Merge branch 'main' into joaomdmoura/fix-tool-execution

adding reference and explaination for package registry

Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>

.env.test

@@ -21,7 +21,6 @@ OPENROUTER_API_KEY=fake-openrouter-key
 AWS_ACCESS_KEY_ID=fake-aws-access-key
 AWS_SECRET_ACCESS_KEY=fake-aws-secret-key
 AWS_DEFAULT_REGION=us-east-1
-AWS_REGION_NAME=us-east-1
 
 # -----------------------------------------------------------------------------
 # Azure OpenAI Configuration

.github/codeql/codeql-config.yml

@@ -14,13 +14,18 @@ paths-ignore:
   - "lib/crewai/src/crewai/experimental/a2a/**"
 
 paths:
+  # Include GitHub Actions workflows/composite actions for CodeQL actions analysis
+  - ".github/workflows/**"
+  - ".github/actions/**"
   # Include all Python source code from workspace packages
   - "lib/crewai/src/**"
   - "lib/crewai-tools/src/**"
+  - "lib/crewai-files/src/**"
   - "lib/devtools/src/**"
   # Include tests (but exclude cassettes via paths-ignore)
   - "lib/crewai/tests/**"
   - "lib/crewai-tools/tests/**"
+  - "lib/crewai-files/tests/**"
   - "lib/devtools/tests/**"
 
 # Configure specific queries or packs if needed

.github/workflows/codeql.yml

@@ -69,7 +69,7 @@ jobs:
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
-      uses: github/codeql-action/init@v3
+      uses: github/codeql-action/init@v4
       with:
         languages: ${{ matrix.language }}
         build-mode: ${{ matrix.build-mode }}
@@ -98,6 +98,6 @@ jobs:
         exit 1
 
     - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v3
+      uses: github/codeql-action/analyze@v4
       with:
         category: "/language:${{matrix.language}}"

.github/workflows/notify-downstream.yml

@@ -1,33 +0,0 @@
-name: Notify Downstream
-
-on:
-  push:
-    branches:
-      - main
-
-permissions:
-  contents: read
-
-jobs:
-  notify-downstream:
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Generate GitHub App token
-        id: app-token
-        uses: tibdex/github-app-token@v2
-        with:
-          app_id: ${{ secrets.OSS_SYNC_APP_ID }}
-          private_key: ${{ secrets.OSS_SYNC_APP_PRIVATE_KEY }}
-
-      - name: Notify Repo B
-        uses: peter-evans/repository-dispatch@v3
-        with:
-          token: ${{ steps.app-token.outputs.token }}
-          repository: ${{ secrets.OSS_SYNC_DOWNSTREAM_REPO }}
-          event-type: upstream-commit
-          client-payload: |
-            {
-              "commit_sha": "${{ github.sha }}"
-            }
-

.gitignore

@@ -27,3 +27,6 @@ conceptual_plan.md
 build_image
 chromadb-*.lock
 .claude
+.crewai/memory
+blogs/*
+secrets/*

conftest.py

@@ -11,7 +11,11 @@ from typing import Any
 from dotenv import load_dotenv
 import pytest
 from vcr.request import Request  # type: ignore[import-untyped]
-import vcr.stubs.httpx_stubs as httpx_stubs  # type: ignore[import-untyped]
+
+try:
+    import vcr.stubs.httpx_stubs as httpx_stubs  # type: ignore[import-untyped]
+except ModuleNotFoundError:
+    import vcr.stubs.httpcore_stubs as httpx_stubs  # type: ignore[import-untyped]
 
 
 env_test_path = Path(__file__).parent / ".env.test"

docs/docs.json

@@ -111,6 +111,13 @@
                       "en/guides/flows/mastering-flow-state"
                     ]
                   },
+                  {
+                    "group": "Coding Tools",
+                    "icon": "terminal",
+                    "pages": [
+                      "en/guides/coding-tools/agents-md"
+                    ]
+                  },
                   {
                     "group": "Advanced",
                     "icon": "gear",
@@ -433,6 +440,7 @@
                   "en/enterprise/guides/build-crew",
                   "en/enterprise/guides/prepare-for-deployment",
                   "en/enterprise/guides/deploy-to-amp",
+                  "en/enterprise/guides/private-package-registry",
                   "en/enterprise/guides/kickoff-crew",
                   "en/enterprise/guides/update-crew",
                   "en/enterprise/guides/enable-crew-studio",
@@ -871,6 +879,7 @@
                   "pt-BR/enterprise/guides/build-crew",
                   "pt-BR/enterprise/guides/prepare-for-deployment",
                   "pt-BR/enterprise/guides/deploy-to-amp",
+                  "pt-BR/enterprise/guides/private-package-registry",
                   "pt-BR/enterprise/guides/kickoff-crew",
                   "pt-BR/enterprise/guides/update-crew",
                   "pt-BR/enterprise/guides/enable-crew-studio",
@@ -1336,6 +1345,7 @@
                   "ko/enterprise/guides/build-crew",
                   "ko/enterprise/guides/prepare-for-deployment",
                   "ko/enterprise/guides/deploy-to-amp",
+                  "ko/enterprise/guides/private-package-registry",
                   "ko/enterprise/guides/kickoff-crew",
                   "ko/enterprise/guides/update-crew",
                   "ko/enterprise/guides/enable-crew-studio",
@@ -1571,4 +1581,4 @@
       "reddit": "https://www.reddit.com/r/crewAIInc/"
     }
   }
-}
+}

docs/en/concepts/flows.mdx

@@ -975,6 +975,79 @@ result = streaming.result
 
 Learn more about streaming in the [Streaming Flow Execution](/en/learn/streaming-flow-execution) guide.
 
+## Memory in Flows
+
+Every Flow automatically has access to CrewAI's unified [Memory](/concepts/memory) system. You can store, recall, and extract memories directly inside any flow method using three built-in convenience methods.
+
+### Built-in Methods
+
+| Method | Description |
+| :--- | :--- |
+| `self.remember(content, **kwargs)` | Store content in memory. Accepts optional `scope`, `categories`, `metadata`, `importance`. |
+| `self.recall(query, **kwargs)` | Retrieve relevant memories. Accepts optional `scope`, `categories`, `limit`, `depth`. |
+| `self.extract_memories(content)` | Break raw text into discrete, self-contained memory statements. |
+
+A default `Memory()` instance is created automatically when the Flow initializes. You can also pass a custom one:
+
+```python
+from crewai.flow.flow import Flow
+from crewai import Memory
+
+custom_memory = Memory(
+    recency_weight=0.5,
+    recency_half_life_days=7,
+    embedder={"provider": "ollama", "config": {"model_name": "mxbai-embed-large"}},
+)
+
+flow = MyFlow(memory=custom_memory)
+```
+
+### Example: Research and Analyze Flow
+
+```python
+from crewai.flow.flow import Flow, listen, start
+
+
+class ResearchAnalysisFlow(Flow):
+    @start()
+    def gather_data(self):
+        # Simulate research findings
+        findings = (
+            "PostgreSQL handles 10k concurrent connections with connection pooling. "
+            "MySQL caps at around 5k. MongoDB scales horizontally but adds complexity."
+        )
+
+        # Extract atomic facts and remember each one
+        memories = self.extract_memories(findings)
+        for mem in memories:
+            self.remember(mem, scope="/research/databases")
+
+        return findings
+
+    @listen(gather_data)
+    def analyze(self, raw_findings):
+        # Recall relevant past research (from this run or previous runs)
+        past = self.recall("database performance and scaling", limit=10, depth="shallow")
+
+        context_lines = [f"- {m.record.content}" for m in past]
+        context = "\n".join(context_lines) if context_lines else "No prior context."
+
+        return {
+            "new_findings": raw_findings,
+            "prior_context": context,
+            "total_memories": len(past),
+        }
+
+
+flow = ResearchAnalysisFlow()
+result = flow.kickoff()
+print(result)
+```
+
+Because memory persists across runs (backed by LanceDB on disk), the `analyze` step will recall findings from previous executions too -- enabling flows that learn and accumulate knowledge over time.
+
+See the [Memory documentation](/concepts/memory) for details on scopes, slices, composite scoring, embedder configuration, and more.
+
 ### Using the CLI
 
 Starting from version 0.103.0, you can run flows using the `crewai run` command:

docs/en/concepts/llms.mdx

@@ -470,7 +470,7 @@ In this section, you'll find detailed examples that help you select, configure,
       To get an Express mode API key:
       - New Google Cloud users: Get an [express mode API key](https://cloud.google.com/vertex-ai/generative-ai/docs/start/quickstart?usertype=apikey)
       - Existing Google Cloud users: Get a [Google Cloud API key bound to a service account](https://cloud.google.com/docs/authentication/api-keys)
-      
+
       For more details, see the [Vertex AI Express mode documentation](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/start/quickstart?usertype=apikey).
     </Info>
 
@@ -652,6 +652,7 @@ In this section, you'll find detailed examples that help you select, configure,
     # Optional
     AWS_SESSION_TOKEN=<your-session-token>  # For temporary credentials
     AWS_DEFAULT_REGION=<your-region>  # Defaults to us-east-1
+    AWS_REGION_NAME=<your-region>  # Alternative configuration for backwards compatibility with LiteLLM. Defaults to us-east-1
     ```
 
     **Basic Usage:**
@@ -695,6 +696,7 @@ In this section, you'll find detailed examples that help you select, configure,
     - `AWS_SECRET_ACCESS_KEY`: AWS secret key (required)
     - `AWS_SESSION_TOKEN`: AWS session token for temporary credentials (optional)
     - `AWS_DEFAULT_REGION`: AWS region (defaults to `us-east-1`)
+    - `AWS_REGION_NAME`: AWS region (defaults to `us-east-1`). Alternative configuration for backwards compatibility with LiteLLM
 
     **Features:**
     - Native tool calling support via Converse API

docs/en/concepts/tasks.mdx

@@ -46,7 +46,7 @@ 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.                                                                                 |
@@ -63,7 +63,7 @@ crew = Crew(
 | **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. |
+| **Guardrails** _(optional)_            | `guardrails`            | `Optional[List[Callable]]`  | 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">

docs/en/enterprise/features/flow-hitl-management.mdx

@@ -38,22 +38,21 @@ CrewAI Enterprise provides a comprehensive Human-in-the-Loop (HITL) management s
 Configure human review checkpoints within your Flows using the `@human_feedback` decorator. When execution reaches a review point, the system pauses, notifies the assignee via email, and waits for a response.
 
 ```python
-from crewai.flow.flow import Flow, start, listen
+from crewai.flow.flow import Flow, start, listen, or_
 from crewai.flow.human_feedback import human_feedback, HumanFeedbackResult
 
 class ContentApprovalFlow(Flow):
     @start()
     def generate_content(self):
-        # AI generates content
         return "Generated marketing copy for Q1 campaign..."
 
-    @listen(generate_content)
     @human_feedback(
         message="Please review this content for brand compliance:",
         emit=["approved", "rejected", "needs_revision"],
     )
-    def review_content(self, content):
-        return content
+    @listen(or_("generate_content", "needs_revision"))
+    def review_content(self):
+        return "Marketing copy for review..."
 
     @listen("approved")
     def publish_content(self, result: HumanFeedbackResult):
@@ -62,10 +61,6 @@ class ContentApprovalFlow(Flow):
     @listen("rejected")
     def archive_content(self, result: HumanFeedbackResult):
         print(f"Content rejected. Reason: {result.feedback}")
-
-    @listen("needs_revision")
-    def revise_content(self, result: HumanFeedbackResult):
-        print(f"Revision requested: {result.feedback}")
 ```
 
 For complete implementation details, see the [Human Feedback in Flows](/en/learn/human-feedback-in-flows) guide.

docs/en/enterprise/guides/deploy-to-amp.mdx

@@ -177,6 +177,11 @@ You need to push your crew to a GitHub repository. If you haven't created a crew
       ![Set Environment Variables](/images/enterprise/set-env-variables.png)
     </Frame>
 
+    <Info>
+      Using private Python packages? You'll need to add your registry credentials here too.
+      See [Private Package Registries](/en/enterprise/guides/private-package-registry) for the required variables.
+    </Info>
+
   </Step>
 
   <Step title="Deploy Your Crew">

docs/en/enterprise/guides/prepare-for-deployment.mdx

@@ -256,6 +256,12 @@ Before deployment, ensure you have:
 1. **LLM API keys** ready (OpenAI, Anthropic, Google, etc.)
 2. **Tool API keys** if using external tools (Serper, etc.)
 
