숨겨져 있으며 사용자가 직접 설정할 수 없습니다.
+  설정 값은 `~/.config/crewai/settings.json`에 저장됩니다. 조직 이름과 UUID와
+  같은 일부 설정 값은 읽기 전용이며 인증 및 조직 명령을 통해 관리됩니다. 도구
+  저장소 관련 설정은 숨겨져 있으며 사용자가 직접 설정할 수 없습니다.
 </Note>

docs/ko/concepts/flows.mdx

@@ -565,6 +565,55 @@ Fourth method running
 
 이 Flow를 실행하면, `start_method`에서 생성된 랜덤 불리언 값에 따라 출력값이 달라집니다.
 
+### Human in the Loop (인간 피드백)
+
+`@human_feedback` 데코레이터는 인간의 피드백을 수집하기 위해 플로우 실행을 일시 중지하는 human-in-the-loop 워크플로우를 가능하게 합니다. 이는 승인 게이트, 품질 검토, 인간의 판단이 필요한 결정 지점에 유용합니다.
+
+```python Code
+from crewai.flow.flow import Flow, start, listen
+from crewai.flow.human_feedback import human_feedback, HumanFeedbackResult
+
+class ReviewFlow(Flow):
+    @start()
+    @human_feedback(
+        message="이 콘텐츠를 승인하시겠습니까?",
+        emit=["approved", "rejected", "needs_revision"],
+        llm="gpt-4o-mini",
+        default_outcome="needs_revision",
+    )
+    def generate_content(self):
+        return "검토할 콘텐츠..."
+
+    @listen("approved")
+    def on_approval(self, result: HumanFeedbackResult):
+        print(f"승인됨! 피드백: {result.feedback}")
+
+    @listen("rejected")
+    def on_rejection(self, result: HumanFeedbackResult):
+        print(f"거부됨. 이유: {result.feedback}")
+```
+
+`emit`이 지정되면, 인간의 자유 형식 피드백이 LLM에 의해 해석되어 지정된 outcome 중 하나로 매핑되고, 해당 `@listen` 데코레이터를 트리거합니다.
+
+라우팅 없이 단순히 피드백만 수집할 수도 있습니다:
+
+```python Code
+@start()
+@human_feedback(message="이 출력에 대한 코멘트가 있으신가요?")
+def my_method(self):
+    return "검토할 출력"
+
+@listen(my_method)
+def next_step(self, result: HumanFeedbackResult):
+    # result.feedback로 피드백에 접근
+    # result.output으로 원래 출력에 접근
+    pass
+```
+
+플로우 실행 중 수집된 모든 피드백은 `self.last_human_feedback` (가장 최근) 또는 `self.human_feedback_history` (리스트 형태의 모든 피드백)를 통해 접근할 수 있습니다.
+
+플로우에서의 인간 피드백에 대한 완전한 가이드는 비동기/논블로킹 피드백과 커스텀 프로바이더(Slack, 웹훅 등)를 포함하여 [Flow에서 인간 피드백](/ko/learn/human-feedback-in-flows)을 참조하세요.
+
 ## 플로우에 에이전트 추가하기
 
 에이전트는 플로우에 원활하게 통합할 수 있으며, 단순하고 집중된 작업 실행이 필요할 때 전체 Crew의 경량 대안으로 활용됩니다. 아래는 에이전트를 플로우 내에서 사용하여 시장 조사를 수행하는 예시입니다:

docs/ko/concepts/production-architecture.mdx

@@ -0,0 +1,154 @@
+---
+title: 프로덕션 아키텍처
+description: CrewAI로 프로덕션 수준의 AI 애플리케이션을 구축하기 위한 모범 사례
+icon: server
+mode: "wide"
+---
+
+# Flow 우선 사고방식 (Flow-First Mindset)
+
+CrewAI로 프로덕션 AI 애플리케이션을 구축할 때는 **Flow로 시작하는 것을 권장합니다**.
+
+개별 Crews나 Agents를 실행하는 것도 가능하지만, 이를 Flow로 감싸면 견고하고 확장 가능한 애플리케이션에 필요한 구조를 제공합니다.
+
+## 왜 Flows인가?
+
+1.  **상태 관리 (State Management)**: Flows는 애플리케이션의 여러 단계에 걸쳐 상태를 관리하는 내장된 방법을 제공합니다. 이는 Crews 간에 데이터를 전달하고, 컨텍스트를 유지하며, 사용자 입력을 처리하는 데 중요합니다.
+2.  **제어 (Control)**: Flows를 사용하면 루프, 조건문, 분기 로직을 포함한 정확한 실행 경로를 정의할 수 있습니다. 이는 예외 상황을 처리하고 애플리케이션이 예측 가능하게 동작하도록 보장하는 데 필수적입니다.
+3.  **관측 가능성 (Observability)**: Flows는 실행을 추적하고, 문제를 디버깅하며, 성능을 모니터링하기 쉽게 만드는 명확한 구조를 제공합니다. 자세한 통찰력을 얻으려면 [CrewAI Tracing](/ko/observability/tracing)을 사용하는 것이 좋습니다. `crewai login`을 실행하여 무료 관측 가능성 기능을 활성화하세요.
+
+## 아키텍처
+
+일반적인 프로덕션 CrewAI 애플리케이션은 다음과 같습니다:
+
+```mermaid
+graph TD
+    Start((시작)) --> Flow[Flow 오케스트레이터]
+    Flow --> State{상태 관리}
+    State --> Step1[1단계: 데이터 수집]
+    Step1 --> Crew1[연구 Crew]
+    Crew1 --> State
+    State --> Step2{조건 확인}
+    Step2 -- "유효함" --> Step3[3단계: 실행]
+    Step3 --> Crew2[액션 Crew]
+    Step2 -- "유효하지 않음" --> End((종료))
+    Crew2 --> End
+```
+
+### 1. Flow 클래스
+`Flow` 클래스는 진입점입니다. 상태 스키마와 로직을 실행하는 메서드를 정의합니다.
+
+```python
+from crewai.flow.flow import Flow, listen, start
+from pydantic import BaseModel
+
+class AppState(BaseModel):
+    user_input: str = ""
+    research_results: str = ""
+    final_report: str = ""
+
+class ProductionFlow(Flow[AppState]):
+    @start()
+    def gather_input(self):
+        # ... 입력 받는 로직 ...
+        pass
+
+    @listen(gather_input)
+    def run_research_crew(self):
+        # ... Crew 트리거 ...
+        pass
+```
+
+### 2. 상태 관리 (State Management)
+Pydantic 모델을 사용하여 상태를 정의하세요. 이는 타입 안전성을 보장하고 각 단계에서 어떤 데이터를 사용할 수 있는지 명확하게 합니다.
+
+- **최소한으로 유지**: 단계 간에 유지해야 할 것만 저장하세요.
+- **구조화된 데이터 사용**: 가능하면 비구조화된 딕셔너리는 피하세요.
+
+### 3. 작업 단위로서의 Crews
+복잡한 작업은 Crews에게 위임하세요. Crew는 특정 목표(예: "주제 연구", "블로그 게시물 작성")에 집중해야 합니다.
+
+- **Crews를 과도하게 설계하지 마세요**: 집중력을 유지하세요.
+- **상태를 명시적으로 전달하세요**: Flow 상태에서 필요한 데이터를 Crew 입력으로 전달하세요.
+
+```python
+    @listen(gather_input)
+    def run_research_crew(self):
+        crew = ResearchCrew()
+        result = crew.kickoff(inputs={"topic": self.state.user_input})
+        self.state.research_results = result.raw
+```
+
+## Control Primitives
+
+CrewAI의 Control Primitives를 활용하여 Crew에 견고함과 제어력을 더하세요.
+
+### 1. Task Guardrails
+[Task Guardrails](/ko/concepts/tasks#task-guardrails)를 사용하여 작업 결과가 수락되기 전에 유효성을 검사하세요. 이를 통해 agent가 고품질 결과를 생성하도록 보장할 수 있습니다.
+
+```python
+def validate_content(result: TaskOutput) -> Tuple[bool, Any]:
+    if len(result.raw) < 100:
+        return (False, "Content is too short. Please expand.")
+    return (True, result.raw)
+
+task = Task(
+    ...,
+    guardrail=validate_content
+)
+```
+
+### 2. 구조화된 출력 (Structured Outputs)
+작업 간에 데이터를 전달하거나 애플리케이션으로 전달할 때는 항상 구조화된 출력(`output_pydantic` 또는 `output_json`)을 사용하세요. 이는 파싱 오류를 방지하고 타입 안전성을 보장합니다.
+
+```python
+class ResearchResult(BaseModel):
+    summary: str
+    sources: List[str]
+
+task = Task(
+    ...,
+    output_pydantic=ResearchResult
+)
+```
+
+### 3. LLM Hooks
+[LLM Hooks](/ko/learn/llm-hooks)를 사용하여 LLM으로 전송되기 전에 메시지를 검사하거나 수정하고, 응답을 정리(sanitize)하세요.
+
+```python
+@before_llm_call
+def log_request(context):
+    print(f"Agent {context.agent.role} is calling the LLM...")
+```
+
+## 배포 패턴
+
+Flow를 배포할 때 다음을 고려하세요:
+
+### CrewAI Enterprise
+Flow를 배포하는 가장 쉬운 방법은 CrewAI Enterprise를 사용하는 것입니다. 인프라, 인증 및 모니터링을 대신 처리합니다.
+
+시작하려면 [배포 가이드](/ko/enterprise/guides/deploy-crew)를 확인하세요.
+
+```bash
+crewai deploy create
+```
+
+### 비동기 실행 (Async Execution)
+장기 실행 작업의 경우 `kickoff_async`를 사용하여 API 차단을 방지하세요.
+
+### 지속성 (Persistence)
+`@persist` 데코레이터를 사용하여 Flow의 상태를 데이터베이스에 저장하세요. 이를 통해 프로세스가 중단되거나 사람의 입력을 기다려야 할 때 실행을 재개할 수 있습니다.
+
+```python
+@persist
+class ProductionFlow(Flow[AppState]):
+    # ...
+```
+
+## 요약
+
+- **Flow로 시작하세요.**
+- **명확한 State를 정의하세요.**
+- **복잡한 작업에는 Crews를 사용하세요.**
+- **API와 지속성을 갖추어 배포하세요.**

docs/ko/enterprise/features/rbac.mdx

@@ -10,7 +10,7 @@ mode: "wide"
 CrewAI AOP의 RBAC는 **조직 수준 역할**과 **자동화(Automation) 수준 가시성**을 결합하여 안전하고 확장 가능한 접근 제어를 제공합니다.
 
 <Frame>
-  <img src="/images/enterprise/users_and_roles.png" alt="CrewAI AOP RBAC 개요" />
+  <img src="/images/enterprise/users_and_roles.png" alt="CrewAI AMP RBAC 개요" />
 
 </Frame>
 
@@ -31,7 +31,8 @@ CrewAI AOP의 RBAC는 **조직 수준 역할**과 **자동화(Automation) 수준
     <b>Settings → Roles</b>로 이동합니다.
   </Step>
   <Step title="역할 선택">
-    <b>Owner</b> 또는 <b>Member</b>를 사용하거나 <b>Create role</b>로 커스텀 역할을 만듭니다.
+    <b>Owner</b> 또는 <b>Member</b>를 사용하거나 <b>Create role</b>로 커스텀
+    역할을 만듭니다.
   </Step>
   <Step title="멤버에 할당">
     사용자들을 선택하여 역할을 지정합니다. 언제든 변경할 수 있습니다.
@@ -40,9 +41,9 @@ CrewAI AOP의 RBAC는 **조직 수준 역할**과 **자동화(Automation) 수준
 
 ### 구성 요약
 
-| 영역 | 위치 | 옵션 |
-|:---|:---|:---|
-| 사용자 & 역할 | Settings → Roles | Owner, Member; 커스텀 역할 |
+| 영역          | 위치                               | 옵션                              |
+| :------------ | :--------------------------------- | :-------------------------------- |
+| 사용자 & 역할 | Settings → Roles                   | Owner, Member; 커스텀 역할        |
 | 자동화 가시성 | Automation → Settings → Visibility | Private; 사용자/역할 화이트리스트 |
 
 ## 자동화 수준 접근 제어
@@ -82,21 +83,26 @@ Private 모드에서는 화이트리스트에 포함된 사용자/역할만 다
 
 ### Private 모드 접근 결과
 
-| 동작 | Owner | 화이트리스트 사용자/역할 | 비포함 |
-|:---|:---|:---|:---|
-| 자동화 보기 | ✓ | ✓ | ✗ |
-| 실행/API | ✓ | ✓ | ✗ |
-| 로그/메트릭/설정 | ✓ | ✓ | ✗ |
+| 동작             | Owner | 화이트리스트 사용자/역할 | 비포함 |
+| :--------------- | :---- | :----------------------- | :----- |
+| 자동화 보기      | ✓     | ✓                        | ✗      |
+| 실행/API         | ✓     | ✓                        | ✗      |
+| 로그/메트릭/설정 | ✓     | ✓                        | ✗      |
 
 <Tip>
-Owner는 항상 접근 가능하며, Private 모드에서는 화이트리스트에 포함된 사용자/역할만 권한이 부여됩니다.
+  Owner는 항상 접근 가능하며, Private 모드에서는 화이트리스트에 포함된
+  사용자/역할만 권한이 부여됩니다.
 </Tip>
 
 <Frame>
-  <img src="/images/enterprise/visibility.png" alt="CrewAI AOP 가시성 설정" />
+  <img src="/images/enterprise/visibility.png" alt="CrewAI AMP 가시성 설정" />
 
 </Frame>
 
-<Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
+<Card
+  title="도움이 필요하신가요?"
+  icon="headset"
+  href="mailto:support@crewai.com"
+>
   RBAC 구성과 점검에 대한 지원이 필요하면 연락해 주세요.
 </Card>

docs/ko/enterprise/features/tools-and-integrations.mdx

@@ -9,221 +9,221 @@ mode: "wide"
 
 도구 & 통합은 서드파티 애플리케이션을 연결하고 에이전트가 런타임에 사용할 내부 도구를 관리하는 중앙 허브입니다.
 