+<Info>
+  If your project depends on packages from a **private PyPI registry**, you'll also need to configure
+  registry authentication credentials as environment variables. See the
+  [Private Package Registries](/en/enterprise/guides/private-package-registry) guide for details.
+</Info>
+
 <Tip>
   Test your project locally with the same environment variables before deploying
   to catch configuration issues early.

docs/en/enterprise/guides/private-package-registry.mdx

@@ -0,0 +1,263 @@
+---
+title: "Private Package Registries"
+description: "Install private Python packages from authenticated PyPI registries in CrewAI AMP"
+icon: "lock"
+mode: "wide"
+---
+
+<Note>
+  This guide covers how to configure your CrewAI project to install Python packages
+  from private PyPI registries (Azure DevOps Artifacts, GitHub Packages, GitLab, AWS CodeArtifact, etc.)
+  when deploying to CrewAI AMP.
+</Note>
+
+## When You Need This
+
+If your project depends on internal or proprietary Python packages hosted on a private registry
+rather than the public PyPI, you'll need to:
+
+1. Tell UV **where** to find the package (an index URL)
+2. Tell UV **which** packages come from that index (a source mapping)
+3. Provide **credentials** so UV can authenticate during install
+
+CrewAI AMP uses [UV](https://docs.astral.sh/uv/) for dependency resolution and installation.
+UV supports authenticated private registries through `pyproject.toml` configuration combined
+with environment variables for credentials.
+
+## Step 1: Configure pyproject.toml
+
+Three pieces work together in your `pyproject.toml`:
+
+### 1a. Declare the dependency
+
+Add the private package to your `[project.dependencies]` like any other dependency:
+
+```toml
+[project]
+dependencies = [
+    "crewai[tools]>=0.100.1,<1.0.0",
+    "my-private-package>=1.2.0",
+]
+```
+
+### 1b. Define the index
+
+Register your private registry as a named index under `[[tool.uv.index]]`:
+
+```toml
+[[tool.uv.index]]
+name = "my-private-registry"
+url = "https://pkgs.dev.azure.com/my-org/_packaging/my-feed/pypi/simple/"
+explicit = true
+```
+
+<Info>
+  The `name` field is important — UV uses it to construct the environment variable names
+  for authentication (see [Step 2](#step-2-set-authentication-credentials) below).
+
+  Setting `explicit = true` means UV won't search this index for every package — only the
+  ones you explicitly map to it in `[tool.uv.sources]`. This avoids unnecessary queries
+  against your private registry and protects against dependency confusion attacks.
+</Info>
+
+### 1c. Map the package to the index
+
+Tell UV which packages should be resolved from your private index using `[tool.uv.sources]`:
+
+```toml
+[tool.uv.sources]
+my-private-package = { index = "my-private-registry" }
+```
+
+### Complete example
+
+```toml
+[project]
+name = "my-crew-project"
+version = "0.1.0"
+requires-python = ">=3.10,<=3.13"
+dependencies = [
+    "crewai[tools]>=0.100.1,<1.0.0",
+    "my-private-package>=1.2.0",
+]
+
+[tool.crewai]
+type = "crew"
+
+[[tool.uv.index]]
+name = "my-private-registry"
+url = "https://pkgs.dev.azure.com/my-org/_packaging/my-feed/pypi/simple/"
+explicit = true
+
+[tool.uv.sources]
+my-private-package = { index = "my-private-registry" }
+```
+
+After updating `pyproject.toml`, regenerate your lock file:
+
+```bash
+uv lock
+```
+
+<Warning>
+  Always commit the updated `uv.lock` along with your `pyproject.toml` changes.
+  The lock file is required for deployment — see [Prepare for Deployment](/en/enterprise/guides/prepare-for-deployment).
+</Warning>
+
+## Step 2: Set Authentication Credentials
+
+UV authenticates against private indexes using environment variables that follow a naming convention
+based on the index name you defined in `pyproject.toml`:
+
+```
+UV_INDEX_{UPPER_NAME}_USERNAME
+UV_INDEX_{UPPER_NAME}_PASSWORD
+```
+
+Where `{UPPER_NAME}` is your index name converted to **uppercase** with **hyphens replaced by underscores**.
+
+For example, an index named `my-private-registry` uses:
+
+| Variable | Value |
+|----------|-------|
+| `UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME` | Your registry username or token name |
+| `UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD` | Your registry password or token/PAT |
+
+<Warning>
+  These environment variables **must** be added via the CrewAI AMP **Environment Variables** settings —
+  either globally or at the deployment level. They cannot be set in `.env` files or hardcoded in your project.
+
+  See [Setting Environment Variables in AMP](#setting-environment-variables-in-amp) below.
+</Warning>
+
+## Registry Provider Reference
+
+The table below shows the index URL format and credential values for common registry providers.
+Replace placeholder values with your actual organization and feed details.
+
+| Provider | Index URL | Username | Password |
+|----------|-----------|----------|----------|
+| **Azure DevOps Artifacts** | `https://pkgs.dev.azure.com/{org}/_packaging/{feed}/pypi/simple/` | Any non-empty string (e.g. `token`) | Personal Access Token (PAT) with Packaging Read scope |
+| **GitHub Packages** | `https://pypi.pkg.github.com/{owner}/simple/` | GitHub username | Personal Access Token (classic) with `read:packages` scope |
+| **GitLab Package Registry** | `https://gitlab.com/api/v4/projects/{project_id}/packages/pypi/simple/` | `__token__` | Project or Personal Access Token with `read_api` scope |
+| **AWS CodeArtifact** | Use the URL from `aws codeartifact get-repository-endpoint` | `aws` | Token from `aws codeartifact get-authorization-token` |
+| **Google Artifact Registry** | `https://{region}-python.pkg.dev/{project}/{repo}/simple/` | `_json_key_base64` | Base64-encoded service account key |
+| **JFrog Artifactory** | `https://{instance}.jfrog.io/artifactory/api/pypi/{repo}/simple/` | Username or email | API key or identity token |
+| **Self-hosted (devpi, Nexus, etc.)** | Your registry's simple API URL | Registry username | Registry password |
+
+<Tip>
+  For **AWS CodeArtifact**, the authorization token expires periodically.
+  You'll need to refresh the `UV_INDEX_*_PASSWORD` value when it expires.
+  Consider automating this in your CI/CD pipeline.
+</Tip>
+
+## Setting Environment Variables in AMP
+
+Private registry credentials must be configured as environment variables in CrewAI AMP.
+You have two options:
+
+<Tabs>
+  <Tab title="Web Interface">
+    1. Log in to [CrewAI AMP](https://app.crewai.com)
+    2. Navigate to your automation
+    3. Open the **Environment Variables** tab
+    4. Add each variable (`UV_INDEX_*_USERNAME` and `UV_INDEX_*_PASSWORD`) with its value
+
+    See the [Deploy to AMP — Set Environment Variables](/en/enterprise/guides/deploy-to-amp#set-environment-variables) step for details.
+  </Tab>
+  <Tab title="CLI Deployment">
+    Add the variables to your local `.env` file before running `crewai deploy create`.
+    The CLI will securely transfer them to the platform:
+
+    ```bash
+    # .env
+    OPENAI_API_KEY=sk-...
+    UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME=token
+    UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD=your-pat-here
+    ```
+
+    ```bash
+    crewai deploy create
+    ```
+  </Tab>
+</Tabs>
+
+<Warning>
+  **Never** commit credentials to your repository. Use AMP environment variables for all secrets.
+  The `.env` file should be listed in `.gitignore`.
+</Warning>
+
+To update credentials on an existing deployment, see [Update Your Crew — Environment Variables](/en/enterprise/guides/update-crew).
+
+## How It All Fits Together
+
+When CrewAI AMP builds your automation, the resolution flow works like this:
+
+<Steps>
+  <Step title="Build starts">
+    AMP pulls your repository and reads `pyproject.toml` and `uv.lock`.
+  </Step>
+  <Step title="UV resolves dependencies">
+    UV reads `[tool.uv.sources]` to determine which index each package should come from.
+  </Step>
+  <Step title="UV authenticates">
+    For each private index, UV looks up `UV_INDEX_{NAME}_USERNAME` and `UV_INDEX_{NAME}_PASSWORD`
+    from the environment variables you configured in AMP.
+  </Step>
+  <Step title="Packages install">
+    UV downloads and installs all packages — both public (from PyPI) and private (from your registry).
+  </Step>
+  <Step title="Automation runs">
+    Your crew or flow starts with all dependencies available.
+  </Step>
+</Steps>
+
+## Troubleshooting
+
+### Authentication Errors During Build
+
+**Symptom**: Build fails with `401 Unauthorized` or `403 Forbidden` when resolving a private package.
+
+**Check**:
+- The `UV_INDEX_*` environment variable names match your index name exactly (uppercased, hyphens → underscores)
+- Credentials are set in AMP environment variables, not just in a local `.env`
+- Your token/PAT has the required read permissions for the package feed
+- The token hasn't expired (especially relevant for AWS CodeArtifact)
+
+### Package Not Found
+
+**Symptom**: `No matching distribution found for my-private-package`.
+
+**Check**:
+- The index URL in `pyproject.toml` ends with `/simple/`
+- The `[tool.uv.sources]` entry maps the correct package name to the correct index name
+- The package is actually published to your private registry
+- Run `uv lock` locally with the same credentials to verify resolution works
+
+### Lock File Conflicts
+
+**Symptom**: `uv lock` fails or produces unexpected results after adding a private index.
+
+**Solution**: Set the credentials locally and regenerate:
+
+```bash
+export UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME=token
+export UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD=your-pat
+uv lock
+```
+
+Then commit the updated `uv.lock`.
+
+## Related Guides
+
+<CardGroup cols={3}>
+  <Card title="Prepare for Deployment" icon="clipboard-check" href="/en/enterprise/guides/prepare-for-deployment">
+    Verify project structure and dependencies before deploying.
+  </Card>
+  <Card title="Deploy to AMP" icon="rocket" href="/en/enterprise/guides/deploy-to-amp">
+    Deploy your crew or flow and configure environment variables.
+  </Card>
+  <Card title="Update Your Crew" icon="arrows-rotate" href="/en/enterprise/guides/update-crew">
+    Update environment variables and push changes to a running deployment.
+  </Card>
+</CardGroup>

docs/en/enterprise/integrations/google_contacts.mdx

@@ -224,6 +224,60 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `groupFields` (string, optional): Fields to include (e.g., 'name,memberCount,clientData'). Default: name,memberCount
 
   </Accordion>
+
+  <Accordion title="google_contacts/get_contact_group">
+    **Description:** Get a specific contact group by resource name.
+
+    **Parameters:**
+    - `resourceName` (string, required): The resource name of the contact group (e.g., 'contactGroups/myContactGroup')
+    - `maxMembers` (integer, optional): Maximum number of members to include. Minimum: 0, Maximum: 20000
+    - `groupFields` (string, optional): Fields to include (e.g., 'name,memberCount,clientData'). Default: name,memberCount
+
+  </Accordion>
+
+  <Accordion title="google_contacts/create_contact_group">
+    **Description:** Create a new contact group (label).
+
+    **Parameters:**
+    - `name` (string, required): The name of the contact group
+    - `clientData` (array, optional): Client-specific data
+      ```json
+      [
+        {
+          "key": "data_key",
+          "value": "data_value"
+        }
+      ]
+      ```
+
+  </Accordion>
+
+  <Accordion title="google_contacts/update_contact_group">
+    **Description:** Update a contact group's information.
+
+    **Parameters:**
+    - `resourceName` (string, required): The resource name of the contact group (e.g., 'contactGroups/myContactGroup')
+    - `name` (string, required): The name of the contact group
+    - `clientData` (array, optional): Client-specific data
+      ```json
+      [
+        {
+          "key": "data_key",
+          "value": "data_value"
+        }
+      ]
+      ```
+
+  </Accordion>
+
+  <Accordion title="google_contacts/delete_contact_group">
+    **Description:** Delete a contact group.
+
+    **Parameters:**
+    - `resourceName` (string, required): The resource name of the contact group to delete (e.g., 'contactGroups/myContactGroup')
+    - `deleteContacts` (boolean, optional): Whether to delete contacts in the group as well. Default: false
+
+  </Accordion>
 </AccordionGroup>
 
 ## Usage Examples

docs/en/enterprise/integrations/google_docs.mdx

@@ -132,6 +132,297 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `endIndex` (integer, required): The end index of the range.
 
   </Accordion>
+
+  <Accordion title="google_docs/create_document_with_content">
+    **Description:** Create a new Google Document with content in one action.
+
+    **Parameters:**
+    - `title` (string, required): The title for the new document. Appears at the top of the document and in Google Drive.
+    - `content` (string, optional): The text content to insert into the document. Use `\n` for new paragraphs.
+
+  </Accordion>
+
+  <Accordion title="google_docs/append_text">
+    **Description:** Append text to the end of a Google Document. Automatically inserts at the document end without needing to specify an index.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID from create_document response or URL.
+    - `text` (string, required): Text to append at the end of the document. Use `\n` for new paragraphs.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_bold">
+    **Description:** Make text bold or remove bold formatting in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of text to format.
+    - `endIndex` (integer, required): End position of text to format (exclusive).
+    - `bold` (boolean, required): Set `true` to make bold, `false` to remove bold.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_italic">
+    **Description:** Make text italic or remove italic formatting in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of text to format.
+    - `endIndex` (integer, required): End position of text to format (exclusive).
+    - `italic` (boolean, required): Set `true` to make italic, `false` to remove italic.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_underline">
+    **Description:** Add or remove underline formatting from text in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of text to format.
+    - `endIndex` (integer, required): End position of text to format (exclusive).
+    - `underline` (boolean, required): Set `true` to underline, `false` to remove underline.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_strikethrough">
+    **Description:** Add or remove strikethrough formatting from text in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of text to format.
+    - `endIndex` (integer, required): End position of text to format (exclusive).
+    - `strikethrough` (boolean, required): Set `true` to add strikethrough, `false` to remove.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_font_size">
+    **Description:** Change the font size of text in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of text to format.
+    - `endIndex` (integer, required): End position of text to format (exclusive).
+    - `fontSize` (number, required): Font size in points. Common sizes: 10, 11, 12, 14, 16, 18, 24, 36.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_color">
+    **Description:** Change the color of text using RGB values (0-1 scale) in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of text to format.
+    - `endIndex` (integer, required): End position of text to format (exclusive).
+    - `red` (number, required): Red component (0-1). Example: `1` for full red.
+    - `green` (number, required): Green component (0-1). Example: `0.5` for half green.
+    - `blue` (number, required): Blue component (0-1). Example: `0` for no blue.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_hyperlink">
+    **Description:** Turn existing text into a clickable hyperlink in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of text to make into a link.
+    - `endIndex` (integer, required): End position of text to make into a link (exclusive).
+    - `url` (string, required): The URL the link should point to. Example: `"https://example.com"`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/apply_heading_style">
+    **Description:** Apply a heading or paragraph style to a text range in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of paragraph(s) to style.
+    - `endIndex` (integer, required): End position of paragraph(s) to style.
+    - `style` (string, required): The style to apply. Enum: `NORMAL_TEXT`, `TITLE`, `SUBTITLE`, `HEADING_1`, `HEADING_2`, `HEADING_3`, `HEADING_4`, `HEADING_5`, `HEADING_6`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_paragraph_alignment">
+    **Description:** Set text alignment for paragraphs in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of paragraph(s) to align.
+    - `endIndex` (integer, required): End position of paragraph(s) to align.
+    - `alignment` (string, required): Text alignment. Enum: `START` (left), `CENTER`, `END` (right), `JUSTIFIED`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_line_spacing">
+    **Description:** Set line spacing for paragraphs in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of paragraph(s).
+    - `endIndex` (integer, required): End position of paragraph(s).
+    - `lineSpacing` (number, required): Line spacing as percentage. `100` = single, `115` = 1.15x, `150` = 1.5x, `200` = double.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_paragraph_bullets">
+    **Description:** Convert paragraphs to a bulleted or numbered list in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of paragraphs to convert to list.
+    - `endIndex` (integer, required): End position of paragraphs to convert to list.
+    - `bulletPreset` (string, required): Bullet/numbering style. Enum: `BULLET_DISC_CIRCLE_SQUARE`, `BULLET_DIAMONDX_ARROW3D_SQUARE`, `BULLET_CHECKBOX`, `BULLET_ARROW_DIAMOND_DISC`, `BULLET_STAR_CIRCLE_SQUARE`, `NUMBERED_DECIMAL_ALPHA_ROMAN`, `NUMBERED_DECIMAL_ALPHA_ROMAN_PARENS`, `NUMBERED_DECIMAL_NESTED`, `NUMBERED_UPPERALPHA_ALPHA_ROMAN`, `NUMBERED_UPPERROMAN_UPPERALPHA_DECIMAL`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_paragraph_bullets">
+    **Description:** Remove bullets or numbering from paragraphs in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `startIndex` (integer, required): Start position of list paragraphs.
+    - `endIndex` (integer, required): End position of list paragraphs.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_with_content">
+    **Description:** Insert a table with content into a Google Document in one action. Provide content as a 2D array.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `rows` (integer, required): Number of rows in the table.
+    - `columns` (integer, required): Number of columns in the table.
+    - `index` (integer, optional): Position to insert the table. If not provided, the table is inserted at the end of the document.
+    - `content` (array, required): Table content as a 2D array. Each inner array is a row. Example: `[["Year", "Revenue"], ["2023", "$43B"], ["2024", "$45B"]]`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_row">
+    **Description:** Insert a new row above or below a reference cell in an existing table.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `tableStartIndex` (integer, required): The start index of the table. Get from get_document.
+    - `rowIndex` (integer, required): Row index (0-based) of reference cell.
+    - `columnIndex` (integer, optional): Column index (0-based) of reference cell. Default is `0`.
+    - `insertBelow` (boolean, optional): If `true`, insert below the reference row. If `false`, insert above. Default is `true`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_column">
+    **Description:** Insert a new column left or right of a reference cell in an existing table.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `tableStartIndex` (integer, required): The start index of the table.
+    - `rowIndex` (integer, optional): Row index (0-based) of reference cell. Default is `0`.
+    - `columnIndex` (integer, required): Column index (0-based) of reference cell.
+    - `insertRight` (boolean, optional): If `true`, insert to the right. If `false`, insert to the left. Default is `true`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_table_row">
+    **Description:** Delete a row from an existing table in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `tableStartIndex` (integer, required): The start index of the table.
+    - `rowIndex` (integer, required): Row index (0-based) to delete.
+    - `columnIndex` (integer, optional): Column index (0-based) of any cell in the row. Default is `0`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_table_column">
+    **Description:** Delete a column from an existing table in a Google Document.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `tableStartIndex` (integer, required): The start index of the table.
+    - `rowIndex` (integer, optional): Row index (0-based) of any cell in the column. Default is `0`.
+    - `columnIndex` (integer, required): Column index (0-based) to delete.
+
+  </Accordion>
+
+  <Accordion title="google_docs/merge_table_cells">
+    **Description:** Merge a range of table cells into a single cell. Content from all cells is preserved.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `tableStartIndex` (integer, required): The start index of the table.
+    - `rowIndex` (integer, required): Starting row index (0-based) for the merge.
+    - `columnIndex` (integer, required): Starting column index (0-based) for the merge.
+    - `rowSpan` (integer, required): Number of rows to merge.
+    - `columnSpan` (integer, required): Number of columns to merge.
+
+  </Accordion>
+
+  <Accordion title="google_docs/unmerge_table_cells">
+    **Description:** Unmerge previously merged table cells back into individual cells.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `tableStartIndex` (integer, required): The start index of the table.
+    - `rowIndex` (integer, required): Row index (0-based) of the merged cell.
+    - `columnIndex` (integer, required): Column index (0-based) of the merged cell.
+    - `rowSpan` (integer, required): Number of rows the merged cell spans.
+    - `columnSpan` (integer, required): Number of columns the merged cell spans.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_inline_image">
+    **Description:** Insert an image from a public URL into a Google Document. The image must be publicly accessible, under 50MB, and in PNG/JPEG/GIF format.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `uri` (string, required): Public URL of the image. Must be accessible without authentication.
+    - `index` (integer, optional): Position to insert the image. If not provided, the image is inserted at the end of the document. Default is `1`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_section_break">
+    **Description:** Insert a section break to create document sections with different formatting.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `index` (integer, required): Position to insert the section break.
+    - `sectionType` (string, required): The type of section break. Enum: `CONTINUOUS` (stays on same page), `NEXT_PAGE` (starts a new page).
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_header">
+    **Description:** Create a header for the document. Returns a headerId which can be used with insert_text to add header content.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `type` (string, optional): Header type. Enum: `DEFAULT`. Default is `DEFAULT`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_footer">
+    **Description:** Create a footer for the document. Returns a footerId which can be used with insert_text to add footer content.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `type` (string, optional): Footer type. Enum: `DEFAULT`. Default is `DEFAULT`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_header">
+    **Description:** Delete a header from the document. Use get_document to find the headerId.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `headerId` (string, required): The header ID to delete. Get from get_document response.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_footer">
+    **Description:** Delete a footer from the document. Use get_document to find the footerId.
+
+    **Parameters:**
+    - `documentId` (string, required): The document ID.
+    - `footerId` (string, required): The footer ID to delete. Get from get_document response.
+
+  </Accordion>
 </AccordionGroup>
 
 ## Usage Examples

docs/en/enterprise/integrations/google_slides.mdx

@@ -62,6 +62,22 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/get_presentation_metadata">
+    **Description:** Get lightweight metadata about a presentation (title, slide count, slide IDs). Use this first before fetching full content.
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation to retrieve.
+
+  </Accordion>
+
+  <Accordion title="google_slides/get_presentation_text">
+    **Description:** Extract all text content from a presentation. Returns slide IDs and text from shapes and tables only (no formatting).
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+
+  </Accordion>
+
   <Accordion title="google_slides/get_presentation">
     **Description:** Retrieves a presentation by ID.
 
@@ -96,6 +112,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/get_slide_text">
+    **Description:** Extract text content from a single slide. Returns only text from shapes and tables (no formatting or styling).
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `pageObjectId` (string, required): The ID of the slide/page to get text from.
+
+  </Accordion>
+
   <Accordion title="google_slides/get_page">
     **Description:** Retrieves a specific page by its ID.
 