-<Frame>
-  ![도구 & 통합 개요](/images/enterprise/crew_connectors.png)
-</Frame>
+<Frame>![도구 & 통합 개요](/images/enterprise/crew_connectors.png)</Frame>
 
 ## 살펴보기
 
 <Tabs>
   <Tab title="통합" icon="plug">
 
-  ## 에이전트 앱 (통합)
+## 에이전트 앱 (통합)
 
-  Gmail, Google Drive, HubSpot, Slack 등 OAuth 기반 서비스에 연결하여 에이전트 액션을 활성화하세요.
+Gmail, Google Drive, HubSpot, Slack 등 OAuth 기반 서비스에 연결하여 에이전트 액션을 활성화하세요.
 
-  <Steps>
-    <Step title="연결">
-      원하는 앱에서 <b>Connect</b>를 클릭하고 OAuth를 완료합니다.
-    </Step>
-    <Step title="구성">
-      필요에 따라 스코프, 트리거, 사용 가능한 액션을 조정합니다.
-    </Step>
-    <Step title="에이전트에서 사용">
-      연결된 서비스는 에이전트 도구로 사용 가능합니다.
-    </Step>
-  </Steps>
+{" "}
+<Steps>
+  <Step title="연결">
+    원하는 앱에서 <b>Connect</b>를 클릭하고 OAuth를 완료합니다.
+  </Step>
+  <Step title="구성">
+    필요에 따라 스코프, 트리거, 사용 가능한 액션을 조정합니다.
+  </Step>
+  <Step title="에이전트에서 사용">
+    연결된 서비스는 에이전트 도구로 사용 가능합니다.
+  </Step>
+</Steps>
 
-  <Frame>
-    ![앱 그리드](/images/enterprise/agent-apps.png)
-  </Frame>
+{" "}
+<Frame>![앱 그리드](/images/enterprise/agent-apps.png)</Frame>
 
-  ### 계정 연결하기
+### 계정 연결하기
 
-  1. <Link href="https://app.crewai.com/crewai_plus/connectors">Integrations</Link>로 이동
-  2. 원하는 서비스에서 <b>Connect</b> 클릭
-  3. OAuth 플로우 완료 및 스코프 승인
-  4. <Link href="https://app.crewai.com/crewai_plus/settings/integrations">통합 설정</Link>에서 Enterprise Token 복사
+1. <Link href="https://app.crewai.com/crewai_plus/connectors">
+     Integrations
+   </Link>
+   로 이동
+2. 원하는 서비스에서 <b>Connect</b> 클릭
+3. OAuth 플로우 완료 및 스코프 승인
+4. <Link href="https://app.crewai.com/crewai_plus/settings/integrations">
+     통합 설정
+   </Link>
+   에서 Enterprise Token 복사
 
-  <Frame>
-    ![Enterprise Token](/images/enterprise/enterprise_action_auth_token.png)
-  </Frame>
+{" "}
+<Frame>
+  ![Enterprise Token](/images/enterprise/enterprise_action_auth_token.png)
+</Frame>
 
-  ### 통합 도구 설치
+### 통합 도구 설치
 
-  로컬에서 통합을 사용하려면 최신 `crewai-tools` 패키지를 설치하세요.
+로컬에서 통합을 사용하려면 최신 `crewai-tools` 패키지를 설치하세요.
 
-  ```bash
-  uv add crewai-tools
-  ```
+```bash
+uv add crewai-tools
+```
 
-  ### 환경 변수 설정
+### 환경 변수 설정
 
-  <Note>
-    `Agent(apps=[])`와 함께 통합을 사용하려면 Enterprise Token으로 `CREWAI_PLATFORM_INTEGRATION_TOKEN` 환경 변수를 설정해야 합니다.
-  </Note>
+{" "}
+<Note>
+  `Agent(apps=[])`와 함께 통합을 사용하려면 Enterprise Token으로
+  `CREWAI_PLATFORM_INTEGRATION_TOKEN` 환경 변수를 설정해야 합니다.
+</Note>
 
-  ```bash
-  export CREWAI_PLATFORM_INTEGRATION_TOKEN="your_enterprise_token"
-  ```
+```bash
+export CREWAI_PLATFORM_INTEGRATION_TOKEN="your_enterprise_token"
+```
 
-  또는 `.env` 파일에 추가하세요:
+또는 `.env` 파일에 추가하세요:
 
-  ```
-  CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
-  ```
+```
+CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
+```
 
-  ### 사용 예시
+### 사용 예시
 
-  <Tip>
-    새로운 간소화된 접근 방식을 사용하여 엔터프라이즈 앱을 통합하세요. Agent 구성에서 앱과 해당 액션을 직접 지정하기만 하면 됩니다.
-  </Tip>
+{" "}
+<Tip>
+  새로운 간소화된 접근 방식을 사용하여 엔터프라이즈 앱을 통합하세요. Agent
+  구성에서 앱과 해당 액션을 직접 지정하기만 하면 됩니다.
+</Tip>
 
-  ```python
-  from crewai import Agent, Task, Crew
+```python
+from crewai import Agent, Task, Crew
 
-  # Gmail 기능을 가진 에이전트 생성
-  email_agent = Agent(
-      role="이메일 매니저",
-      goal="이메일 커뮤니케이션 관리",
-      backstory="이메일 관리에 특화된 AI 어시스턴트",
-      apps=['gmail', 'gmail/send_email']  # 정식 이름 'gmail' 사용
-  )
+# Gmail 기능을 가진 에이전트 생성
+email_agent = Agent(
+    role="이메일 매니저",
+    goal="이메일 커뮤니케이션 관리",
+    backstory="이메일 관리에 특화된 AI 어시스턴트",
+    apps=['gmail', 'gmail/send_email']  # 정식 이름 'gmail' 사용
+)
 
-  email_task = Task(
-      description="프로젝트 업데이트에 대한 후속 이메일 작성 및 전송",
-      agent=email_agent,
-      expected_output="이메일 전송 성공 확인"
-  )
+email_task = Task(
+    description="프로젝트 업데이트에 대한 후속 이메일 작성 및 전송",
+    agent=email_agent,
+    expected_output="이메일 전송 성공 확인"
+)
 
-  crew = Crew(agents=[email_agent], tasks=[email_task])
-  crew.kickoff()
-  ```
+crew = Crew(agents=[email_agent], tasks=[email_task])
+crew.kickoff()
+```
 
-  ### 도구 필터링
+### 도구 필터링
 
-  ```python
-  from crewai import Agent, Task, Crew
+```python
+from crewai import Agent, Task, Crew
 
-  # 특정 Gmail 액션만 사용하는 에이전트 생성
-  gmail_agent = Agent(
-      role="Gmail 매니저",
-      goal="Gmail 커뮤니케이션 및 알림 관리",
-      backstory="Gmail 커뮤니케이션 조율 AI 어시스턴트",
-      apps=['gmail/fetch_emails']  # 정식 이름과 특정 액션 사용
-  )
+# 특정 Gmail 액션만 사용하는 에이전트 생성
+gmail_agent = Agent(
+    role="Gmail 매니저",
+    goal="Gmail 커뮤니케이션 및 알림 관리",
+    backstory="Gmail 커뮤니케이션 조율 AI 어시스턴트",
+    apps=['gmail/fetch_emails']  # 정식 이름과 특정 액션 사용
+)
 
-  notification_task = Task(
-      description="john@example.com에서 온 이메일 찾기",
-      agent=gmail_agent,
-      expected_output="john@example.com의 이메일을 찾았다는 확인"
-  )
+notification_task = Task(
+    description="john@example.com에서 온 이메일 찾기",
+    agent=gmail_agent,
+    expected_output="john@example.com의 이메일을 찾았다는 확인"
+)
 
-  crew = Crew(agents=[gmail_agent], tasks=[notification_task])
-  ```
+crew = Crew(agents=[gmail_agent], tasks=[notification_task])
+```
 
-  배포된 크루에서는 각 통합의 서비스 설정 페이지에서 사용 가능한 액션을 지정할 수 있습니다.
+배포된 크루에서는 각 통합의 서비스 설정 페이지에서 사용 가능한 액션을 지정할 수 있습니다.
 
-  <Frame>
-    ![액션 필터링](/images/enterprise/filtering_enterprise_action_tools.png)
-  </Frame>
+{" "}
+<Frame>
+  ![액션 필터링](/images/enterprise/filtering_enterprise_action_tools.png)
+</Frame>
 
-  ### 범위 지정 배포 (다중 사용자 조직)
+### 범위 지정 배포 (다중 사용자 조직)
 
-  각 통합을 특정 사용자로 범위 지정할 수 있습니다 (예: 특정 사용자의 Gmail 계정 사용).
+각 통합을 특정 사용자로 범위 지정할 수 있습니다 (예: 특정 사용자의 Gmail 계정 사용).
 
-  <Tip>
-    팀/사용자별 데이터 접근을 분리해야 할 때 유용합니다.
-  </Tip>
+{" "}
+<Tip>팀/사용자별 데이터 접근을 분리해야 할 때 유용합니다.</Tip>
 
-  `user_bearer_token`을 사용해 요청 사용자로 인증을 범위 지정합니다. 사용자가 로그인하지 않은 경우 연결된 통합을 사용하지 않으며, 그렇지 않으면 배포에 설정된 기본 토큰을 사용합니다.
+`user_bearer_token`을 사용해 요청 사용자로 인증을 범위 지정합니다. 사용자가 로그인하지 않은 경우 연결된 통합을 사용하지 않으며, 그렇지 않으면 배포에 설정된 기본 토큰을 사용합니다.
 
-  <Frame>
-    ![사용자 토큰](/images/enterprise/user_bearer_token.png)
-  </Frame>
+{" "}
+<Frame>![사용자 토큰](/images/enterprise/user_bearer_token.png)</Frame>
 
-  <div id="catalog"></div>
-  ### 카탈로그
+{" "}
+<div id="catalog"></div>
+### 카탈로그
 
-  #### 커뮤니케이션 & 협업
-  - Gmail — 이메일 및 초안 관리
-  - Slack — 워크스페이스 알림 및 경보
-  - Microsoft — Office 365 및 Teams 통합
+#### 커뮤니케이션 & 협업
 
-  #### 프로젝트 관리
-  - Jira — 이슈 추적 및 프로젝트 관리
-  - ClickUp — 작업 및 생산성 관리
-  - Asana — 팀 작업 조율
-  - Notion — 페이지 및 데이터베이스 관리
-  - Linear — 버그/프로젝트 추적
-  - GitHub — 리포지토리 및 이슈 관리
+- Gmail — 이메일 및 초안 관리
+- Slack — 워크스페이스 알림 및 경보
+- Microsoft — Office 365 및 Teams 통합
 
-  #### CRM
-  - Salesforce — 계정 및 기회 관리
-  - HubSpot — 파이프라인/연락처 관리
-  - Zendesk — 고객 지원 티켓 관리
+#### 프로젝트 관리
 
-  #### 비즈니스 & 금융
-  - Stripe — 결제 처리 및 고객 관리
-  - Shopify — 전자상거래 및 상품 관리
+- Jira — 이슈 추적 및 프로젝트 관리
+- ClickUp — 작업 및 생산성 관리
+- Asana — 팀 작업 조율
+- Notion — 페이지 및 데이터베이스 관리
+- Linear — 버그/프로젝트 추적
+- GitHub — 리포지토리 및 이슈 관리
 
-  #### 생산성 & 스토리지
-  - Google Sheets — 스프레드시트 동기화
-  - Google Calendar — 일정/이벤트 관리
-  - Box — 파일 스토리지
+#### CRM
 
-  …더 많은 통합이 추가될 예정입니다!
+- Salesforce — 계정 및 기회 관리
+- HubSpot — 파이프라인/연락처 관리
+- Zendesk — 고객 지원 티켓 관리
+
+#### 비즈니스 & 금융
+
+- Stripe — 결제 처리 및 고객 관리
+- Shopify — 전자상거래 및 상품 관리
+
+#### 생산성 & 스토리지
+
+- Google Sheets — 스프레드시트 동기화
+- Google Calendar — 일정/이벤트 관리
+- Box — 파일 스토리지
+
+…더 많은 통합이 추가될 예정입니다!
 