@@ -114,6 +139,120 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/create_slide">
+    **Description:** Add an additional blank slide to a presentation. New presentations already have one blank slide - check get_presentation_metadata first. For slides with title/body areas, use create_slide_with_layout instead.
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `insertionIndex` (integer, optional): Where to insert the slide (0-based). If omitted, adds at the end.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_slide_with_layout">
+    **Description:** Create a slide with a predefined layout containing placeholder areas for title, body, etc. This is better than create_slide for structured content. After creating, use get_page to find placeholder IDs, then insert text into them.
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `layout` (string, required): Layout type. One of: `BLANK`, `TITLE`, `TITLE_AND_BODY`, `TITLE_AND_TWO_COLUMNS`, `TITLE_ONLY`, `SECTION_HEADER`, `ONE_COLUMN_TEXT`, `MAIN_POINT`, `BIG_NUMBER`. TITLE_AND_BODY is best for title+description. TITLE for title-only slides. SECTION_HEADER for section dividers.
+    - `insertionIndex` (integer, optional): Where to insert (0-based). Omit to add at end.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_text_box">
+    **Description:** Create a text box on a slide with content. Use this for titles, descriptions, paragraphs - not tables. Optionally specify position (x, y) and size (width, height) in EMU units (914400 EMU = 1 inch).
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideId` (string, required): The ID of the slide to add the text box to.
+    - `text` (string, required): The text content for the text box.
+    - `x` (integer, optional): X position in EMU (914400 = 1 inch). Default: 914400 (1 inch from left).
+    - `y` (integer, optional): Y position in EMU (914400 = 1 inch). Default: 914400 (1 inch from top).
+    - `width` (integer, optional): Width in EMU. Default: 7315200 (~8 inches).
+    - `height` (integer, optional): Height in EMU. Default: 914400 (~1 inch).
+
+  </Accordion>
+
+  <Accordion title="google_slides/delete_slide">
+    **Description:** Remove a slide from the presentation. Use get_presentation first to find the slide ID.
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideId` (string, required): The object ID of the slide to delete. Get from get_presentation.
+
+  </Accordion>
+
+  <Accordion title="google_slides/duplicate_slide">
+    **Description:** Create a copy of an existing slide. The duplicate is inserted immediately after the original.
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideId` (string, required): The object ID of the slide to duplicate. Get from get_presentation.
+
+  </Accordion>
+
+  <Accordion title="google_slides/move_slides">
+    **Description:** Reorder slides by moving them to a new position. Slide IDs must be in their current presentation order (no duplicates).
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideIds` (array of strings, required): Array of slide IDs to move. Must be in current presentation order.
+    - `insertionIndex` (integer, required): Target position (0-based). 0 = beginning, slide count = end.
+
+  </Accordion>
+
+  <Accordion title="google_slides/insert_youtube_video">
+    **Description:** Embed a YouTube video on a slide. The video ID is the value after "v=" in YouTube URLs (e.g., for youtube.com/watch?v=abc123, use "abc123").
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideId` (string, required): The ID of the slide to add the video to. Get from get_presentation.
+    - `videoId` (string, required): The YouTube video ID (the value after v= in the URL).
+
+  </Accordion>
+
+  <Accordion title="google_slides/insert_drive_video">
+    **Description:** Embed a video from Google Drive on a slide. The file ID can be found in the Drive file URL.
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideId` (string, required): The ID of the slide to add the video to. Get from get_presentation.
+    - `fileId` (string, required): The Google Drive file ID of the video.
+
+  </Accordion>
+
+  <Accordion title="google_slides/set_slide_background_image">
+    **Description:** Set a background image for a slide. The image URL must be publicly accessible.
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideId` (string, required): The ID of the slide to set the background for. Get from get_presentation.
+    - `imageUrl` (string, required): Publicly accessible URL of the image to use as background.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_table">
+    **Description:** Create an empty table on a slide. To create a table with content, use create_table_with_content instead.
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideId` (string, required): The ID of the slide to add the table to. Get from get_presentation.
+    - `rows` (integer, required): Number of rows in the table.
+    - `columns` (integer, required): Number of columns in the table.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_table_with_content">
+    **Description:** Create a table with content in one action. Provide content as a 2D array where each inner array is a row. Example: [["Header1", "Header2"], ["Row1Col1", "Row1Col2"]].
+
+    **Parameters:**
+    - `presentationId` (string, required): The ID of the presentation.
+    - `slideId` (string, required): The ID of the slide to add the table to. Get from get_presentation.
+    - `rows` (integer, required): Number of rows in the table.
+    - `columns` (integer, required): Number of columns in the table.
+    - `content` (array, required): Table content as 2D array. Each inner array is a row. Example: [["Year", "Revenue"], ["2023", "$10M"]].
+
+  </Accordion>
+
   <Accordion title="google_slides/import_data_from_sheet">
     **Description:** Imports data from a Google Sheet into a presentation.
 

docs/en/enterprise/integrations/microsoft_excel.mdx

@@ -169,6 +169,16 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_excel/get_table_data">
+    **Description:** Get data from a specific table in an Excel worksheet.
+
+    **Parameters:**
+    - `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
+
+  </Accordion>
+
   <Accordion title="microsoft_excel/create_chart">
     **Description:** Create a chart in an Excel worksheet.
 
@@ -201,6 +211,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_excel/get_used_range_metadata">
+    **Description:** Get the used range metadata (dimensions only, no data) of an Excel worksheet.
+
+    **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">
     **Description:** Get all charts in an Excel worksheet.
 

docs/en/enterprise/integrations/microsoft_onedrive.mdx

@@ -151,6 +151,49 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `item_id` (string, required): The ID of the file.
 
   </Accordion>
+
+  <Accordion title="microsoft_onedrive/list_files_by_path">
+    **Description:** List files and folders in a specific OneDrive path.
+
+    **Parameters:**
+    - `folder_path` (string, required): The folder path (e.g., 'Documents/Reports').
+    - `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".
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_recent_files">
+    **Description:** Get recently accessed files from OneDrive.
+
+    **Parameters:**
+    - `top` (integer, optional): Number of items to retrieve (max 200). Default is `25`.
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_shared_with_me">
+    **Description:** Get files and folders shared with the user.
+
+    **Parameters:**
+    - `top` (integer, optional): Number of items to retrieve (max 200). Default is `50`.
+    - `orderby` (string, optional): Order by field. Default is "name asc".
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_file_by_path">
+    **Description:** Get information about a specific file or folder by path.
+
+    **Parameters:**
+    - `file_path` (string, required): The file or folder path (e.g., 'Documents/report.docx').
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/download_file_by_path">
+    **Description:** Download a file from OneDrive by its path.
+
+    **Parameters:**
+    - `file_path` (string, required): The file path (e.g., 'Documents/report.docx').
+
+  </Accordion>
 </AccordionGroup>
 
 ## Usage Examples

docs/en/enterprise/integrations/microsoft_outlook.mdx

@@ -133,6 +133,74 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `companyName` (string, optional): Contact's company name.
 
   </Accordion>
+
+  <Accordion title="microsoft_outlook/get_message">
+    **Description:** Get a specific email message by ID.
+
+    **Parameters:**
+    - `message_id` (string, required): The unique identifier of the message. Obtain from get_messages action.
+    - `select` (string, optional): Comma-separated list of properties to return. Example: "id,subject,body,from,receivedDateTime". Default is "id,subject,body,from,toRecipients,receivedDateTime".
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/reply_to_email">
+    **Description:** Reply to an email message.
+
+    **Parameters:**
+    - `message_id` (string, required): The unique identifier of the message to reply to. Obtain from get_messages action.
+    - `comment` (string, required): The reply message content. Can be plain text or HTML. The original message will be quoted below this content.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/forward_email">
+    **Description:** Forward an email message.
+
+    **Parameters:**
+    - `message_id` (string, required): The unique identifier of the message to forward. Obtain from get_messages action.
+    - `to_recipients` (array, required): Array of recipient email addresses to forward to. Example: ["john@example.com", "jane@example.com"].
+    - `comment` (string, optional): Optional message to include above the forwarded content. Can be plain text or HTML.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/mark_message_read">
+    **Description:** Mark a message as read or unread.
+
+    **Parameters:**
+    - `message_id` (string, required): The unique identifier of the message. Obtain from get_messages action.
+    - `is_read` (boolean, required): Set to true to mark as read, false to mark as unread.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/delete_message">
+    **Description:** Delete an email message.
+
+    **Parameters:**
+    - `message_id` (string, required): The unique identifier of the message to delete. Obtain from get_messages action.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/update_event">
+    **Description:** Update an existing calendar event.
+
+    **Parameters:**
+    - `event_id` (string, required): The unique identifier of the event. Obtain from get_calendar_events action.
+    - `subject` (string, optional): New subject/title for the event.
+    - `start_time` (string, optional): New start time in ISO 8601 format (e.g., "2024-01-20T10:00:00"). REQUIRED: Must also provide start_timezone when using this field.
+    - `start_timezone` (string, optional): Timezone for start time. REQUIRED when updating start_time. Examples: "Pacific Standard Time", "Eastern Standard Time", "UTC".
+    - `end_time` (string, optional): New end time in ISO 8601 format. REQUIRED: Must also provide end_timezone when using this field.
+    - `end_timezone` (string, optional): Timezone for end time. REQUIRED when updating end_time. Examples: "Pacific Standard Time", "Eastern Standard Time", "UTC".
+    - `location` (string, optional): New location for the event.
+    - `body` (string, optional): New body/description for the event. Supports HTML formatting.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/delete_event">
+    **Description:** Delete a calendar event.
+
+    **Parameters:**
+    - `event_id` (string, required): The unique identifier of the event to delete. Obtain from get_calendar_events action.
+
+  </Accordion>
 </AccordionGroup>
 
 ## Usage Examples

docs/en/enterprise/integrations/microsoft_sharepoint.mdx

@@ -78,6 +78,17 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_sharepoint/get_drives">
+    **Description:** List all document libraries (drives) in a SharePoint site. Use this to discover available libraries before using file operations.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `top` (integer, optional): Maximum number of drives to return per page (1-999). Default is 100
+    - `skip_token` (string, optional): Pagination token from a previous response to fetch the next page of results
+    - `select` (string, optional): Comma-separated list of properties to return (e.g., 'id,name,webUrl,driveType')
+
+  </Accordion>
+
   <Accordion title="microsoft_sharepoint/get_site_lists">
     **Description:** Get all lists in a SharePoint site.
 
@@ -159,20 +170,317 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
-  <Accordion title="microsoft_sharepoint/get_drive_items">
-    **Description:** Get files and folders from a SharePoint document library.
+  <Accordion title="microsoft_sharepoint/list_files">
+    **Description:** Retrieve files and folders from a SharePoint document library. By default lists the root folder, but you can navigate into subfolders by providing a folder_id.
 
     **Parameters:**
-    - `site_id` (string, required): The ID of the SharePoint site
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `folder_id` (string, optional): The ID of the folder to list contents from. Use 'root' for the root folder, or provide a folder ID from a previous list_files call. Default is 'root'
+    - `top` (integer, optional): Maximum number of items to return per page (1-1000). Default is 50
+    - `skip_token` (string, optional): Pagination token from a previous response to fetch the next page of results
+    - `orderby` (string, optional): Sort order for results (e.g., 'name asc', 'size desc', 'lastModifiedDateTime desc'). Default is 'name asc'
+    - `filter` (string, optional): OData filter to narrow results (e.g., 'file ne null' for files only, 'folder ne null' for folders only)
+    - `select` (string, optional): Comma-separated list of fields to return (e.g., 'id,name,size,folder,file,webUrl,lastModifiedDateTime')
 
   </Accordion>
 
-  <Accordion title="microsoft_sharepoint/delete_drive_item">
-    **Description:** Delete a file or folder from SharePoint document library.
+  <Accordion title="microsoft_sharepoint/delete_file">
+    **Description:** Delete a file or folder from a SharePoint document library. For folders, all contents are deleted recursively. Items are moved to the site recycle bin.
 