   </Tab>
   <Tab title="내부 도구" icon="toolbox">
 
-  ## 내부 도구
+## 내부 도구
 
-  로컬에서 도구를 만들고, CrewAI AOP 도구 저장소에 게시한 후, 에이전트에서 사용하세요.
+로컬에서 도구를 만들고, CrewAI AMP 도구 저장소에 게시한 후, 에이전트에서 사용하세요.
 
-  <Tip>
-  아래 명령을 실행하기 전에 CrewAI AOP 계정에 로그인하세요:
-    ```bash
-    crewai login
-    ```
-  </Tip>
+{" "}
+<Tip>
+  아래 명령을 실행하기 전에 CrewAI AMP 계정에 로그인하세요: ```bash crewai login```
+</Tip>
 
-  <Frame>
-    ![내부 도구](/images/enterprise/tools-integrations-internal.png)
-  </Frame>
+{" "}
+<Frame>![내부 도구](/images/enterprise/tools-integrations-internal.png)</Frame>
 
-  <Steps>
-    <Step title="생성">
-      로컬에서 새 도구 생성
-      ```bash
-      crewai tool create your-tool
-      ```
-    </Step>
-    <Step title="게시">
-      도구 저장소에 게시
-      ```bash
-      crewai tool publish
-      ```
-    </Step>
-    <Step title="설치">
-      도구 저장소에서 설치
-      ```bash
-      crewai tool install your-tool
-      ```
-    </Step>
-  </Steps>
+{" "}
+<Steps>
+  <Step title="생성">
+    로컬에서 새 도구 생성 ```bash crewai tool create your-tool ```
+  </Step>
+  <Step title="게시">도구 저장소에 게시 ```bash crewai tool publish ```</Step>
+  <Step title="설치">
+    도구 저장소에서 설치 ```bash crewai tool install your-tool ```
+  </Step>
+</Steps>
 
-  관리:
+관리:
 
-  - 이름 및 설명
-  - 가시성 (비공개 / 공개)
-  - 필요한 환경 변수
-  - 버전 이력 및 다운로드
-  - 팀/역할 접근 권한
+- 이름 및 설명
+- 가시성 (비공개 / 공개)
+- 필요한 환경 변수
+- 버전 이력 및 다운로드
+- 팀/역할 접근 권한
 
-  <Frame>
-    ![도구 설정](/images/enterprise/tool-configs.png)
-  </Frame>
+{" "}
+<Frame>![도구 설정](/images/enterprise/tool-configs.png)</Frame>
 
   </Tab>
 </Tabs>
@@ -231,10 +231,18 @@ mode: "wide"
 ## 관련 문서
 
 <CardGroup cols={2}>
-  <Card title="도구 저장소" href="/ko/enterprise/guides/tool-repository" icon="toolbox">
+  <Card
+    title="도구 저장소"
+    href="/ko/enterprise/guides/tool-repository"
+    icon="toolbox"
+  >
     크루 기능을 확장할 수 있도록 도구를 게시하고 설치하세요.
   </Card>
-  <Card title="Webhook 자동화" href="/ko/enterprise/guides/webhook-automation" icon="bolt">
+  <Card
+    title="Webhook 자동화"
+    href="/ko/enterprise/guides/webhook-automation"
+    icon="bolt"
+  >
     워크플로를 자동화하고 외부 플랫폼/서비스와 통합하세요.
   </Card>
 </CardGroup>

docs/ko/enterprise/features/traces.mdx

@@ -20,15 +20,13 @@ CrewAI AOP의 Traces는 crew의 작동 과정을 처음 입력에서 최종 출
 - 실행 시간
 - 비용 추정치
 
-<Frame>
-  ![Traces Overview](/images/enterprise/traces-overview.png)
-</Frame>
+<Frame>![Traces Overview](/images/enterprise/traces-overview.png)</Frame>
 
 ## 트레이스(Traces) 접근하기
 
 <Steps>
   <Step title="트레이스 탭으로 이동">
-    CrewAI AOP 대시보드에 들어가면, **트레이스**를 클릭하여 모든 실행 기록을 볼 수 있습니다.
+    CrewAI AMP 대시보드에 들어가면, **트레이스**를 클릭하여 모든 실행 기록을 볼 수 있습니다.
   </Step>
 
   <Step title="실행 선택하기">
@@ -51,9 +49,7 @@ CrewAI AOP의 Traces는 crew의 작동 과정을 처음 입력에서 최종 출
 - **실행 시간**: crew 런의 전체 소요 시간
 - **예상 비용**: 토큰 사용량을 기반으로 한 대략적인 비용
 
-<Frame>
-  ![Execution Summary](/images/enterprise/trace-summary.png)
-</Frame>
+<Frame>![Execution Summary](/images/enterprise/trace-summary.png)</Frame>
 
 ### 2. Tasks & Agents
 
@@ -64,33 +60,25 @@ CrewAI AOP의 Traces는 crew의 작동 과정을 처음 입력에서 최종 출
 - 상태 (완료/실패)
 - task의 개별 실행 시간
 
-<Frame>
-  ![Task List](/images/enterprise/trace-tasks.png)
-</Frame>
+<Frame>![Task List](/images/enterprise/trace-tasks.png)</Frame>
 
 ### 3. 최종 결과
 
 모든 작업이 완료된 후 crew가 생성한 최종 결과를 표시합니다.
 
-<Frame>
-  ![최종 결과](/images/enterprise/final-output.png)
-</Frame>
+<Frame>![최종 결과](/images/enterprise/final-output.png)</Frame>
 
 ### 4. 실행 타임라인
 
 각 작업이 시작되고 종료된 시점을 시각적으로 표현하여 병목 현상이나 병렬 실행 패턴을 파악하는 데 도움이 됩니다.
 
-<Frame>
-  ![실행 타임라인](/images/enterprise/trace-timeline.png)
-</Frame>
+<Frame>![실행 타임라인](/images/enterprise/trace-timeline.png)</Frame>
 
 ### 5. 상세 작업 보기
 
 타임라인이나 작업 목록에서 특정 작업을 클릭하면 다음을 볼 수 있습니다:
 
-<Frame>
-  ![상세 작업 보기](/images/enterprise/trace-detailed-task.png)
-</Frame>
+<Frame>![상세 작업 보기](/images/enterprise/trace-detailed-task.png)</Frame>
 
 - **작업 키**: 작업의 고유 식별자
 - **작업 ID**: 시스템 내의 기술적 식별자
@@ -120,6 +108,7 @@ CrewAI AOP의 Traces는 crew의 작동 과정을 처음 입력에서 최종 출
     <Frame>
       ![Failure Points](/images/enterprise/failure.png)
     </Frame>
+
   </Step>
 
   <Step title="성능 최적화">
@@ -129,6 +118,7 @@ CrewAI AOP의 Traces는 crew의 작동 과정을 처음 입력에서 최종 출
     - 과도한 토큰 사용
     - 중복된 도구 작업
     - 불필요한 API 호출
+
   </Step>
 
   <Step title="비용 효율성 향상">
@@ -138,9 +128,15 @@ CrewAI AOP의 Traces는 crew의 작동 과정을 처음 입력에서 최종 출
     - 프롬프트를 더 간결하게 다듬기
     - 자주 액세스하는 정보 캐싱
     - 중복 작업을 최소화하도록 작업 구조화하기
+
   </Step>
 </Steps>
 
-<Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
-  트레이스 분석이나 기타 CrewAI 엔터프라이즈 기능에 대한 지원이 필요하시면 저희 지원팀에 문의하세요.
+<Card
+  title="도움이 필요하신가요?"
+  icon="headset"
+  href="mailto:support@crewai.com"
+>
+  트레이스 분석이나 기타 CrewAI 엔터프라이즈 기능에 대한 지원이 필요하시면 저희
+  지원팀에 문의하세요.
 </Card>

docs/ko/enterprise/guides/automation-triggers.mdx

@@ -1,11 +1,11 @@
 ---
 title: "트리거 개요"
-description: "CrewAI AOP 트리거의 동작 방식과 관리 방법, 그리고 통합별 플레이북을 한눈에 확인하세요"
+description: "CrewAI AMP 트리거의 동작 방식과 관리 방법, 그리고 통합별 플레이북을 한눈에 확인하세요"
 icon: "bolt"
 mode: "wide"
 ---
 
-CrewAI AOP 트리거는 팀이 이미 사용하고 있는 도구의 실시간 이벤트와 자동화를 연결합니다. 폴링이나 수동 실행 대신, 트리거는 새로운 이메일, 캘린더 업데이트, CRM 상태 변화 등을 감지하여 지정한 크루 또는 플로우를 즉시 실행합니다.
+CrewAI AMP 트리거는 팀이 이미 사용하고 있는 도구의 실시간 이벤트와 자동화를 연결합니다. 폴링이나 수동 실행 대신, 트리거는 새로운 이메일, 캘린더 업데이트, CRM 상태 변화 등을 감지하여 지정한 크루 또는 플로우를 즉시 실행합니다.
 
 <iframe
   className="w-full aspect-video rounded-xl"
@@ -25,37 +25,61 @@ CrewAI AOP 트리거는 팀이 이미 사용하고 있는 도구의 실시간
     <a href="/ko/enterprise/guides/gmail-trigger">새로운 이메일이나 스레드 업데이트에 맞춰 크루를 실행하세요.</a>
   </Card>
 
-  <Card title="Google Calendar 트리거" icon="calendar-days">
-    <a href="/ko/enterprise/guides/google-calendar-trigger">캘린더 이벤트 생성, 수정, 취소에 대응하세요.</a>
-  </Card>
+{" "}
+<Card title="Google Calendar 트리거" icon="calendar-days">
+  <a href="/ko/enterprise/guides/google-calendar-trigger">
+    캘린더 이벤트 생성, 수정, 취소에 대응하세요.
+  </a>
+</Card>
 
-  <Card title="Google Drive 트리거" icon="folder-open">
-    <a href="/ko/enterprise/guides/google-drive-trigger">Drive 파일 업로드, 수정, 삭제를 감시하세요.</a>
-  </Card>
+{" "}
+<Card title="Google Drive 트리거" icon="folder-open">
+  <a href="/ko/enterprise/guides/google-drive-trigger">
+    Drive 파일 업로드, 수정, 삭제를 감시하세요.
+  </a>
+</Card>
 
-  <Card title="Outlook 트리거" icon="envelope-open">
-    <a href="/ko/enterprise/guides/outlook-trigger">Outlook의 새로운 메일이나 삭제된 이벤트에 대응하세요.</a>
-  </Card>
+{" "}
+<Card title="Outlook 트리거" icon="envelope-open">
+  <a href="/ko/enterprise/guides/outlook-trigger">
+    Outlook의 새로운 메일이나 삭제된 이벤트에 대응하세요.
+  </a>
+</Card>
 
-  <Card title="OneDrive 트리거" icon="cloud">
-    <a href="/ko/enterprise/guides/onedrive-trigger">OneDrive 파일 활동 및 공유 변경 사항을 감사하세요.</a>
-  </Card>
+{" "}
+<Card title="OneDrive 트리거" icon="cloud">
+  <a href="/ko/enterprise/guides/onedrive-trigger">
+    OneDrive 파일 활동 및 공유 변경 사항을 감사하세요.
+  </a>
+</Card>
 
-  <Card title="Microsoft Teams 트리거" icon="comments">
-    <a href="/ko/enterprise/guides/microsoft-teams-trigger">새로운 Teams 채팅이 생성될 때 워크플로우를 시작하세요.</a>
-  </Card>
+{" "}
+<Card title="Microsoft Teams 트리거" icon="comments">
+  <a href="/ko/enterprise/guides/microsoft-teams-trigger">
+    새로운 Teams 채팅이 생성될 때 워크플로우를 시작하세요.
+  </a>
+</Card>
 
-  <Card title="HubSpot 트리거" icon="hubspot">
-    <a href="/ko/enterprise/guides/hubspot-trigger">HubSpot 워크플로우와 라이프사이클 이벤트에서 자동화를 실행하세요.</a>
-  </Card>
+{" "}
+<Card title="HubSpot 트리거" icon="hubspot">
+  <a href="/ko/enterprise/guides/hubspot-trigger">
+    HubSpot 워크플로우와 라이프사이클 이벤트에서 자동화를 실행하세요.
+  </a>
+</Card>
 
-  <Card title="Salesforce 트리거" icon="salesforce">
-    <a href="/ko/enterprise/guides/salesforce-trigger">Salesforce 프로세스를 CrewAI 크루와 연결해 CRM 자동화를 구현하세요.</a>
-  </Card>
+{" "}
+<Card title="Salesforce 트리거" icon="salesforce">
+  <a href="/ko/enterprise/guides/salesforce-trigger">
+    Salesforce 프로세스를 CrewAI 크루와 연결해 CRM 자동화를 구현하세요.
+  </a>
+</Card>
 
-  <Card title="Slack 트리거" icon="slack">
-    <a href="/ko/enterprise/guides/slack-trigger">Slack 슬래시 명령으로 크루를 바로 실행하세요.</a>
-  </Card>
+{" "}
+<Card title="Slack 트리거" icon="slack">
+  <a href="/ko/enterprise/guides/slack-trigger">
+    Slack 슬래시 명령으로 크루를 바로 실행하세요.
+  </a>
+</Card>
 
   <Card title="Zapier 트리거" icon="bolt">
     <a href="/ko/enterprise/guides/zapier-trigger">CrewAI를 수천 개의 Zapier 지원 앱과 연동하세요.</a>
@@ -77,7 +101,10 @@ CrewAI AOP 트리거는 팀이 이미 사용하고 있는 도구의 실시간
 2. **Triggers** 탭을 클릭하여 사용 가능한 통합을 확인합니다.
 