     **Parameters:**
-    - `site_id` (string, required): The ID of the SharePoint site
-    - `item_id` (string, required): The ID of the file or folder to delete
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the file or folder to delete. Obtain from list_files
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_files_by_path">
+    **Description:** List files and folders in a SharePoint document library folder by its path. More efficient than multiple list_files calls for deep navigation.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `folder_path` (string, required): The full path to the folder without leading/trailing slashes (e.g., 'Documents', 'Reports/2024/Q1')
+    - `top` (integer, optional): Maximum number of items to return per page (1-1000). Default is 50
+    - `skip_token` (string, optional): Pagination token from a previous response to fetch the next page of results
+    - `orderby` (string, optional): Sort order for results (e.g., 'name asc', 'size desc'). Default is 'name asc'
+    - `select` (string, optional): Comma-separated list of fields to return (e.g., 'id,name,size,folder,file,webUrl,lastModifiedDateTime')
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/download_file">
+    **Description:** Download raw file content from a SharePoint document library. Use only for plain text files (.txt, .csv, .json). For Excel files, use the Excel-specific actions. For Word files, use get_word_document_content.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the file to download. Obtain from list_files or list_files_by_path
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_file_info">
+    **Description:** Retrieve detailed metadata for a specific file or folder in a SharePoint document library, including name, size, created/modified dates, and author information.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the file or folder. Obtain from list_files or list_files_by_path
+    - `select` (string, optional): Comma-separated list of properties to return (e.g., 'id,name,size,createdDateTime,lastModifiedDateTime,webUrl,createdBy,lastModifiedBy')
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_folder">
+    **Description:** Create a new folder in a SharePoint document library. By default creates the folder in the root; use parent_id to create subfolders.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `folder_name` (string, required): Name for the new folder. Cannot contain: \ / : * ? " < > |
+    - `parent_id` (string, optional): The ID of the parent folder. Use 'root' for the document library root, or provide a folder ID from list_files. Default is 'root'
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/search_files">
+    **Description:** Search for files and folders in a SharePoint document library by keywords. Searches file names, folder names, and file contents for Office documents. Do not use wildcards or special characters.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `query` (string, required): Search keywords (e.g., 'report', 'budget 2024'). Wildcards like *.txt are not supported
+    - `top` (integer, optional): Maximum number of results to return per page (1-1000). Default is 50
+    - `skip_token` (string, optional): Pagination token from a previous response to fetch the next page of results
+    - `select` (string, optional): Comma-separated list of fields to return (e.g., 'id,name,size,folder,file,webUrl,lastModifiedDateTime')
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/copy_file">
+    **Description:** Copy a file or folder to a new location within SharePoint. The original item remains unchanged. The copy operation is asynchronous for large files.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the file or folder to copy. Obtain from list_files or search_files
+    - `destination_folder_id` (string, required): The ID of the destination folder. Use 'root' for the root folder, or a folder ID from list_files
+    - `new_name` (string, optional): New name for the copy. If not provided, the original name is used
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/move_file">
+    **Description:** Move a file or folder to a new location within SharePoint. The item is removed from its original location. For folders, all contents are moved as well.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the file or folder to move. Obtain from list_files or search_files
+    - `destination_folder_id` (string, required): The ID of the destination folder. Use 'root' for the root folder, or a folder ID from list_files
+    - `new_name` (string, optional): New name for the moved item. If not provided, the original name is kept
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_worksheets">
+    **Description:** List all worksheets (tabs) in an Excel workbook stored in a SharePoint document library. Use the returned worksheet name with other Excel actions.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `select` (string, optional): Comma-separated list of properties to return (e.g., 'id,name,position,visibility')
+    - `filter` (string, optional): OData filter expression (e.g., "visibility eq 'Visible'" to exclude hidden sheets)
+    - `top` (integer, optional): Maximum number of worksheets to return. Minimum: 1, Maximum: 999
+    - `orderby` (string, optional): Sort order (e.g., 'position asc' to return sheets in tab order)
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_excel_worksheet">
+    **Description:** Create a new worksheet (tab) in an Excel workbook stored in a SharePoint document library. The new sheet is added at the end of the tab list.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `name` (string, required): Name for the new worksheet. Maximum 31 characters. Cannot contain: \ / * ? : [ ]. Must be unique within the workbook
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_range_data">
+    **Description:** Retrieve cell values from a specific range in an Excel worksheet stored in SharePoint. For reading all data without knowing dimensions, use get_excel_used_range instead.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet (tab) to read from. Obtain from get_excel_worksheets. Case-sensitive
+    - `range` (string, required): Cell range in A1 notation (e.g., 'A1:C10', 'A:C', '1:5', 'A1')
+    - `select` (string, optional): Comma-separated list of properties to return (e.g., 'address,values,formulas,numberFormat,text')
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/update_excel_range_data">
+    **Description:** Write values to a specific range in an Excel worksheet stored in SharePoint. Overwrites existing cell contents. The values array dimensions must match the range dimensions exactly.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet (tab) to update. Obtain from get_excel_worksheets. Case-sensitive
+    - `range` (string, required): Cell range in A1 notation where values will be written (e.g., 'A1:C3' for a 3x3 block)
+    - `values` (array, required): 2D array of values (rows containing cells). Example for A1:B2: [["Header1", "Header2"], ["Value1", "Value2"]]. Use null to clear a cell
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_used_range_metadata">
+    **Description:** Return only the metadata (address and dimensions) of the used range in a worksheet, without the actual cell values. Ideal for large files to understand spreadsheet size before reading data in chunks.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet (tab) to read. Obtain from get_excel_worksheets. Case-sensitive
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_used_range">
+    **Description:** Retrieve all cells containing data in a worksheet stored in SharePoint. Do not use for files larger than 2MB. For large files, use get_excel_used_range_metadata first, then get_excel_range_data to read in smaller chunks.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet (tab) to read. Obtain from get_excel_worksheets. Case-sensitive
+    - `select` (string, optional): Comma-separated list of properties to return (e.g., 'address,values,formulas,numberFormat,text,rowCount,columnCount')
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_cell">
+    **Description:** Retrieve the value of a single cell by row and column index from an Excel file in SharePoint. Indices are 0-based (row 0 = Excel row 1, column 0 = column A).
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet (tab). Obtain from get_excel_worksheets. Case-sensitive
+    - `row` (integer, required): 0-based row index (row 0 = Excel row 1). Valid range: 0-1048575
+    - `column` (integer, required): 0-based column index (column 0 = A, column 1 = B). Valid range: 0-16383
+    - `select` (string, optional): Comma-separated list of properties to return (e.g., 'address,values,formulas,numberFormat,text')
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/add_excel_table">
+    **Description:** Convert a cell range into a formatted Excel table with filtering, sorting, and structured data capabilities. Tables enable add_excel_table_row for appending data.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet containing the data range. Obtain from get_excel_worksheets
+    - `range` (string, required): Cell range to convert into a table, including headers and data (e.g., 'A1:D10' where A1:D1 contains column headers)
+    - `has_headers` (boolean, optional): Set to true if the first row contains column headers. Default is true
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_tables">
+    **Description:** List all tables in a specific Excel worksheet stored in SharePoint. Returns table properties including id, name, showHeaders, and showTotals.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet to get tables from. Obtain from get_excel_worksheets
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/add_excel_table_row">
+    **Description:** Append a new row to the end of an Excel table in a SharePoint file. The values array must have the same number of elements as the table has columns.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet containing the table. Obtain from get_excel_worksheets
+    - `table_name` (string, required): Name of the table to add the row to (e.g., 'Table1'). Obtain from get_excel_tables. Case-sensitive
+    - `values` (array, required): Array of cell values for the new row, one per column in table order (e.g., ["John Doe", "john@example.com", 25])
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_table_data">
+    **Description:** Get all rows from an Excel table in a SharePoint file as a data range. Easier than get_excel_range_data when working with structured tables since you don't need to know the exact range.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet containing the table. Obtain from get_excel_worksheets
+    - `table_name` (string, required): Name of the table to get data from (e.g., 'Table1'). Obtain from get_excel_tables. Case-sensitive
+    - `select` (string, optional): Comma-separated list of properties to return (e.g., 'address,values,formulas,numberFormat,text')
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_excel_chart">
+    **Description:** Create a chart visualization in an Excel worksheet stored in SharePoint from a data range. The chart is embedded in the worksheet.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet where the chart will be created. Obtain from get_excel_worksheets
+    - `chart_type` (string, required): Chart type (e.g., 'ColumnClustered', 'ColumnStacked', 'Line', 'LineMarkers', 'Pie', 'Bar', 'BarClustered', 'Area', 'Scatter', 'Doughnut')
+    - `source_data` (string, required): Data range for the chart in A1 notation, including headers (e.g., 'A1:B10')
+    - `series_by` (string, optional): How data series are organized: 'Auto', 'Columns', or 'Rows'. Default is 'Auto'
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_excel_charts">
+    **Description:** List all charts embedded in an Excel worksheet stored in SharePoint. Returns chart properties including id, name, chartType, height, width, and position.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet to list charts from. Obtain from get_excel_worksheets
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/delete_excel_worksheet">
+    **Description:** Permanently remove a worksheet (tab) and all its contents from an Excel workbook stored in SharePoint. Cannot be undone. A workbook must have at least one worksheet.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet to delete. Case-sensitive. All data, tables, and charts on this sheet will be permanently removed
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/delete_excel_table">
+    **Description:** Remove a table from an Excel worksheet in SharePoint. This deletes the table structure (filtering, formatting, table features) but preserves the underlying cell data.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+    - `worksheet_name` (string, required): Name of the worksheet containing the table. Obtain from get_excel_worksheets
+    - `table_name` (string, required): Name of the table to delete (e.g., 'Table1'). Obtain from get_excel_tables. The data in the cells will remain after table deletion
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_excel_names">
+    **Description:** Retrieve all named ranges defined in an Excel workbook stored in SharePoint. Named ranges are user-defined labels for cell ranges (e.g., 'SalesData' for A1:D100).
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Excel file in SharePoint. Obtain from list_files or search_files
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_word_document_content">
+    **Description:** Download and extract text content from a Word document (.docx) stored in a SharePoint document library. This is the recommended way to read Word documents from SharePoint.
+
+    **Parameters:**
+    - `site_id` (string, required): The full SharePoint site identifier from get_sites
+    - `drive_id` (string, required): The ID of the document library. Call get_drives first to get valid drive IDs
+    - `item_id` (string, required): The unique identifier of the Word document (.docx) in SharePoint. Obtain from list_files or search_files
 
   </Accordion>
 </AccordionGroup>

docs/en/enterprise/integrations/microsoft_teams.mdx

@@ -108,6 +108,86 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `join_web_url` (string, required): The join web URL of the meeting to search for.
 