 <Frame>
-  <img src="/images/enterprise/list-available-triggers.png" alt="사용 가능한 트리거 목록" />
+  <img
+    src="/images/enterprise/list-available-triggers.png"
+    alt="사용 가능한 트리거 목록"
+  />
 </Frame>
 
 ### 트리거 활성화/비활성화
@@ -123,6 +150,7 @@ crewai triggers list
 ```
 
 이 명령은 연결된 통합을 기반으로 사용 가능한 모든 트리거를 표시합니다:
+
 - 통합 이름 및 연결 상태
 - 사용 가능한 트리거 유형
 - 트리거 이름 및 설명
@@ -142,6 +170,7 @@ crewai triggers run microsoft_onedrive/file_changed
 ```
 
 이 명령은:
+
 - 로컬에서 크루를 실행합니다
 - 완전하고 실제적인 트리거 payload를 전달합니다
 - 프로덕션에서 크루가 호출되는 방식을 정확히 시뮬레이션합니다
@@ -221,17 +250,20 @@ def delegate_to_crew(self, crewai_trigger_payload: dict = None):
 ## 문제 해결
 
 **트리거가 실행되지 않나요?**
+
 - 배포의 Triggers 탭에서 트리거가 활성화되어 있는지 확인하세요
 - Tools & Integrations에서 통합 연결 상태를 확인하세요
 - 필요한 모든 환경 변수가 올바르게 구성되어 있는지 확인하세요
 
 **실행 중 오류가 발생하나요?**
+
 - 실행 로그에서 오류 세부 정보를 확인하세요
 - `crewai triggers run <트리거_이름>`을 사용하여 로컬에서 테스트하고 정확한 payload 구조를 확인하세요
 - 크루가 `crewai_trigger_payload` 매개변수를 처리할 수 있는지 확인하세요
 - 크루가 트리거 payload에 포함되지 않은 매개변수를 기대하지 않는지 확인하세요
 
 **개발 문제:**
+
 - 배포하기 전에 항상 `crewai triggers run <trigger>`로 테스트하여 전체 payload를 확인하세요
 - `crewai run`은 트리거 호출을 시뮬레이션하지 않으므로 `crewai triggers run`을 대신 사용하세요
 - `crewai triggers list`를 사용하여 연결된 통합에 사용 가능한 트리거를 확인하세요

docs/ko/enterprise/guides/azure-openai-setup.mdx

@@ -19,8 +19,8 @@ mode: "wide"
             </Frame>
     </Step>
 
-    <Step title="CrewAI AOP 연결 구성">
-        4. 다른 탭에서 `CrewAI AOP > LLM Connections`를 엽니다. LLM Connection에 이름을 지정하고, 공급자로 Azure를 선택한 다음, Azure에서 선택한 것과 동일한 모델을 선택하세요.
+    <Step title="CrewAI AMP 연결 구성">
+        4. 다른 탭에서 `CrewAI AMP > LLM Connections`를 엽니다. LLM Connection에 이름을 지정하고, 공급자로 Azure를 선택한 다음, Azure에서 선택한 것과 동일한 모델을 선택하세요.
         5. 같은 페이지에서 3단계에서 가져온 환경 변수를 추가하세요:
             - 하나는 `AZURE_DEPLOYMENT_TARGET_URL` (Target URI 사용)로 명명합니다. URL은 다음과 같이 표시됩니다: https://your-deployment.openai.azure.com/openai/deployments/gpt-4o/chat/completions?api-version=2024-08-01-preview
             - 다른 하나는 `AZURE_API_KEY` (Key 사용)로 명명합니다.
@@ -28,7 +28,7 @@ mode: "wide"
     </Step>
 
     <Step title="기본 구성 설정">
-        7. `CrewAI AOP > Settings > Defaults > Crew Studio LLM Settings`에서 새 LLM Connection과 모델을 기본값으로 설정합니다.
+        7. `CrewAI AMP > Settings > Defaults > Crew Studio LLM Settings`에서 새 LLM Connection과 모델을 기본값으로 설정합니다.
     </Step>
 
     <Step title="네트워크 액세스 구성">
@@ -37,6 +37,7 @@ mode: "wide"
             - `Resource Management > Networking`으로 이동합니다.
             - `Allow access from all networks`가 활성화되어 있는지 확인하세요. 이 설정이 제한되어 있으면 CrewAI가 Azure OpenAI 엔드포인트에 접근하지 못할 수 있습니다.
     </Step>
+
 </Steps>
 
 ## 확인
@@ -46,6 +47,7 @@ mode: "wide"
 ## 문제 해결
 
 문제가 발생한 경우:
+
 - Target URI 형식이 예상 패턴과 일치하는지 확인하세요
 - API 키가 올바르고 적절한 권한을 가지고 있는지 확인하세요
 - 네트워크 액세스가 CrewAI 연결을 허용하도록 구성되어 있는지 확인하세요

docs/ko/enterprise/guides/build-crew.mdx

@@ -7,7 +7,7 @@ mode: "wide"
 
 ## 개요
 
-[CrewAI AOP](https://app.crewai.com)는 프로덕션 환경에서 AI 에이전트를 **생성**, **배포** 및 **관리**하는 과정을 간소화합니다.
+[CrewAI AMP](https://app.crewai.com)는 프로덕션 환경에서 AI 에이전트를 **생성**, **배포** 및 **관리**하는 과정을 간소화합니다.
 
 ## 시작하기
 
@@ -23,20 +23,22 @@ mode: "wide"
 ### 설치 및 설정
 
 <Card title="표준 설치 따라하기" icon="wrench" href="/ko/installation">
-  CrewAI CLI를 설정하고 첫 번째 프로젝트를 생성하기 위해 표준 설치 가이드를 따라주세요.
+  CrewAI CLI를 설정하고 첫 번째 프로젝트를 생성하기 위해 표준 설치 가이드를
+  따라주세요.
 </Card>
 
 ### 크루 구성하기
 
 <Card title="빠른 시작 튜토리얼" icon="rocket" href="/ko/quickstart">
-  YAML 구성을 사용하여 첫 번째 에이전트 크루를 만드는 방법은 빠른 시작 가이드를 따라주세요.
+  YAML 구성을 사용하여 첫 번째 에이전트 크루를 만드는 방법은 빠른 시작 가이드를
+  따라주세요.
 </Card>
 
 ## 지원 및 리소스
 
 Enterprise 전용 지원 또는 문의가 필요하신 경우, [support@crewai.com](mailto:support@crewai.com)으로 저희 전담 지원팀에 연락해 주시기 바랍니다.
 
-
 <Card title="데모 예약" icon="calendar" href="mailto:support@crewai.com">
-  Enterprise 기능과 해당 기능이 귀사의 조직에 어떻게 도움이 될 수 있는지 알아보시려면 저희 팀과 상담 일정을 예약하세요.
+  Enterprise 기능과 해당 기능이 귀사의 조직에 어떻게 도움이 될 수 있는지
+  알아보시려면 저희 팀과 상담 일정을 예약하세요.
 </Card>

docs/ko/enterprise/guides/deploy-crew.mdx

@@ -6,14 +6,17 @@ mode: "wide"
 ---
 
 <Note>
-로컬에서 또는 Crew Studio를 통해 crew를 생성한 후, 다음 단계는 이를 CrewAI AOP 플랫폼에 배포하는 것입니다. 본 가이드에서는 다양한 배포 방법을 다루며, 여러분의 워크플로우에 가장 적합한 방식을 선택할 수 있도록 안내합니다.
+  로컬에서 또는 Crew Studio를 통해 crew를 생성한 후, 다음 단계는 이를 CrewAI AMP
+  플랫폼에 배포하는 것입니다. 본 가이드에서는 다양한 배포 방법을 다루며,
+  여러분의 워크플로우에 가장 적합한 방식을 선택할 수 있도록 안내합니다.
 </Note>
 
 ## 사전 준비 사항
 
 <CardGroup cols={2}>
   <Card title="배포 준비가 된 Crew" icon="users">
-    작동 중인 crew가 로컬에서 빌드되었거나 Crew Studio를 통해 생성되어 있어야 합니다.
+    작동 중인 crew가 로컬에서 빌드되었거나 Crew Studio를 통해 생성되어 있어야
+    합니다.
   </Card>
   <Card title="GitHub 저장소" icon="github">
     crew 코드가 GitHub 저장소에 있어야 합니다(GitHub 연동 방식의 경우).
@@ -39,10 +42,10 @@ CLI는 로컬에서 개발된 crew를 Enterprise 플랫폼에 가장 빠르게
   </Step>
 
   <Step title="Enterprise 플랫폼에 인증">
-    먼저, CrewAI AOP 플랫폼에 CLI를 인증해야 합니다:
+    먼저, CrewAI AMP 플랫폼에 CLI를 인증해야 합니다:
 
     ```bash
-    # 이미 CrewAI AOP 계정이 있거나 새로 생성하고 싶을 때:
+    # 이미 CrewAI AMP 계정이 있거나 새로 생성하고 싶을 때:
     crewai login
     ```
 
@@ -124,19 +127,19 @@ crewai deploy remove <deployment_id>
 
 ## 옵션 2: 웹 인터페이스를 통한 직접 배포
 
-GitHub 계정을 연결하여 CrewAI AOP 웹 인터페이스를 통해 crews를 직접 배포할 수도 있습니다. 이 방법은 로컬 머신에서 CLI를 사용할 필요가 없습니다.
+GitHub 계정을 연결하여 CrewAI AMP 웹 인터페이스를 통해 crews를 직접 배포할 수도 있습니다. 이 방법은 로컬 머신에서 CLI를 사용할 필요가 없습니다.
 
 <Steps>
 
   <Step title="GitHub로 푸시하기">
 
-  crew를 GitHub 저장소에 푸시해야 합니다. 아직 crew를 만들지 않았다면, [이 튜토리얼](/ko/quickstart)을 따라할 수 있습니다.
+crew를 GitHub 저장소에 푸시해야 합니다. 아직 crew를 만들지 않았다면, [이 튜토리얼](/ko/quickstart)을 따라할 수 있습니다.
 
   </Step>
 
   <Step title="GitHub를 CrewAI AOP에 연결하기">
 
-    1. [CrewAI AOP](https://app.crewai.com)에 로그인합니다.
+    1. [CrewAI AMP](https://app.crewai.com)에 로그인합니다.
     2. "Connect GitHub" 버튼을 클릭합니다.
 
     <Frame>
@@ -190,7 +193,8 @@ GitHub 계정을 연결하여 CrewAI AOP 웹 인터페이스를 통해 crews를
 ## ⚠️ 환경 변수 보안 요구사항
 
 <Warning>
-**중요**: CrewAI AOP는 환경 변수 이름에 대한 보안 제한이 있으며, 이를 따르지 않을 경우 배포가 실패할 수 있습니다.
+  **중요**: CrewAI AOP는 환경 변수 이름에 대한 보안 제한이 있으며, 이를 따르지
+  않을 경우 배포가 실패할 수 있습니다.
 </Warning>
 
 ### 차단된 환경 변수 패턴
@@ -198,12 +202,14 @@ GitHub 계정을 연결하여 CrewAI AOP 웹 인터페이스를 통해 crews를
 보안상의 이유로, 다음과 같은 환경 변수 명명 패턴은 **자동으로 필터링**되며 배포에 문제가 발생할 수 있습니다:
 
 **차단된 패턴:**
+
 - `_TOKEN`으로 끝나는 변수 (예: `MY_API_TOKEN`)
 - `_PASSWORD`로 끝나는 변수 (예: `DB_PASSWORD`)
 - `_SECRET`로 끝나는 변수 (예: `API_SECRET`)
 - 특정 상황에서 `_KEY`로 끝나는 변수
 
 **특정 차단 변수:**
+
 - `GITHUB_USER`, `GITHUB_TOKEN`
 - `AWS_REGION`, `AWS_DEFAULT_REGION`
 - 다양한 내부 CrewAI 시스템 변수
@@ -211,6 +217,7 @@ GitHub 계정을 연결하여 CrewAI AOP 웹 인터페이스를 통해 crews를
 ### 허용된 예외
 
 일부 변수는 차단된 패턴과 일치하더라도 명시적으로 허용됩니다:
+
 - `AZURE_AD_TOKEN`
 - `AZURE_OPENAI_AD_TOKEN`
 - `ENTERPRISE_ACTION_TOKEN`
@@ -240,7 +247,8 @@ API_CONFIG=secret123
 4. **변경 내용 문서화**: 팀을 위해 이름이 변경된 변수를 기록
 
 <Tip>
-배포 실패 시, 환경 변수 에러 메시지가 난해하다면 먼저 변수 이름이 이 패턴을 따르는지 확인하세요.
+  배포 실패 시, 환경 변수 에러 메시지가 난해하다면 먼저 변수 이름이 이 패턴을
+  따르는지 확인하세요.
 </Tip>
 
 ### 배포된 Crew와 상호작용하기
@@ -248,6 +256,7 @@ API_CONFIG=secret123
 배포가 완료되면 다음을 통해 crew에 접근할 수 있습니다:
 
 1. **REST API**: 플랫폼에서 아래의 주요 경로가 포함된 고유한 HTTPS 엔드포인트를 생성합니다:
+
    - `/inputs`: 필요한 입력 파라미터 목록
    - `/kickoff`: 제공된 입력값으로 실행 시작
    - `/status/{kickoff_id}`: 실행 상태 확인
@@ -286,6 +295,11 @@ Enterprise 플랫폼은 또한 다음을 제공합니다:
 - **Custom Tools Repository**: 도구 생성, 공유 및 설치
 - **Crew Studio**: 코드를 작성하지 않고 채팅 인터페이스를 통해 crew 빌드
 
-<Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
-  Enterprise 플랫폼의 배포 문제 또는 문의 사항이 있으시면 지원팀에 연락해 주십시오.
+<Card
+  title="도움이 필요하신가요?"
+  icon="headset"
+  href="mailto:support@crewai.com"
+>
+  Enterprise 플랫폼의 배포 문제 또는 문의 사항이 있으시면 지원팀에 연락해
+  주십시오.
 </Card>

docs/ko/enterprise/guides/enable-crew-studio.mdx

@@ -6,7 +6,8 @@ mode: "wide"
 ---
 
 <Tip>
-Crew Studio는 대화형 인터페이스를 통해 빠르게 Crew를 스캐폴딩하거나 구축할 수 있는 강력한 **노코드/로우코드** 도구입니다.
+  Crew Studio는 대화형 인터페이스를 통해 빠르게 Crew를 스캐폴딩하거나 구축할 수
+  있는 강력한 **노코드/로우코드** 도구입니다.
 </Tip>
 
 ## Crew Studio란?
@@ -24,7 +25,7 @@ Crew Studio를 사용하면 다음과 같은 작업이 가능합니다:
 - 적절한 tool 선택
 - 필요한 입력값 구성
 - 커스터마이징을 위한 다운로드 가능한 코드 생성
-- CrewAI AOP 플랫폼에 직접 배포
+- CrewAI AMP 플랫폼에 직접 배포
 
 ## 구성 단계
 
@@ -32,7 +33,7 @@ Crew Studio를 사용하기 전에 LLM 연결을 구성해야 합니다:
 
 <Steps>
   <Step title="LLM 연결 설정">
-    CrewAI AOP 대시보드의 **LLM Connections** 탭으로 이동하여 새 LLM 연결을 만듭니다.
+    CrewAI AMP 대시보드의 **LLM Connections** 탭으로 이동하여 새 LLM 연결을 만듭니다.
 
     <Note>
       CrewAI에서 지원하는 원하는 LLM 공급자를 자유롭게 사용하실 수 있습니다.
@@ -52,6 +53,7 @@ Crew Studio를 사용하기 전에 LLM 연결을 구성해야 합니다:
     <Frame>
       ![LLM 연결 구성](/images/enterprise/llm-connection-config.png)
     </Frame>
+
   </Step>
 
   <Step title="연결 추가 확인">
@@ -60,6 +62,7 @@ Crew Studio를 사용하기 전에 LLM 연결을 구성해야 합니다:
     <Frame>
       ![연결 추가됨](/images/enterprise/connection-added.png)
     </Frame>
+
   </Step>
 
   <Step title="LLM 기본값 구성">
@@ -73,6 +76,7 @@ Crew Studio를 사용하기 전에 LLM 연결을 구성해야 합니다:
     <Frame>
       ![LLM 기본값 구성](/images/enterprise/llm-defaults.png)
     </Frame>
+
   </Step>
 </Steps>
 
@@ -82,7 +86,7 @@ LLM 연결과 기본 설정을 구성했다면 이제 Crew Studio 사용을 시
 
 <Steps>
   <Step title="Studio 접속">
-    CrewAI AOP 대시보드에서 **Studio** 섹션으로 이동하세요.
+    CrewAI AMP 대시보드에서 **Studio** 섹션으로 이동하세요.
   </Step>
 
   <Step title="대화 시작">
@@ -93,6 +97,7 @@ LLM 연결과 기본 설정을 구성했다면 이제 Crew Studio 사용을 시
     ```
 
     Crew Assistant는 귀하의 요구 사항을 더 잘 이해하기 위해 추가 질문을 할 것입니다.
+
   </Step>
 
   <Step title="생성된 crew 검토">
@@ -104,14 +109,16 @@ LLM 연결과 기본 설정을 구성했다면 이제 Crew Studio 사용을 시
     - 사용할 도구
 
     이 단계에서 구성 내용을 세부적으로 수정할 수 있습니다.
+
   </Step>
 
   <Step title="배포 또는 다운로드">
     구성에 만족하면 다음을 수행할 수 있습니다:
 
     - 생성된 코드를 다운로드하여 로컬에서 커스터마이징
-    - crew를 CrewAI AOP 플랫폼에 직접 배포
+    - crew를 CrewAI AMP 플랫폼에 직접 배포
     - 구성을 수정하고 crew를 재생성
+
   </Step>
 
   <Step title="crew 테스트">
@@ -120,7 +127,8 @@ LLM 연결과 기본 설정을 구성했다면 이제 Crew Studio 사용을 시
 </Steps>
 
 <Tip>
-최상의 결과를 얻으려면 crew가 달성해야 할 목표를 명확하고 상세하게 설명하세요. 원하는 입력값과 예상 결과를 설명에 포함시키는 것이 좋습니다.
+  최상의 결과를 얻으려면 crew가 달성해야 할 목표를 명확하고 상세하게 설명하세요.
+  원하는 입력값과 예상 결과를 설명에 포함시키는 것이 좋습니다.
 </Tip>
 
 ## 예시 워크플로우
@@ -134,11 +142,13 @@ LLM 연결과 기본 설정을 구성했다면 이제 Crew Studio 사용을 시
     ```md
     I need a crew that can analyze financial news and provide investment recommendations
     ```
+
   </Step>
 
-  <Step title="질문에 답하기">
-    crew assistant가 요구 사항을 구체화할 수 있도록 하는 추가 질문에 답변하세요.
-  </Step>
+{" "}
+<Step title="질문에 답하기">
+  crew assistant가 요구 사항을 구체화할 수 있도록 하는 추가 질문에 답변하세요.
+</Step>
 
   <Step title="계획 검토하기">
     생성된 crew 계획을 검토하세요. 여기에는 다음과 같은 항목이 포함될 수 있습니다:
@@ -146,21 +156,28 @@ LLM 연결과 기본 설정을 구성했다면 이제 Crew Studio 사용을 시
     - 금융 뉴스를 수집하는 Research Agent
     - 데이터를 해석하는 Analysis Agent
     - 투자 조언을 제공하는 Recommendations Agent
+
   </Step>
 
-  <Step title="승인 또는 수정">
-    계획을 승인하거나 필요하다면 변경을 요청하세요.
-  </Step>
+{" "}
+<Step title="승인 또는 수정">
+  계획을 승인하거나 필요하다면 변경을 요청하세요.
+</Step>
 
-  <Step title="다운로드 또는 배포">
-    사용자화를 위해 코드를 다운로드하거나 플랫폼에 직접 배포하세요.
-  </Step>
+{" "}
+<Step title="다운로드 또는 배포">
+  사용자화를 위해 코드를 다운로드하거나 플랫폼에 직접 배포하세요.
+</Step>
 
   <Step title="테스트 및 개선">
     샘플 입력으로 crew를 테스트하고 필요에 따라 개선하세요.
   </Step>
 </Steps>
 
-<Card title="도움이 필요하세요?" icon="headset" href="mailto:support@crewai.com">
-  Crew Studio 또는 기타 CrewAI AOP 기능 지원이 필요하다면 지원팀에 문의하세요.
+<Card
+  title="도움이 필요하세요?"
+  icon="headset"
+  href="mailto:support@crewai.com"
+>
+  Crew Studio 또는 기타 CrewAI AMP 기능 지원이 필요하다면 지원팀에 문의하세요.
 </Card>

docs/ko/enterprise/guides/gmail-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Use the Gmail Trigger to kick off your deployed crews when Gmail events happen in connected accounts, such as receiving a new email or messages matching a label/filter.
 
 <Tip>
-  Make sure Gmail is connected in Tools & Integrations and the trigger is enabled for your deployment.
+  Make sure Gmail is connected in Tools & Integrations and the trigger is
+  enabled for your deployment.
 </Tip>
 
 ## Enabling the Gmail Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Gmail** and switch the toggle to enable
 
 <Frame>
-  <img src="/images/enterprise/trigger-selected.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/trigger-selected.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Process new emails
@@ -62,13 +66,14 @@ CrewAI CLI를 사용하여 Gmail 트리거 통합을 로컬에서 테스트하
 crewai triggers list
 