   </Accordion>
+
+  <Accordion title="microsoft_teams/search_online_meetings_by_meeting_id">
+    **Description:** Search online meetings by external Meeting ID.
+
+    **Parameters:**
+    - `join_meeting_id` (string, required): The meeting ID (numeric code) that attendees use to join. This is the joinMeetingId shown in meeting invitations, not the Graph API meeting id.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_meeting">
+    **Description:** Get details of a specific online meeting.
+
+    **Parameters:**
+    - `meeting_id` (string, required): The Graph API meeting ID (a long alphanumeric string). Obtain from create_meeting or search_online_meetings actions. Different from the numeric joinMeetingId.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_team_members">
+    **Description:** Get members of a specific team.
+
+    **Parameters:**
+    - `team_id` (string, required): The unique identifier of the team. Obtain from get_teams action.
+    - `top` (integer, optional): Maximum number of members to retrieve per page (1-999). Default is `100`.
+    - `skip_token` (string, optional): Pagination token from a previous response. When the response includes @odata.nextLink, extract the $skiptoken parameter value and pass it here to get the next page of results.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/create_channel">
+    **Description:** Create a new channel in a team.
+
+    **Parameters:**
+    - `team_id` (string, required): The unique identifier of the team. Obtain from get_teams action.
+    - `display_name` (string, required): Name of the channel as displayed in Teams. Must be unique within the team. Max 50 characters.
+    - `description` (string, optional): Optional description explaining the channel's purpose. Visible in channel details. Max 1024 characters.
+    - `membership_type` (string, optional): Channel visibility. Enum: `standard`, `private`. "standard" = visible to all team members, "private" = visible only to specifically added members. Default is `standard`.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_message_replies">
+    **Description:** Get replies to a specific message in a channel.
+
+    **Parameters:**
+    - `team_id` (string, required): The unique identifier of the team. Obtain from get_teams action.
+    - `channel_id` (string, required): The unique identifier of the channel. Obtain from get_channels action.
+    - `message_id` (string, required): The unique identifier of the parent message. Obtain from get_messages action.
+    - `top` (integer, optional): Maximum number of replies to retrieve per page (1-50). Default is `50`.
+    - `skip_token` (string, optional): Pagination token from a previous response. When the response includes @odata.nextLink, extract the $skiptoken parameter value and pass it here to get the next page of results.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/reply_to_message">
+    **Description:** Reply to a message in a Teams channel.
+
+    **Parameters:**
+    - `team_id` (string, required): The unique identifier of the team. Obtain from get_teams action.
+    - `channel_id` (string, required): The unique identifier of the channel. Obtain from get_channels action.
+    - `message_id` (string, required): The unique identifier of the message to reply to. Obtain from get_messages action.
+    - `message` (string, required): The reply content. For HTML, include formatting tags. For text, plain text only.
+    - `content_type` (string, optional): Content format. Enum: `html`, `text`. "text" for plain text, "html" for rich text with formatting. Default is `text`.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/update_meeting">
+    **Description:** Update an existing online meeting.
+
+    **Parameters:**
+    - `meeting_id` (string, required): The unique identifier of the meeting. Obtain from create_meeting or search_online_meetings actions.
+    - `subject` (string, optional): New meeting title.
+    - `startDateTime` (string, optional): New start time in ISO 8601 format with timezone. Example: "2024-01-20T10:00:00-08:00".
+    - `endDateTime` (string, optional): New end time in ISO 8601 format with timezone.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/delete_meeting">
+    **Description:** Delete an online meeting.
+
+    **Parameters:**
+    - `meeting_id` (string, required): The unique identifier of the meeting to delete. Obtain from create_meeting or search_online_meetings actions.
+
+  </Accordion>
 </AccordionGroup>
 
 ## Usage Examples

docs/en/enterprise/integrations/microsoft_word.mdx

@@ -98,6 +98,26 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `file_id` (string, required): The ID of the document to delete.
 
   </Accordion>
+
+  <Accordion title="microsoft_word/copy_document">
+    **Description:** Copy a document to a new location in OneDrive.
+
+    **Parameters:**
+    - `file_id` (string, required): The ID of the document to copy
+    - `name` (string, optional): New name for the copied document
+    - `parent_id` (string, optional): The ID of the destination folder (defaults to root)
+
+  </Accordion>
+
+  <Accordion title="microsoft_word/move_document">
+    **Description:** Move a document to a new location in OneDrive.
+
+    **Parameters:**
+    - `file_id` (string, required): The ID of the document to move
+    - `parent_id` (string, required): The ID of the destination folder
+    - `name` (string, optional): New name for the moved document
+
+  </Accordion>
 </AccordionGroup>
 
 ## Usage Examples

docs/en/guides/coding-tools/agents-md.mdx

@@ -0,0 +1,61 @@
+---
+title: Coding Tools
+description: Use AGENTS.md to guide coding agents and IDEs across your CrewAI projects.
+icon: terminal
+mode: "wide"
+---
+
+## Why AGENTS.md
+
+`AGENTS.md` is a lightweight, repo-local instruction file that gives coding agents consistent, project-specific guidance. Keep it in the project root and treat it as the source of truth for how you want assistants to work: conventions, commands, architecture notes, and guardrails.
+
+## Create a Project with the CLI
+
+Use the CrewAI CLI to scaffold a project, then `AGENTS.md` will be automatically added at the root.
+
+```bash
+# Crew
+crewai create crew my_crew
+
+# Flow
+crewai create flow my_flow
+
+# Tool repository
+crewai tool create my_tool
+```
+
+## Tool Setup: Point Assistants to AGENTS.md
+
+### Codex
+
+Codex can be guided by `AGENTS.md` files placed in your repository. Use them to supply persistent project context such as conventions, commands, and workflow expectations.
+
+### Claude Code
+
+Claude Code stores project memory in `CLAUDE.md`. You can bootstrap it with `/init` and edit it using `/memory`. Claude Code also supports imports inside `CLAUDE.md`, so you can add a single line like `@AGENTS.md` to pull in the shared instructions without duplicating them.
+
+You can simply use:
+
+```bash
+mv AGENTS.md CLAUDE.md
+```
+
+### Gemini CLI and Google Antigravity
+
+Gemini CLI and Antigravity load a project context file (default: `GEMINI.md`) from the repo root and parent directories. You can configure it to read `AGENTS.md` instead (or in addition) by setting `context.fileName` in your Gemini CLI settings. For example, set it to `AGENTS.md` only, or include both `AGENTS.md` and `GEMINI.md` if you want to keep each tool’s format.
+
+You can simply use:
+
+```bash
+mv AGENTS.md GEMINI.md
+```
+
+### Cursor
+
+Cursor supports `AGENTS.md` as a project instruction file. Place it at the project root to provide guidance for Cursor’s coding assistant.
+
+### Windsurf
+
+Claude Code provides an official integration with Windsurf. If you use Claude Code inside Windsurf, follow the Claude Code guidance above and import `AGENTS.md` from `CLAUDE.md`.
+
+If you are using Windsurf’s native assistant, configure its project rules or instructions feature (if available) to read from `AGENTS.md` or paste the contents directly.

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

@@ -73,6 +73,8 @@ When this flow runs, it will:
 | `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) |
+| `learn` | `bool` | No | Enable HITL learning: distill lessons from feedback and pre-review future output. Default `False`. See [Learning from Feedback](#learning-from-feedback) |
+| `learn_limit` | `int` | No | Max past lessons to recall for pre-review. Default `5` |
 
 ### Basic Usage (No Routing)
 
@@ -96,33 +98,43 @@ def handle_feedback(self, result):
 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..."
+from crewai.flow.flow import Flow, start, listen, or_
+from crewai.flow.human_feedback import human_feedback
 
-@listen("approved")
-def publish(self, result):
-    print(f"Publishing! User said: {result.feedback}")
+class ReviewFlow(Flow):
+    @start()
+    def generate_content(self):
+        return "Draft blog post content here..."
 
-@listen("rejected")
-def discard(self, result):
-    print(f"Discarding. Reason: {result.feedback}")
+    @human_feedback(
+        message="Do you approve this content for publication?",
+        emit=["approved", "rejected", "needs_revision"],
+        llm="gpt-4o-mini",
+        default_outcome="needs_revision",
+    )
+    @listen(or_("generate_content", "needs_revision"))
+    def review_content(self):
+        return "Draft blog post content here..."
 
-@listen("needs_revision")
-def revise(self, result):
-    print(f"Revising based on: {result.feedback}")
+    @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}")
 ```
 
+When the human says something like "needs more detail", the LLM collapses that to `"needs_revision"`, which triggers `review_content` again via `or_()` — creating a revision loop. The loop continues until the outcome is `"approved"` or `"rejected"`.
+
 <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>
 
+<Warning>
+A `@start()` method only runs once at the beginning of the flow. If you need a revision loop, separate the start method from the review method and use `@listen(or_("trigger", "revision_outcome"))` on the review method to enable the self-loop.
+</Warning>
+
 ## HumanFeedbackResult
 
 The `HumanFeedbackResult` dataclass contains all information about a human feedback interaction:
@@ -186,127 +198,183 @@ Each `HumanFeedbackResult` is appended to `human_feedback_history`, so multiple
 
 ## Complete Example: Content Approval Workflow
 
-Here's a full example implementing a content review and approval workflow:
+Here's a full example implementing a content review and approval workflow with a revision loop:
 
 <CodeGroup>
 
 ```python Code
-from crewai.flow.flow import Flow, start, listen
+from crewai.flow.flow import Flow, start, listen, or_
 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
+    status: str = "pending"
 
 
 class ContentApprovalFlow(Flow[ContentState]):
-    """A flow that generates content and gets human approval."""
+    """A flow that generates content and loops until the human approves."""
 
     @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}..."
+    def generate_draft(self):
+        self.state.draft = "# AI Safety\n\nThis is a draft about AI Safety..."
         return self.state.draft
 
-    @listen(generate_draft)
     @human_feedback(
-        message="Please review this draft. Reply 'approved', 'rejected', or provide revision feedback:",
+        message="Please review this draft. Approve, reject, or describe what needs changing:",
         emit=["approved", "rejected", "needs_revision"],
         llm="gpt-4o-mini",
         default_outcome="needs_revision",
     )
-    def review_draft(self, draft):
-        return draft
+    @listen(or_("generate_draft", "needs_revision"))
+    def review_draft(self):
+        self.state.revision_count += 1
+        return f"{self.state.draft} (v{self.state.revision_count})"
 
     @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}")
+        self.state.status = "published"
+        print(f"Content approved and published! Reviewer said: {result.feedback}")
         return "published"
 
     @listen("rejected")
     def handle_rejection(self, result: HumanFeedbackResult):
-        print("\n❌ Content rejected")
-        print(f"Reason: {result.feedback}")
+        self.state.status = "rejected"
+        print(f"Content rejected. 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}")
+print(f"\nFlow completed. Status: {flow.state.status}, Reviews: {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... (v1)
+==================================================
+
+Please review this draft. Approve, reject, or describe what needs changing:
+(Press Enter to skip, or type your feedback)
+
+Your feedback: Needs more detail on alignment research
 
 ==================================================
 OUTPUT FOR REVIEW:
 ==================================================
 # AI Safety
 
-This is a draft about AI Safety...
+This is a draft about AI Safety... (v2)
 ==================================================
 
-Please review this draft. Reply 'approved', 'rejected', or provide revision feedback:
+Please review this draft. Approve, reject, or describe what needs changing:
 (Press Enter to skip, or type your feedback)
 
 Your feedback: Looks good, approved!
 
-✅ Content approved and published!
-Reviewer comment: Looks good, approved!
+Content approved and published! Reviewer said: Looks good, approved!
 
-Flow completed. Revisions requested: 0
+Flow completed. Status: published, Reviews: 2
 ```
 
 </CodeGroup>
 
+The key pattern is `@listen(or_("generate_draft", "needs_revision"))` — the review method listens to both the initial trigger and its own revision outcome, creating a self-loop that repeats until the human approves or rejects.
+
 ## Combining with Other Decorators
 
-The `@human_feedback` decorator works with other flow decorators. Place it as the innermost decorator (closest to the function):
+The `@human_feedback` decorator works with `@start()`, `@listen()`, and `or_()`. Both decorator orderings work — the framework propagates attributes in both directions — but the recommended patterns are:
 
 ```python Code
-# Correct: @human_feedback is innermost (closest to the function)
+# One-shot review at the start of a flow (no self-loop)
 @start()
-@human_feedback(message="Review this:")
+@human_feedback(message="Review this:", emit=["approved", "rejected"], llm="gpt-4o-mini")
 def my_start_method(self):
     return "content"
 
+# Linear review on a listener (no self-loop)
 @listen(other_method)
-@human_feedback(message="Review this too:")
+@human_feedback(message="Review this too:", emit=["good", "bad"], llm="gpt-4o-mini")
 def my_listener(self, data):
     return f"processed: {data}"
+
+# Self-loop: review that can loop back for revisions
+@human_feedback(message="Approve or revise?", emit=["approved", "revise"], llm="gpt-4o-mini")
+@listen(or_("upstream_method", "revise"))
+def review_with_loop(self):
+    return "content for review"
 ```
 
-<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>
+### Self-loop pattern
+
+To create a revision loop, the review method must listen to **both** an upstream trigger and its own revision outcome using `or_()`:
+
+```python Code
+@start()
+def generate(self):
+    return "initial draft"
+
+@human_feedback(
+    message="Approve or request changes?",
+    emit=["revise", "approved"],
+    llm="gpt-4o-mini",
+    default_outcome="approved",
+)
+@listen(or_("generate", "revise"))
+def review(self):
+    return "content"
+
+@listen("approved")
+def publish(self):
+    return "published"
+```
+
+When the outcome is `"revise"`, the flow routes back to `review` (because it listens to `"revise"` via `or_()`). When the outcome is `"approved"`, the flow continues to `publish`. This works because the flow engine exempts routers from the "fire once" rule, allowing them to re-execute on each loop iteration.
+
+### Chained routers
+
+A listener triggered by one router's outcome can itself be a router:
+
+```python Code
+@start()
+def generate(self):
+    return "draft content"
+
+@human_feedback(message="First review:", emit=["approved", "rejected"], llm="gpt-4o-mini")
+@listen("generate")
+def first_review(self):
+    return "draft content"
+
+@human_feedback(message="Final review:", emit=["publish", "hold"], llm="gpt-4o-mini")
+@listen("approved")
+def final_review(self, prev):
+    return "final content"
+
+@listen("publish")
+def on_publish(self, prev):
+    return "published"
+
+@listen("hold")
+def on_hold(self, prev):
+    return "held for later"
+```
+
+### Limitations
+
+- **`@start()` methods run once**: A `@start()` method cannot self-loop. If you need a revision cycle, use a separate `@start()` method as the entry point and put the `@human_feedback` on a `@listen()` method.
+- **No `@start()` + `@listen()` on the same method**: This is a Flow framework constraint. A method is either a start point or a listener, not both.
 
 ## Best Practices
 
 ### 1. Write Clear Request Messages
 
-The `request` parameter is what the human sees. Make it actionable:
+The `message` parameter is what the human sees. Make it actionable:
 
 ```python Code
 # ✅ Good - clear and actionable
@@ -514,9 +582,9 @@ class ContentPipeline(Flow):
     @start()
     @human_feedback(
         message="Approve this content for publication?",
-        emit=["approved", "rejected", "needs_revision"],
+        emit=["approved", "rejected"],
         llm="gpt-4o-mini",
-        default_outcome="needs_revision",
+        default_outcome="rejected",
         provider=SlackNotificationProvider("#content-reviews"),
     )
     def generate_content(self):
@@ -532,11 +600,6 @@ class ContentPipeline(Flow):
         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():
@@ -576,6 +639,64 @@ If you're using an async web framework (FastAPI, aiohttp, Slack Bolt async mode)
 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
 
+## Learning from Feedback
+
+The `learn=True` parameter enables a feedback loop between human reviewers and the memory system. When enabled, the system progressively improves its outputs by learning from past human corrections.
+
+### How It Works
+
+1. **After feedback**: The LLM extracts generalizable lessons from the output + feedback and stores them in memory with `source="hitl"`. If the feedback is just approval (e.g. "looks good"), nothing is stored.
+2. **Before next review**: Past HITL lessons are recalled from memory and applied by the LLM to improve the output before the human sees it.
+
+Over time, the human sees progressively better pre-reviewed output because each correction informs future reviews.
+
+### Example
+
+```python Code
+class ArticleReviewFlow(Flow):
+    @start()
+    def generate_article(self):
+        return self.crew.kickoff(inputs={"topic": "AI Safety"}).raw
+
+    @human_feedback(
+        message="Review this article draft:",
+        emit=["approved", "needs_revision"],
+        llm="gpt-4o-mini",
+        learn=True,  # enable HITL learning
+    )
+    @listen(or_("generate_article", "needs_revision"))
+    def review_article(self):
+        return self.last_human_feedback.output if self.last_human_feedback else "article draft"
+
+    @listen("approved")
+    def publish(self):
+        print(f"Publishing: {self.last_human_feedback.output}")
+```
+
+**First run**: The human sees the raw output and says "Always include citations for factual claims." The lesson is distilled and stored in memory.
+
+**Second run**: The system recalls the citation lesson, pre-reviews the output to add citations, then shows the improved version. The human's job shifts from "fix everything" to "catch what the system missed."
+
+### Configuration
+
+| Parameter | Default | Description |
+|-----------|---------|-------------|
+| `learn` | `False` | Enable HITL learning |
+| `learn_limit` | `5` | Max past lessons to recall for pre-review |
+
+### Key Design Decisions
+
+- **Same LLM for everything**: The `llm` parameter on the decorator is shared by outcome collapsing, lesson distillation, and pre-review. No need to configure multiple models.
+- **Structured output**: Both distillation and pre-review use function calling with Pydantic models when the LLM supports it, falling back to text parsing otherwise.
+- **Non-blocking storage**: Lessons are stored via `remember_many()` which runs in a background thread -- the flow continues immediately.
+- **Graceful degradation**: If the LLM fails during distillation, nothing is stored. If it fails during pre-review, the raw output is shown. Neither failure blocks the flow.
+- **No scope/categories needed**: When storing lessons, only `source` is passed. The encoding pipeline infers scope, categories, and importance automatically.
+
+<Note>
+`learn=True` requires the Flow to have memory available. Flows get memory automatically by default, but if you've disabled it with `_skip_auto_memory`, HITL learning will be silently skipped.
+</Note>
+
+
 ## Related Documentation
 
 - [Flows Overview](/en/concepts/flows) - Learn about CrewAI Flows
@@ -583,3 +704,4 @@ If you're using an async web framework (FastAPI, aiohttp, Slack Bolt async mode)
 - [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
+- [Memory](/en/concepts/memory) - The unified memory system used by HITL learning

docs/en/tools/database-data/nl2sqltool.mdx

@@ -15,6 +15,29 @@ Along with that provides the ability for the Agent to update the database based
 
 **Attention**: Make sure that the Agent has access to a Read-Replica or that is okay for the Agent to run insert/update queries on the database.
 
+## Security Model
+
+`NL2SQLTool` is an execution-capable tool. It runs model-generated SQL directly against the configured database connection.
+
+This means risk depends on your deployment choices:
+
+- Which credentials you provide in `db_uri`
+- Whether untrusted input can influence prompts
+- Whether you add tool-call guardrails before execution
+
+If you route untrusted input to agents using this tool, treat it as a high-risk integration.
+
+## Hardening Recommendations
+
+Use all of the following in production:
+
+- Use a read-only database user whenever possible
+- Prefer a read replica for analytics/retrieval workloads
+- Grant least privilege (no superuser/admin roles, no file/system-level capabilities)
+- Apply database-side resource limits (statement timeout, lock timeout, cost/row limits)
+- Add `before_tool_call` hooks to enforce allowed query patterns
+- Enable query logging and alerting for destructive statements
+
 ## Requirements
 
 - SqlAlchemy

docs/ko/enterprise/features/flow-hitl-management.mdx

@@ -38,22 +38,21 @@ CrewAI Enterprise는 AI 워크플로우를 협업적인 인간-AI 프로세스
 `@human_feedback` 데코레이터를 사용하여 Flow 내에 인간 검토 체크포인트를 구성합니다. 실행이 검토 포인트에 도달하면 시스템이 일시 중지되고, 담당자에게 이메일로 알리며, 응답을 기다립니다.
 
 ```python
-from crewai.flow.flow import Flow, start, listen
+from crewai.flow.flow import Flow, start, listen, or_
 from crewai.flow.human_feedback import human_feedback, HumanFeedbackResult
 
 class ContentApprovalFlow(Flow):
     @start()
     def generate_content(self):
-        # AI가 콘텐츠 생성
         return "Q1 캠페인용 마케팅 카피 생성..."
 
-    @listen(generate_content)
     @human_feedback(
         message="브랜드 준수를 위해 이 콘텐츠를 검토해 주세요:",
         emit=["approved", "rejected", "needs_revision"],
     )
-    def review_content(self, content):
-        return content
+    @listen(or_("generate_content", "needs_revision"))
+    def review_content(self):
+        return "검토용 마케팅 카피..."
 
     @listen("approved")
     def publish_content(self, result: HumanFeedbackResult):
@@ -62,10 +61,6 @@ class ContentApprovalFlow(Flow):
     @listen("rejected")
     def archive_content(self, result: HumanFeedbackResult):
         print(f"콘텐츠 거부됨. 사유: {result.feedback}")
-
-    @listen("needs_revision")
-    def revise_content(self, result: HumanFeedbackResult):
-        print(f"수정 요청: {result.feedback}")
 ```
 
 완전한 구현 세부 사항은 [Flow에서 인간 피드백](/ko/learn/human-feedback-in-flows) 가이드를 참조하세요.

docs/ko/enterprise/guides/deploy-to-amp.mdx

@@ -176,6 +176,11 @@ Crew를 GitHub 저장소에 푸시해야 합니다. 아직 Crew를 만들지 않
       ![Set Environment Variables](/images/enterprise/set-env-variables.png)
     </Frame>
 
+    <Info>
+      프라이빗 Python 패키지를 사용하시나요? 여기에 레지스트리 자격 증명도 추가해야 합니다.
+      필요한 변수는 [프라이빗 패키지 레지스트리](/ko/enterprise/guides/private-package-registry)를 참조하세요.
+    </Info>
+
   </Step>
 
   <Step title="Crew 배포하기">

docs/ko/enterprise/guides/prepare-for-deployment.mdx

@@ -256,6 +256,12 @@ Crews와 Flows 모두 `src/project_name/main.py`에 진입점이 있습니다:
 1. **LLM API 키** (OpenAI, Anthropic, Google 등)
 2. **도구 API 키** - 외부 도구를 사용하는 경우 (Serper 등)
 
+<Info>
+  프로젝트가 **프라이빗 PyPI 레지스트리**의 패키지에 의존하는 경우, 레지스트리 인증 자격 증명도
+  환경 변수로 구성해야 합니다. 자세한 내용은
+  [프라이빗 패키지 레지스트리](/ko/enterprise/guides/private-package-registry) 가이드를 참조하세요.
+</Info>
+
 <Tip>
   구성 문제를 조기에 발견하기 위해 배포 전에 동일한 환경 변수로
   로컬에서 프로젝트를 테스트하세요.