 # 실제 payload로 Gmail 트리거 시뮬레이션
-crewai triggers run gmail/new_email
+crewai triggers run gmail/new_email_received
 ```
 
 `crewai triggers run` 명령은 완전한 Gmail payload로 크루를 실행하여 배포 전에 파싱 로직을 테스트할 수 있게 해줍니다.
 
 <Warning>
-  개발 중에는 `crewai triggers run gmail/new_email`을 사용하세요 (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
+  개발 중에는 `crewai triggers run gmail/new_email_received`을 사용하세요
+  (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
 </Warning>
 
 ## Monitoring Executions
@@ -76,13 +81,16 @@ crewai triggers run gmail/new_email
 Track history and performance of triggered runs:
 
 <Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+  <img
+    src="/images/enterprise/list-executions.png"
+    alt="List of executions triggered by automation"
+  />
 </Frame>
 
 ## Troubleshooting
 
 - Ensure Gmail is connected in Tools & Integrations
 - Verify the Gmail Trigger is enabled on the Triggers tab
-- `crewai triggers run gmail/new_email`로 로컬 테스트하여 정확한 payload 구조를 확인하세요
+- `crewai triggers run gmail/new_email_received`로 로컬 테스트하여 정확한 payload 구조를 확인하세요
 - Check the execution logs and confirm the payload is passed as `crewai_trigger_payload`
 - 주의: 트리거 실행을 시뮬레이션하려면 `crewai triggers run`을 사용하세요 (`crewai run`이 아님)

docs/ko/enterprise/guides/google-calendar-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Use the Google Calendar trigger to launch automations whenever calendar events change. Common use cases include briefing a team before a meeting, notifying stakeholders when a critical event is cancelled, or summarizing daily schedules.
 
 <Tip>
-  Make sure Google Calendar is connected in **Tools & Integrations** and enabled for the deployment you want to automate.
+  Make sure Google Calendar is connected in **Tools & Integrations** and enabled
+  for the deployment you want to automate.
 </Tip>
 
 ## Enabling the Google Calendar Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Google Calendar** and switch the toggle to enable
 
 <Frame>
-  <img src="/images/enterprise/calendar-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/calendar-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Summarize meeting details
@@ -54,7 +58,8 @@ crewai triggers run google_calendar/event_changed
 `crewai triggers run` 명령은 완전한 Calendar payload로 크루를 실행하여 배포 전에 파싱 로직을 테스트할 수 있게 해줍니다.
 
 <Warning>
-  개발 중에는 `crewai triggers run google_calendar/event_changed`를 사용하세요 (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
+  개발 중에는 `crewai triggers run google_calendar/event_changed`를 사용하세요
+  (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
 </Warning>
 
 ## Monitoring Executions
@@ -62,7 +67,10 @@ crewai triggers run google_calendar/event_changed
 The **Executions** list in the deployment dashboard tracks every triggered run and surfaces payload metadata, output summaries, and errors.
 
 <Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+  <img
+    src="/images/enterprise/list-executions.png"
+    alt="List of executions triggered by automation"
+  />
 </Frame>
 
 ## Troubleshooting

docs/ko/enterprise/guides/google-drive-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Trigger your automations when files are created, updated, or removed in Google Drive. Typical workflows include summarizing newly uploaded content, enforcing sharing policies, or notifying owners when critical files change.
 
 <Tip>
-  Connect Google Drive in **Tools & Integrations** and confirm the trigger is enabled for the automation you want to monitor.
+  Connect Google Drive in **Tools & Integrations** and confirm the trigger is
+  enabled for the automation you want to monitor.
 </Tip>
 
 ## Enabling the Google Drive Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Google Drive** and switch the toggle to enable
 
 <Frame>
-  <img src="/images/enterprise/gdrive-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/gdrive-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Summarize file activity
@@ -51,7 +55,8 @@ crewai triggers run google_drive/file_changed
 `crewai triggers run` 명령은 완전한 Drive payload로 크루를 실행하여 배포 전에 파싱 로직을 테스트할 수 있게 해줍니다.
 
 <Warning>
-  개발 중에는 `crewai triggers run google_drive/file_changed`를 사용하세요 (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
+  개발 중에는 `crewai triggers run google_drive/file_changed`를 사용하세요
+  (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
 </Warning>
 
 ## Monitoring Executions
@@ -59,7 +64,10 @@ crewai triggers run google_drive/file_changed
 Track history and performance of triggered runs with the **Executions** list in the deployment dashboard.
 
 <Frame>
-  <img src="/images/enterprise/list-executions.png" alt="List of executions triggered by automation" />
+  <img
+    src="/images/enterprise/list-executions.png"
+    alt="List of executions triggered by automation"
+  />
 </Frame>
 
 ## Troubleshooting

docs/ko/enterprise/guides/hubspot-trigger.mdx

@@ -9,44 +9,53 @@ mode: "wide"
 
 ## 사전 준비 사항
 
-- CrewAI AOP 계정
+- CrewAI AMP 계정
 - [HubSpot Workflows](https://knowledge.hubspot.com/workflows/create-workflows) 기능이 활성화된 HubSpot 계정
 
 ## 설정 단계
 
 <Steps>
-    <Step title="HubSpot 계정을 CrewAI AOP와 연결하기">
-        - `CrewAI AOP 계정 > 트리거`에 로그인합니다.
-        - 사용 가능한 트리거 목록에서 `HubSpot`을 선택합니다.
-        - CrewAI AOP와 연결하고자 하는 HubSpot 계정을 선택합니다.
-        - 화면에 나타나는 안내에 따라 CrewAI AOP가 HubSpot 계정에 접근하도록 승인합니다.
-        - HubSpot이 CrewAI AOP와 성공적으로 연결되면 확인 메시지가 표시됩니다.
-    </Step>
-    <Step title="HubSpot 워크플로우 생성하기">
-        - `HubSpot 계정 > 자동화 > 워크플로우 > 새 워크플로우`에 로그인합니다.
-        - 필요에 맞는 워크플로우 유형을 선택합니다 (예: 처음부터 시작).
-        - 워크플로우 빌더에서 더하기(+) 아이콘을 클릭하여 새로운 작업을 추가합니다.
-        - `통합 앱 > CrewAI > Crew 시작하기`를 선택합니다.
-        - 시작할 Crew를 선택합니다.
-        - `저장`을 클릭하여 워크플로우에 작업을 추가합니다.
-        <Frame>
-            <img src="/images/enterprise/hubspot-workflow-1.png" alt="HubSpot Workflow 1" />
-        </Frame>
-    </Step>
-    <Step title="Crew 결과를 다른 작업과 함께 사용하기">
-        - Crew 시작 단계 이후, 더하기(+) 아이콘을 클릭하여 새로운 작업을 추가합니다.
-        - 예를 들어, 내부 이메일 알림을 전송하려면 `커뮤니케이션 > 내부 이메일 알림 전송`을 선택합니다.
-        - 본문 필드에서 `데이터 삽입`을 클릭하고, `다음에서 속성 또는 작업 결과 보기 > 작업 결과 > Crew 결과`를 선택하여 이메일에 Crew 데이터를 포함합니다.
-            <Frame>
-                <img src="/images/enterprise/hubspot-workflow-2.png" alt="HubSpot Workflow 2" />
-            </Frame>
-        - 필요에 따라 추가 작업을 구성합니다.
-        - 모든 워크플로우 단계를 검토하여 올바르게 설정되었는지 확인합니다.
-        - 워크플로우를 활성화합니다.
-            <Frame>
-                <img src="/images/enterprise/hubspot-workflow-3.png" alt="HubSpot Workflow 3" />
-            </Frame>
-    </Step>
+  <Step title="HubSpot 계정을 CrewAI AOP와 연결하기">
+    - `CrewAI AMP 계정 > 트리거`에 로그인합니다. - 사용 가능한 트리거 목록에서
+    `HubSpot`을 선택합니다. - CrewAI AOP와 연결하고자 하는 HubSpot 계정을
+    선택합니다. - 화면에 나타나는 안내에 따라 CrewAI AOP가 HubSpot 계정에
+    접근하도록 승인합니다. - HubSpot이 CrewAI AOP와 성공적으로 연결되면 확인
+    메시지가 표시됩니다.
+  </Step>
+  <Step title="HubSpot 워크플로우 생성하기">
+    - `HubSpot 계정 > 자동화 > 워크플로우 > 새 워크플로우`에 로그인합니다. -
+    필요에 맞는 워크플로우 유형을 선택합니다 (예: 처음부터 시작). - 워크플로우
+    빌더에서 더하기(+) 아이콘을 클릭하여 새로운 작업을 추가합니다. - `통합 앱 >
+    CrewAI > Crew 시작하기`를 선택합니다. - 시작할 Crew를 선택합니다. - `저장`을
+    클릭하여 워크플로우에 작업을 추가합니다.
+    <Frame>
+      <img
+        src="/images/enterprise/hubspot-workflow-1.png"
+        alt="HubSpot Workflow 1"
+      />
+    </Frame>
+  </Step>
+  <Step title="Crew 결과를 다른 작업과 함께 사용하기">
+    - Crew 시작 단계 이후, 더하기(+) 아이콘을 클릭하여 새로운 작업을 추가합니다.
+    - 예를 들어, 내부 이메일 알림을 전송하려면 `커뮤니케이션 > 내부 이메일 알림
+    전송`을 선택합니다. - 본문 필드에서 `데이터 삽입`을 클릭하고, `다음에서 속성
+    또는 작업 결과 보기 > 작업 결과 > Crew 결과`를 선택하여 이메일에 Crew
+    데이터를 포함합니다.
+    <Frame>
+      <img
+        src="/images/enterprise/hubspot-workflow-2.png"
+        alt="HubSpot Workflow 2"
+      />
+    </Frame>
+    - 필요에 따라 추가 작업을 구성합니다. - 모든 워크플로우 단계를
+    검토하여 올바르게 설정되었는지 확인합니다. - 워크플로우를 활성화합니다.
+    <Frame>
+      <img
+        src="/images/enterprise/hubspot-workflow-3.png"
+        alt="HubSpot Workflow 3"
+      />
+    </Frame>
+  </Step>
 </Steps>
 
 사용 가능한 작업과 사용자 지정 옵션에 대한 자세한 정보는 [HubSpot 워크플로우 문서](https://knowledge.hubspot.com/workflows/create-workflows)를 참고하세요.

docs/ko/enterprise/guides/kickoff-crew.mdx

@@ -7,19 +7,17 @@ mode: "wide"
 
 ## 개요
 
-Crew를 CrewAI AOP 플랫폼에 배포한 후에는 웹 인터페이스 또는 API를 통해 실행을 시작할 수 있습니다. 이 가이드는 두 가지 접근 방식을 모두 다룹니다.
+Crew를 CrewAI AMP 플랫폼에 배포한 후에는 웹 인터페이스 또는 API를 통해 실행을 시작할 수 있습니다. 이 가이드는 두 가지 접근 방식을 모두 다룹니다.
 
 ## 방법 1: 웹 인터페이스 사용
 
 ### 1단계: 배포된 Crew로 이동하기
 
-1. [CrewAI AOP](https://app.crewai.com)에 로그인합니다.
+1. [CrewAI AMP](https://app.crewai.com)에 로그인합니다.
 2. 프로젝트 목록에서 crew 이름을 클릭합니다.
 3. crew의 상세 페이지로 이동합니다.
 
-<Frame>
-  ![Crew Dashboard](/images/enterprise/crew-dashboard.png)
-</Frame>
+<Frame>![Crew Dashboard](/images/enterprise/crew-dashboard.png)</Frame>
 
 ### 2단계: 실행 시작
 
@@ -31,9 +29,7 @@ crew의 상세 페이지에서 실행을 시작할 수 있는 두 가지 옵션
 2. JSON 에디터에서 crew에 필요한 입력 파라미터를 입력합니다.
 3. `Send Request` 버튼을 클릭합니다.
 
-<Frame>
-  ![Kickoff Endpoint](/images/enterprise/kickoff-endpoint.png)
-</Frame>
+<Frame>![Kickoff Endpoint](/images/enterprise/kickoff-endpoint.png)</Frame>
 
 #### 옵션 B: 시각적 인터페이스 사용
 
@@ -41,9 +37,7 @@ crew의 상세 페이지에서 실행을 시작할 수 있는 두 가지 옵션
 2. 양식 필드에 필요한 입력값을 입력합니다.
 3. `Run Crew` 버튼을 클릭합니다.
 
-<Frame>
-  ![Run Crew](/images/enterprise/run-crew.png)
-</Frame>
+<Frame>![Run Crew](/images/enterprise/run-crew.png)</Frame>
 
 ### 3단계: 실행 진행 상황 모니터링
 
@@ -52,9 +46,7 @@ crew의 상세 페이지에서 실행을 시작할 수 있는 두 가지 옵션
 1. `kickoff_id`가 포함된 응답을 받게 됩니다. - **이 ID를 복사하세요**
 2. 이 ID는 실행을 추적하는 데 필수적입니다
 
-<Frame>
-  ![작업 ID 복사](/images/enterprise/copy-task-id.png)
-</Frame>
+<Frame>![작업 ID 복사](/images/enterprise/copy-task-id.png)</Frame>
 
 ### 4단계: 실행 상태 확인
 
@@ -64,11 +56,10 @@ crew의 상세 페이지에서 실행을 시작할 수 있는 두 가지 옵션
 2. 지정된 필드에 `kickoff_id`를 붙여넣으세요
 3. "Get Status" 버튼을 클릭하세요
 
-<Frame>
-  ![Get Status](/images/enterprise/get-status.png)
-</Frame>
+<Frame>![Get Status](/images/enterprise/get-status.png)</Frame>
 
 상태 응답에는 다음이 표시됩니다:
+
 - 현재 실행 상태(`running`, `completed` 등)
 - 진행 중인 작업에 대한 세부 정보
 - 지금까지 생성된 모든 출력
@@ -83,7 +74,7 @@ crew의 상세 페이지에서 실행을 시작할 수 있는 두 가지 옵션
 
 ## 방법 2: API 사용
 
-CrewAI AOP REST API를 사용하여 프로그래밍 방식으로 crews를 시작할 수도 있습니다.
+CrewAI AMP REST API를 사용하여 프로그래밍 방식으로 crews를 시작할 수도 있습니다.
 
 ### 인증
 
@@ -122,7 +113,7 @@ curl -X GET \
 응답은 예를 들어 다음과 같이 필수 입력 파라미터 배열을 포함한 JSON 객체로 반환됩니다:
 
 ```json
-{"inputs":["topic","current_year"]}
+{ "inputs": ["topic", "current_year"] }
 ```
 
 이 예시에서는 해당 crew에서 두 개의 입력값인 `topic`과 `current_year`를 필요로 함을 보여줍니다.
@@ -142,7 +133,7 @@ curl -X POST \
 응답에는 추적에 필요한 `kickoff_id`가 포함됩니다:
 
 ```json
-{"kickoff_id":"abcd1234-5678-90ef-ghij-klmnopqrstuv"}
+{ "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv" }
 ```
 
 ### 3단계: 실행 상태 확인
@@ -181,6 +172,11 @@ curl -X GET \
 2. "Traces" 탭에서 단계별 실행 세부 정보를 검토하세요
 3. 트레이스 세부 정보에서 LLM 응답과 도구 사용 내역을 확인하세요
 
-<Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
-  실행 문제 또는 엔터프라이즈 플랫폼 관련 질문이 있으신 경우, 지원팀에 문의하세요.
+<Card
+  title="도움이 필요하신가요?"
+  icon="headset"
+  href="mailto:support@crewai.com"
+>
+  실행 문제 또는 엔터프라이즈 플랫폼 관련 질문이 있으신 경우, 지원팀에
+  문의하세요.
 </Card>

docs/ko/enterprise/guides/microsoft-teams-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Use the Microsoft Teams trigger to start automations whenever a new chat is created. Common patterns include summarizing inbound requests, routing urgent messages to support teams, or creating follow-up tasks in other systems.
 
 <Tip>
-  Confirm Microsoft Teams is connected under **Tools & Integrations** and enabled in the **Triggers** tab for your deployment.
+  Confirm Microsoft Teams is connected under **Tools & Integrations** and
+  enabled in the **Triggers** tab for your deployment.
 </Tip>
 
 ## Enabling the Microsoft Teams Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Microsoft Teams** and switch the toggle to enable
 
 <Frame caption="Microsoft Teams trigger connection">
-  <img src="/images/enterprise/msteams-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/msteams-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Summarize a new chat thread
@@ -52,7 +56,9 @@ crewai triggers run microsoft_teams/teams_message_created
 `crewai triggers run` 명령은 완전한 Teams payload로 크루를 실행하여 배포 전에 파싱 로직을 테스트할 수 있게 해줍니다.
 
 <Warning>
-  개발 중에는 `crewai triggers run microsoft_teams/teams_message_created`를 사용하세요 (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
+  개발 중에는 `crewai triggers run microsoft_teams/teams_message_created`를
+  사용하세요 (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를
+  받습니다.
 </Warning>
 
 ## Troubleshooting

docs/ko/enterprise/guides/onedrive-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Start automations when files change inside OneDrive. You can generate audit summaries, notify security teams about external sharing, or update downstream line-of-business systems with new document metadata.
 
 <Tip>
-  Connect OneDrive in **Tools & Integrations** and toggle the trigger on for your deployment.
+  Connect OneDrive in **Tools & Integrations** and toggle the trigger on for
+  your deployment.
 </Tip>
 
 ## Enabling the OneDrive Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **OneDrive** and switch the toggle to enable
 
 <Frame caption="Microsoft OneDrive trigger connection">
-  <img src="/images/enterprise/onedrive-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/onedrive-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Audit file permissions
@@ -51,7 +55,8 @@ crewai triggers run microsoft_onedrive/file_changed
 `crewai triggers run` 명령은 완전한 OneDrive payload로 크루를 실행하여 배포 전에 파싱 로직을 테스트할 수 있게 해줍니다.
 
 <Warning>
-  개발 중에는 `crewai triggers run microsoft_onedrive/file_changed`를 사용하세요 (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
+  개발 중에는 `crewai triggers run microsoft_onedrive/file_changed`를 사용하세요
+  (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
 </Warning>
 
 ## Troubleshooting

docs/ko/enterprise/guides/outlook-trigger.mdx

@@ -10,17 +10,21 @@ mode: "wide"
 Automate responses when Outlook delivers a new message or when an event is removed from the calendar. Teams commonly route escalations, file tickets, or alert attendees of cancellations.
 
 <Tip>
-  Connect Outlook in **Tools & Integrations** and ensure the trigger is enabled for your deployment.
+  Connect Outlook in **Tools & Integrations** and ensure the trigger is enabled
+  for your deployment.
 </Tip>
 
 ## Enabling the Outlook Trigger
 
-1. Open your deployment in CrewAI AOP
+1. Open your deployment in CrewAI AMP
 2. Go to the **Triggers** tab
 3. Locate **Outlook** and switch the toggle to enable
 
 <Frame caption="Microsoft Outlook trigger connection">
-  <img src="/images/enterprise/outlook-trigger.png" alt="Enable or disable triggers with toggle" />
+  <img
+    src="/images/enterprise/outlook-trigger.png"
+    alt="Enable or disable triggers with toggle"
+  />
 </Frame>
 
 ## Example: Summarize a new email
@@ -51,7 +55,9 @@ crewai triggers run microsoft_outlook/email_received
 `crewai triggers run` 명령은 완전한 Outlook payload로 크루를 실행하여 배포 전에 파싱 로직을 테스트할 수 있게 해줍니다.
 
 <Warning>
-  개발 중에는 `crewai triggers run microsoft_outlook/email_received`를 사용하세요 (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를 받습니다.
+  개발 중에는 `crewai triggers run microsoft_outlook/email_received`를
+  사용하세요 (`crewai run`이 아님). 배포 후에는 크루가 자동으로 트리거 payload를
+  받습니다.
 </Warning>
 
 ## Troubleshooting

docs/ko/enterprise/guides/react-component-export.mdx

@@ -1,11 +1,11 @@
 ---
 title: "React 컴포넌트 내보내기"
-description: "CrewAI AOP React 컴포넌트를 애플리케이션에 내보내고 통합하는 방법을 알아보세요"
+description: "CrewAI AMP React 컴포넌트를 애플리케이션에 내보내고 통합하는 방법을 알아보세요"
 icon: "react"
 mode: "wide"
 ---
 
-이 가이드는 CrewAI AOP crew를 React 컴포넌트로 내보내고 이를 여러분의 애플리케이션에 통합하는 방법을 설명합니다.
+이 가이드는 CrewAI AMP crew를 React 컴포넌트로 내보내고 이를 여러분의 애플리케이션에 통합하는 방법을 설명합니다.
 
 ## React 컴포넌트 내보내기
 
@@ -17,6 +17,7 @@ mode: "wide"
             <img src="/images/enterprise/export-react-component.png" alt="React 컴포넌트 내보내기" />
         </Frame>
     </Step>
+
 </Steps>
 
 ## 리액트 환경 설정
@@ -83,6 +84,7 @@ mode: "wide"
             ```
         - 개발 서버가 시작되며, 기본 웹 브라우저가 자동으로 http://localhost:3000 을 열고 리액트 앱이 실행되는 것을 확인할 수 있습니다.
     </Step>
+
 </Steps>
 
 ## 커스터마이징
@@ -90,10 +92,16 @@ mode: "wide"
 그런 다음 `CrewLead.jsx`를 커스터마이즈하여 색상, 제목 등을 추가할 수 있습니다.
 
 <Frame>
-    <img src="/images/enterprise/customise-react-component.png" alt="React 컴포넌트 커스터마이즈" />
+  <img
+    src="/images/enterprise/customise-react-component.png"
+    alt="React 컴포넌트 커스터마이즈"
+  />
 </Frame>
 <Frame>
-    <img src="/images/enterprise/customise-react-component-2.png" alt="React 컴포넌트 커스터마이즈" />
+  <img
+    src="/images/enterprise/customise-react-component-2.png"
+    alt="React 컴포넌트 커스터마이즈"
+  />
 </Frame>
 
 ## 다음 단계

docs/ko/enterprise/guides/salesforce-trigger.mdx

@@ -31,7 +31,7 @@ Salesforce는 기업이 영업, 서비스, 마케팅 운영을 효율화할 수
 
 Salesforce 트리거를 설정하려면:
 
-1. **지원팀 문의**: Salesforce 트리거 설정을 위해 CrewAI AOP 지원팀에 연락하세요.
+1. **지원팀 문의**: Salesforce 트리거 설정을 위해 CrewAI AMP 지원팀에 연락하세요.
 2. **요구 사항 검토**: 필요한 Salesforce 권한과 API 액세스 권한이 있는지 확인하세요.
 3. **연결 구성**: 지원팀과 협력하여 CrewAI와 귀하의 Salesforce 인스턴스 간의 연결을 설정하세요.
 4. **트리거 테스트**: 트리거가 귀하의 특정 사용 사례에 맞게 올바르게 작동하는지 확인하세요.
@@ -47,4 +47,4 @@ Salesforce 트리거를 설정하려면:
 
 ## 다음 단계
 
-자세한 설정 지침 및 고급 구성 옵션에 대해서는 CrewAI AOP 지원팀에 문의해 주시기 바랍니다. 지원팀은 귀하의 특정 Salesforce 환경과 비즈니스 요구에 맞는 맞춤형 안내를 제공해 드릴 수 있습니다.
+자세한 설정 지침 및 고급 구성 옵션에 대해서는 CrewAI AMP 지원팀에 문의해 주시기 바랍니다. 지원팀은 귀하의 특정 Salesforce 환경과 비즈니스 요구에 맞는 맞춤형 안내를 제공해 드릴 수 있습니다.

docs/ko/enterprise/guides/team-management.mdx

@@ -1,40 +1,38 @@
 ---
 title: "팀 관리"
-description: "CrewAI AOP 조직에서 팀원을 초대하고 관리하는 방법을 알아보세요"
+description: "CrewAI AMP 조직에서 팀원을 초대하고 관리하는 방법을 알아보세요"
 icon: "users"
 mode: "wide"
 ---
 
-CrewAI AOP 계정의 관리자라면 새로운 팀원을 조직에 쉽게 초대할 수 있습니다. 이 안내서는 단계별로 프로세스를 안내합니다.
+CrewAI AMP 계정의 관리자라면 새로운 팀원을 조직에 쉽게 초대할 수 있습니다. 이 안내서는 단계별로 프로세스를 안내합니다.
 
 ## 팀 멤버 초대하기
 
 <Steps>
-    <Step title="설정 페이지 접속">
-        - CrewAI AOP 계정에 로그인합니다
-        - 대시보드 오른쪽 상단에 있는 기어 아이콘(⚙️)을 찾습니다
-        - 기어 아이콘을 클릭하여 **설정** 페이지에 접속합니다:
-            <Frame>
-                <img src="/images/enterprise/settings-page.png" alt="Settings Page" />
-            </Frame>
-    </Step>
-    <Step title="멤버 섹션으로 이동">
-        - 설정 페이지에서 `Members` 탭이 보입니다
-        - `Members` 탭을 클릭하여 **멤버** 페이지에 접속합니다:
-            <Frame>
-                <img src="/images/enterprise/members-tab.png" alt="Members Tab" />
-            </Frame>
-    </Step>
-    <Step title="새 멤버 초대">
-        - 멤버 섹션에서 현재 멤버 목록(본인 포함)을 확인할 수 있습니다
-        - `Email` 입력 필드를 찾습니다
-        - 초대하고자 하는 사람의 이메일 주소를 입력합니다
-        - `Invite` 버튼을 클릭하여 초대장을 보냅니다
-    </Step>
-    <Step title="필요에 따라 반복">
-        - 이 과정을 반복하여 여러 팀 멤버를 초대할 수 있습니다
-        - 초대한 각 멤버는 조직에 가입할 수 있는 이메일 초대장을 받게 됩니다
-    </Step>
+  <Step title="설정 페이지 접속">
+    - CrewAI AMP 계정에 로그인합니다 - 대시보드 오른쪽 상단에 있는 기어
+    아이콘(⚙️)을 찾습니다 - 기어 아이콘을 클릭하여 **설정** 페이지에 접속합니다:
+    <Frame>
+      <img src="/images/enterprise/settings-page.png" alt="Settings Page" />
+    </Frame>
+  </Step>
+  <Step title="멤버 섹션으로 이동">
+    - 설정 페이지에서 `Members` 탭이 보입니다 - `Members` 탭을 클릭하여 **멤버**
+    페이지에 접속합니다:
+    <Frame>
+      <img src="/images/enterprise/members-tab.png" alt="Members Tab" />
+    </Frame>
+  </Step>
+  <Step title="새 멤버 초대">
+    - 멤버 섹션에서 현재 멤버 목록(본인 포함)을 확인할 수 있습니다 - `Email`
+    입력 필드를 찾습니다 - 초대하고자 하는 사람의 이메일 주소를 입력합니다 -
+    `Invite` 버튼을 클릭하여 초대장을 보냅니다
+  </Step>
+  <Step title="필요에 따라 반복">
+    - 이 과정을 반복하여 여러 팀 멤버를 초대할 수 있습니다 - 초대한 각 멤버는
+    조직에 가입할 수 있는 이메일 초대장을 받게 됩니다
+  </Step>
 </Steps>
 
 ## 역할 추가하기
@@ -42,40 +40,42 @@ CrewAI AOP 계정의 관리자라면 새로운 팀원을 조직에 쉽게 초대
 플랫폼의 다양한 부분에 대한 접근 권한을 제어하기 위해 팀원들에게 역할을 추가할 수 있습니다.
 
 <Steps>
-    <Step title="설정 페이지 접근">
-        - CrewAI AOP 계정에 로그인하세요
-        - 대시보드 오른쪽 상단에서 기어 아이콘(⚙️)을 찾으세요
-        - 기어 아이콘을 클릭하여 **설정** 페이지에 접근하세요:
-            <Frame>
-                <img src="/images/enterprise/settings-page.png" alt="설정 페이지" />
-            </Frame>
-    </Step>
-    <Step title="멤버 섹션으로 이동">
-        - 설정 페이지에서 `Roles` 탭을 확인할 수 있습니다
-        - `Roles` 탭을 클릭하여 **Roles** 페이지로 이동하세요.
-            <Frame>
-                <img src="/images/enterprise/roles-tab.png" alt="Roles 탭" />
-            </Frame>
-        - 새로운 역할을 추가하려면 `Add Role` 버튼을 클릭하세요.
-        - 역할의 세부 정보와 권한을 입력한 후 `Create Role` 버튼을 클릭하여 역할을 생성하세요.
-            <Frame>
-                <img src="/images/enterprise/add-role-modal.png" alt="Add Role 모달" />
-            </Frame>
-    </Step>
-    <Step title="멤버에게 역할 추가하기">
-        - 멤버 섹션에서 현재 멤버(본인 포함) 목록을 확인할 수 있습니다
-           <Frame>
-                <img src="/images/enterprise/member-accepted-invitation.png" alt="멤버 초대 수락 완료" />
-           </Frame>
-        - 멤버가 초대를 수락하면 역할을 추가할 수 있습니다.
-        - 다시 `Roles` 탭으로 이동하세요
-        - 역할을 추가할 멤버로 이동한 후 `Role` 열에서 드롭다운을 클릭하세요
-        - 멤버에게 추가할 역할을 선택하세요
-        - `Update` 버튼을 클릭하여 역할을 저장하세요
-            <Frame>
-                <img src="/images/enterprise/assign-role.png" alt="멤버에 역할 추가" />
-            </Frame>
-    </Step>
+  <Step title="설정 페이지 접근">
+    - CrewAI AMP 계정에 로그인하세요 - 대시보드 오른쪽 상단에서 기어
+    아이콘(⚙️)을 찾으세요 - 기어 아이콘을 클릭하여 **설정** 페이지에 접근하세요:
+    <Frame>
+      <img src="/images/enterprise/settings-page.png" alt="설정 페이지" />
+    </Frame>
+  </Step>
+  <Step title="멤버 섹션으로 이동">
+    - 설정 페이지에서 `Roles` 탭을 확인할 수 있습니다 - `Roles` 탭을 클릭하여
+    **Roles** 페이지로 이동하세요.
+    <Frame>
+      <img src="/images/enterprise/roles-tab.png" alt="Roles 탭" />
+    </Frame>
+    - 새로운 역할을 추가하려면 `Add Role` 버튼을 클릭하세요. - 역할의
+    세부 정보와 권한을 입력한 후 `Create Role` 버튼을 클릭하여 역할을
+    생성하세요.
+    <Frame>
+      <img src="/images/enterprise/add-role-modal.png" alt="Add Role 모달" />
+    </Frame>
+  </Step>
+  <Step title="멤버에게 역할 추가하기">
+    - 멤버 섹션에서 현재 멤버(본인 포함) 목록을 확인할 수 있습니다
+    <Frame>
+      <img
+        src="/images/enterprise/member-accepted-invitation.png"
+        alt="멤버 초대 수락 완료"
+      />
+    </Frame>
+    - 멤버가 초대를 수락하면 역할을 추가할 수 있습니다. - 다시 `Roles`
+    탭으로 이동하세요 - 역할을 추가할 멤버로 이동한 후 `Role` 열에서 드롭다운을
+    클릭하세요 - 멤버에게 추가할 역할을 선택하세요 - `Update` 버튼을 클릭하여
+    역할을 저장하세요
+    <Frame>
+      <img src="/images/enterprise/assign-role.png" alt="멤버에 역할 추가" />
+    </Frame>
+  </Step>
 </Steps>
 
 ## 중요 참고 사항
@@ -85,4 +85,4 @@ CrewAI AOP 계정의 관리자라면 새로운 팀원을 조직에 쉽게 초대
 - **초대 수락**: 초대된 멤버는 조직에 가입하기 위해 초대를 수락해야 합니다
 - **이메일 알림**: 팀 멤버에게 초대 이메일(스팸 폴더 포함)을 확인하도록 안내할 수 있습니다
 
-이 단계들을 따르면 팀을 손쉽게 확장하고 CrewAI AOP 조직 내에서 더욱 효과적으로 협업할 수 있습니다.
+이 단계들을 따르면 팀을 손쉽게 확장하고 CrewAI AMP 조직 내에서 더욱 효과적으로 협업할 수 있습니다.

docs/ko/enterprise/guides/tool-repository.mdx

@@ -20,11 +20,11 @@ Tool Repository는 CrewAI 도구를 위한 패키지 관리자입니다. 사용
 
 Tool Repository를 사용하기 전에 다음이 준비되어 있어야 합니다:
 
-- [CrewAI AOP](https://app.crewai.com) 계정
+- [CrewAI AMP](https://app.crewai.com) 계정
 - [CrewAI CLI](/ko/concepts/cli#cli) 설치됨
 - uv>=0.5.0 이 설치되어 있어야 합니다. [업그레이드 방법](https://docs.astral.sh/uv/getting-started/installation/#upgrading-uv)을 참고하세요.
 - [Git](https://git-scm.com) 설치 및 구성 완료
-- CrewAI AOP 조직에서 도구를 게시하거나 설치할 수 있는 액세스 권한
+- CrewAI AMP 조직에서 도구를 게시하거나 설치할 수 있는 액세스 권한
 
 ## 도구 설치
 
@@ -85,13 +85,13 @@ crewai tool publish
 
 도구를 삭제하려면:
 
-1. [CrewAI AOP](https://app.crewai.com)로 이동합니다.
+1. [CrewAI AMP](https://app.crewai.com)로 이동합니다.
 2. **Tools**로 이동합니다.
 3. 도구를 선택합니다.
 4. **Delete**를 클릭합니다.
 
 <Warning>
-삭제는 영구적입니다. 삭제된 도구는 복구하거나 다시 설치할 수 없습니다.
+  삭제는 영구적입니다. 삭제된 도구는 복구하거나 다시 설치할 수 없습니다.
 </Warning>
 
 ## 보안 점검
@@ -100,8 +100,12 @@ crewai tool publish
 
 도구의 보안 점검 상태는 다음에서 확인할 수 있습니다:
 
-`CrewAI AOP > Tools > Your Tool > Versions`
+`CrewAI AMP > Tools > Your Tool > Versions`
 
-<Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
+<Card
+  title="도움이 필요하신가요?"
+  icon="headset"
+  href="mailto:support@crewai.com"
+>
   API 통합 또는 문제 해결에 대한 지원이 필요하시면 지원팀에 문의해 주세요.
 </Card>

docs/ko/enterprise/guides/update-crew.mdx

@@ -6,8 +6,9 @@ mode: "wide"
 ---
 
 <Note>
-CrewAI AOP에 crew를 배포한 후, 코드, 보안 설정 또는 구성을 업데이트해야 할 수 있습니다.
-이 가이드는 이러한 일반적인 업데이트 작업을 수행하는 방법을 설명합니다.
+  CrewAI AOP에 crew를 배포한 후, 코드, 보안 설정 또는 구성을 업데이트해야 할 수
+  있습니다. 이 가이드는 이러한 일반적인 업데이트 작업을 수행하는 방법을
+  설명합니다.
 </Note>
 
 ## 왜 Crew를 업데이트해야 하나요?
@@ -15,6 +16,7 @@ CrewAI AOP에 crew를 배포한 후, 코드, 보안 설정 또는 구성을 업
 CrewAI는 기본적으로 GitHub 업데이트를 자동으로 반영하지 않으므로, 배포 시 `Auto-update` 옵션을 선택하지 않았다면 수동으로 업데이트를 트리거해야 합니다.
 
 Crew 배포를 업데이트하고 싶은 이유는 여러 가지가 있을 수 있습니다:
+
 - GitHub에 푸시한 최신 커밋으로 코드를 업데이트하고 싶은 경우
 - 보안상의 이유로 bearer 토큰을 재설정하고 싶은 경우
 - 환경 변수를 업데이트하고 싶은 경우
@@ -23,12 +25,10 @@ Crew 배포를 업데이트하고 싶은 이유는 여러 가지가 있을 수
 
 GitHub 저장소에 새로운 커밋을 푸시한 후 배포를 업데이트하려면 다음 단계를 따르세요:
 
-1. CrewAI AOP 플랫폼에서 자신의 crew로 이동하세요.
+1. CrewAI AMP 플랫폼에서 자신의 crew로 이동하세요.
 2. crew 상세 페이지에서 `Re-deploy` 버튼을 클릭하세요.
 
-<Frame>
-  ![Re-deploy Button](/images/enterprise/redeploy-button.png)
-</Frame>
+<Frame>![Re-deploy Button](/images/enterprise/redeploy-button.png)</Frame>
 
 이 작업을 수행하면 진행률 표시줄을 통해 추적할 수 있는 업데이트가 트리거됩니다. 시스템은 저장소에서 최신 코드를 가져와서 배포를 다시 빌드합니다.
 
@@ -36,16 +36,15 @@ GitHub 저장소에 새로운 커밋을 푸시한 후 배포를 업데이트하
 
 현재 토큰이 유출되었을 가능성이 있다고 의심되는 경우 등, 새 베어러 토큰을 생성해야 한다면 다음 단계를 따르세요:
 
-1. CrewAI AOP 플랫폼에서 해당 crew로 이동하세요.
+1. CrewAI AMP 플랫폼에서 해당 crew로 이동하세요.
 2. `Bearer Token` 섹션을 찾으세요.
 3. 현재 토큰 옆에 있는 `Reset` 버튼을 클릭하세요.
 
-<Frame>
-  ![Reset Token](/images/enterprise/reset-token.png)
-</Frame>
+<Frame>![Reset Token](/images/enterprise/reset-token.png)</Frame>
 
 <Warning>
-베어러 토큰을 재설정하면 이전 토큰은 즉시 사용할 수 없게 됩니다. 이전 토큰을 사용하고 있는 모든 애플리케이션이나 스크립트에서 토큰을 반드시 업데이트하세요.
+  베어러 토큰을 재설정하면 이전 토큰은 즉시 사용할 수 없게 됩니다. 이전 토큰을
+  사용하고 있는 모든 애플리케이션이나 스크립트에서 토큰을 반드시 업데이트하세요.
 </Warning>
 
 ## 3. 환경 변수 업데이트하기
@@ -54,22 +53,19 @@ crew의 환경 변수를 업데이트하려면 다음 단계를 따르세요:
 
 1. 먼저 crew 이름을 클릭하여 배포 페이지에 접속합니다.
 
-<Frame>
-  ![환경 변수 버튼](/images/enterprise/env-vars-button.png)
-</Frame>
+<Frame>![환경 변수 버튼](/images/enterprise/env-vars-button.png)</Frame>
 
 2. `Environment Variables` 섹션을 찾습니다 (`Settings` 아이콘을 클릭해야 접근할 수 있습니다)
 3. 제공된 필드에서 기존 변수를 수정하거나 새 변수를 추가합니다
 4. 수정한 각 변수 옆의 `Update` 버튼을 클릭합니다
 
-<Frame>
-  ![환경 변수 업데이트](/images/enterprise/update-env-vars.png)
-</Frame>
+<Frame>![환경 변수 업데이트](/images/enterprise/update-env-vars.png)</Frame>
 
 5. 마지막으로, 변경 사항을 적용하려면 페이지 하단의 `Update Deployment` 버튼을 클릭합니다
 
 <Note>
-환경 변수를 업데이트하면 새로운 배포가 트리거되지만, 이는 환경 설정만 업데이트하며 코드 자체는 변경되지 않습니다.
+  환경 변수를 업데이트하면 새로운 배포가 트리거되지만, 이는 환경 설정만
+  업데이트하며 코드 자체는 변경되지 않습니다.
 </Note>
 
 ## 업데이트 후
@@ -81,9 +77,15 @@ crew의 환경 변수를 업데이트하려면 다음 단계를 따르세요:
 3. 완료되면 변경 사항이 예상대로 작동하는지 crew를 테스트합니다
 
 <Tip>
-업데이트 후 문제가 발생하면 플랫폼에서 배포 로그를 확인하거나 지원팀에 문의하여 도움을 받을 수 있습니다.
+  업데이트 후 문제가 발생하면 플랫폼에서 배포 로그를 확인하거나 지원팀에
+  문의하여 도움을 받을 수 있습니다.
 </Tip>
 
-<Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
-  crew 업데이트나 배포 문제 해결에 대해 지원이 필요하시면 지원팀에 문의해 주세요.
+<Card
+  title="도움이 필요하신가요?"
+  icon="headset"
+  href="mailto:support@crewai.com"
+>
+  crew 업데이트나 배포 문제 해결에 대해 지원이 필요하시면 지원팀에 문의해
+  주세요.
 </Card>