docs/ko/enterprise/guides/private-package-registry.mdx

@@ -0,0 +1,261 @@
+---
+title: "프라이빗 패키지 레지스트리"
+description: "CrewAI AMP에서 인증된 PyPI 레지스트리의 프라이빗 Python 패키지 설치하기"
+icon: "lock"
+mode: "wide"
+---
+
+<Note>
+  이 가이드는 CrewAI AMP에 배포할 때 프라이빗 PyPI 레지스트리(Azure DevOps Artifacts, GitHub Packages,
+  GitLab, AWS CodeArtifact 등)에서 Python 패키지를 설치하도록 CrewAI 프로젝트를 구성하는 방법을 다룹니다.
+</Note>
+
+## 이 가이드가 필요한 경우
+
+프로젝트가 공개 PyPI가 아닌 프라이빗 레지스트리에 호스팅된 내부 또는 독점 Python 패키지에
+의존하는 경우, 다음을 수행해야 합니다:
+
+1. UV에 패키지를 **어디서** 찾을지 알려줍니다 (index URL)
+2. UV에 **어떤** 패키지가 해당 index에서 오는지 알려줍니다 (source 매핑)
+3. UV가 설치 중에 인증할 수 있도록 **자격 증명**을 제공합니다
+
+CrewAI AMP는 의존성 해결 및 설치에 [UV](https://docs.astral.sh/uv/)를 사용합니다.
+UV는 `pyproject.toml` 구성과 자격 증명용 환경 변수를 결합하여 인증된 프라이빗 레지스트리를 지원합니다.
+
+## 1단계: pyproject.toml 구성
+
+`pyproject.toml`에서 세 가지 요소가 함께 작동합니다:
+
+### 1a. 의존성 선언
+
+프라이빗 패키지를 다른 의존성과 마찬가지로 `[project.dependencies]`에 추가합니다:
+
+```toml
+[project]
+dependencies = [
+    "crewai[tools]>=0.100.1,<1.0.0",
+    "my-private-package>=1.2.0",
+]
+```
+
+### 1b. index 정의
+
+프라이빗 레지스트리를 `[[tool.uv.index]]` 아래에 명명된 index로 등록합니다:
+
+```toml
+[[tool.uv.index]]
+name = "my-private-registry"
+url = "https://pkgs.dev.azure.com/my-org/_packaging/my-feed/pypi/simple/"
+explicit = true
+```
+
+<Info>
+  `name` 필드는 중요합니다 — UV는 이를 사용하여 인증을 위한 환경 변수 이름을
+  구성합니다 (아래 [2단계](#2단계-인증-자격-증명-설정)를 참조하세요).
+
+  `explicit = true`를 설정하면 UV가 모든 패키지에 대해 이 index를 검색하지 않습니다 —
+  `[tool.uv.sources]`에서 명시적으로 매핑한 패키지만 검색합니다. 이렇게 하면 프라이빗
+  레지스트리에 대한 불필요한 쿼리를 방지하고 의존성 혼동 공격을 차단할 수 있습니다.
+</Info>
+
+### 1c. 패키지를 index에 매핑
+
+`[tool.uv.sources]`를 사용하여 프라이빗 index에서 해결해야 할 패키지를 UV에 알려줍니다:
+
+```toml
+[tool.uv.sources]
+my-private-package = { index = "my-private-registry" }
+```
+
+### 전체 예시
+
+```toml
+[project]
+name = "my-crew-project"
+version = "0.1.0"
+requires-python = ">=3.10,<=3.13"
+dependencies = [
+    "crewai[tools]>=0.100.1,<1.0.0",
+    "my-private-package>=1.2.0",
+]
+
+[tool.crewai]
+type = "crew"
+
+[[tool.uv.index]]
+name = "my-private-registry"
+url = "https://pkgs.dev.azure.com/my-org/_packaging/my-feed/pypi/simple/"
+explicit = true
+
+[tool.uv.sources]
+my-private-package = { index = "my-private-registry" }
+```
+
+`pyproject.toml`을 업데이트한 후 lock 파일을 다시 생성합니다:
+
+```bash
+uv lock
+```
+
+<Warning>
+  업데이트된 `uv.lock`을 항상 `pyproject.toml` 변경 사항과 함께 커밋하세요.
+  lock 파일은 배포에 필수입니다 — [배포 준비하기](/ko/enterprise/guides/prepare-for-deployment)를 참조하세요.
+</Warning>
+
+## 2단계: 인증 자격 증명 설정
+
+UV는 `pyproject.toml`에서 정의한 index 이름을 기반으로 한 명명 규칙을 따르는
+환경 변수를 사용하여 프라이빗 index에 인증합니다:
+
+```
+UV_INDEX_{UPPER_NAME}_USERNAME
+UV_INDEX_{UPPER_NAME}_PASSWORD
+```
+
+여기서 `{UPPER_NAME}`은 index 이름을 **대문자**로 변환하고 **하이픈을 언더스코어로 대체**한 것입니다.
+
+예를 들어, `my-private-registry`라는 이름의 index는 다음을 사용합니다:
+
+| 변수 | 값 |
+|------|-----|
+| `UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME` | 레지스트리 사용자 이름 또는 토큰 이름 |
+| `UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD` | 레지스트리 비밀번호 또는 토큰/PAT |
+
+<Warning>
+  이 환경 변수는 CrewAI AMP **환경 변수** 설정을 통해 **반드시** 추가해야 합니다 —
+  전역적으로 또는 배포 수준에서. `.env` 파일에 설정하거나 프로젝트에 하드코딩할 수 없습니다.
+
+  아래 [AMP에서 환경 변수 설정](#amp에서-환경-변수-설정)을 참조하세요.
+</Warning>
+
+## 레지스트리 제공업체 참조
+
+아래 표는 일반적인 레지스트리 제공업체의 index URL 형식과 자격 증명 값을 보여줍니다.
+자리 표시자 값을 실제 조직 및 피드 세부 정보로 대체하세요.
+
+| 제공업체 | Index URL | 사용자 이름 | 비밀번호 |
+|---------|-----------|-----------|---------|
+| **Azure DevOps Artifacts** | `https://pkgs.dev.azure.com/{org}/_packaging/{feed}/pypi/simple/` | 비어 있지 않은 임의의 문자열 (예: `token`) | Packaging Read 범위의 Personal Access Token (PAT) |
+| **GitHub Packages** | `https://pypi.pkg.github.com/{owner}/simple/` | GitHub 사용자 이름 | `read:packages` 범위의 Personal Access Token (classic) |
+| **GitLab Package Registry** | `https://gitlab.com/api/v4/projects/{project_id}/packages/pypi/simple/` | `__token__` | `read_api` 범위의 Project 또는 Personal Access Token |
+| **AWS CodeArtifact** | `aws codeartifact get-repository-endpoint`의 URL 사용 | `aws` | `aws codeartifact get-authorization-token`의 토큰 |
+| **Google Artifact Registry** | `https://{region}-python.pkg.dev/{project}/{repo}/simple/` | `_json_key_base64` | Base64로 인코딩된 서비스 계정 키 |
+| **JFrog Artifactory** | `https://{instance}.jfrog.io/artifactory/api/pypi/{repo}/simple/` | 사용자 이름 또는 이메일 | API 키 또는 ID 토큰 |
+| **자체 호스팅 (devpi, Nexus 등)** | 레지스트리의 simple API URL | 레지스트리 사용자 이름 | 레지스트리 비밀번호 |
+
+<Tip>
+  **AWS CodeArtifact**의 경우 인증 토큰이 주기적으로 만료됩니다.
+  만료되면 `UV_INDEX_*_PASSWORD` 값을 갱신해야 합니다.
+  CI/CD 파이프라인에서 이를 자동화하는 것을 고려하세요.
+</Tip>
+
+## AMP에서 환경 변수 설정
+
+프라이빗 레지스트리 자격 증명은 CrewAI AMP에서 환경 변수로 구성해야 합니다.
+두 가지 옵션이 있습니다:
+
+<Tabs>
+  <Tab title="웹 인터페이스">
+    1. [CrewAI AMP](https://app.crewai.com)에 로그인합니다
+    2. 자동화로 이동합니다
+    3. **Environment Variables** 탭을 엽니다
+    4. 각 변수 (`UV_INDEX_*_USERNAME` 및 `UV_INDEX_*_PASSWORD`)에 값을 추가합니다
+
+    자세한 내용은 [AMP에 배포하기 — 환경 변수 설정하기](/ko/enterprise/guides/deploy-to-amp#환경-변수-설정하기) 단계를 참조하세요.
+  </Tab>
+  <Tab title="CLI 배포">
+    `crewai deploy create`를 실행하기 전에 로컬 `.env` 파일에 변수를 추가합니다.
+    CLI가 이를 안전하게 플랫폼으로 전송합니다:
+
+    ```bash
+    # .env
+    OPENAI_API_KEY=sk-...
+    UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME=token
+    UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD=your-pat-here
+    ```
+
+    ```bash
+    crewai deploy create
+    ```
+  </Tab>
+</Tabs>
+
+<Warning>
+  자격 증명을 저장소에 **절대** 커밋하지 마세요. 모든 비밀 정보에는 AMP 환경 변수를 사용하세요.
+  `.env` 파일은 `.gitignore`에 포함되어야 합니다.
+</Warning>
+
+기존 배포의 자격 증명을 업데이트하려면 [Crew 업데이트하기 — 환경 변수](/ko/enterprise/guides/update-crew)를 참조하세요.
+
+## 전체 동작 흐름
+
+CrewAI AMP가 자동화를 빌드할 때, 해결 흐름은 다음과 같이 작동합니다:
+
+<Steps>
+  <Step title="빌드 시작">
+    AMP가 저장소를 가져오고 `pyproject.toml`과 `uv.lock`을 읽습니다.
+  </Step>
+  <Step title="UV가 의존성 해결">
+    UV가 `[tool.uv.sources]`를 읽어 각 패키지가 어떤 index에서 와야 하는지 결정합니다.
+  </Step>
+  <Step title="UV가 인증">
+    각 프라이빗 index에 대해 UV가 AMP에서 구성한 환경 변수에서
+    `UV_INDEX_{NAME}_USERNAME`과 `UV_INDEX_{NAME}_PASSWORD`를 조회합니다.
+  </Step>
+  <Step title="패키지 설치">
+    UV가 공개(PyPI) 및 프라이빗(레지스트리) 패키지를 모두 다운로드하고 설치합니다.
+  </Step>
+  <Step title="자동화 실행">
+    모든 의존성이 사용 가능한 상태에서 crew 또는 flow가 시작됩니다.
+  </Step>
+</Steps>
+
+## 문제 해결
+
+### 빌드 중 인증 오류
+
+**증상**: 프라이빗 패키지를 해결할 때 `401 Unauthorized` 또는 `403 Forbidden`으로 빌드가 실패합니다.
+
+**확인사항**:
+- `UV_INDEX_*` 환경 변수 이름이 index 이름과 정확히 일치하는지 확인합니다 (대문자, 하이픈 -> 언더스코어)
+- 자격 증명이 로컬 `.env`뿐만 아니라 AMP 환경 변수에 설정되어 있는지 확인합니다
+- 토큰/PAT에 패키지 피드에 필요한 읽기 권한이 있는지 확인합니다
+- 토큰이 만료되지 않았는지 확인합니다 (특히 AWS CodeArtifact의 경우)
+
+### 패키지를 찾을 수 없음
+
+**증상**: `No matching distribution found for my-private-package`.
+
+**확인사항**:
+- `pyproject.toml`의 index URL이 `/simple/`로 끝나는지 확인합니다
+- `[tool.uv.sources]` 항목이 올바른 패키지 이름을 올바른 index 이름에 매핑하는지 확인합니다
+- 패키지가 실제로 프라이빗 레지스트리에 게시되어 있는지 확인합니다
+- 동일한 자격 증명으로 로컬에서 `uv lock`을 실행하여 해결이 작동하는지 확인합니다
+
+### Lock 파일 충돌
+
+**증상**: 프라이빗 index를 추가한 후 `uv lock`이 실패하거나 예상치 못한 결과를 생성합니다.
+
+**해결책**: 로컬에서 자격 증명을 설정하고 다시 생성합니다:
+
+```bash
+export UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME=token
+export UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD=your-pat
+uv lock
+```
+
+그런 다음 업데이트된 `uv.lock`을 커밋합니다.
+
+## 관련 가이드
+
+<CardGroup cols={3}>
+  <Card title="배포 준비하기" icon="clipboard-check" href="/ko/enterprise/guides/prepare-for-deployment">
+    배포 전에 프로젝트 구조와 의존성을 확인합니다.
+  </Card>
+  <Card title="AMP에 배포하기" icon="rocket" href="/ko/enterprise/guides/deploy-to-amp">
+    crew 또는 flow를 배포하고 환경 변수를 구성합니다.
+  </Card>
+  <Card title="Crew 업데이트하기" icon="arrows-rotate" href="/ko/enterprise/guides/update-crew">
+    환경 변수를 업데이트하고 실행 중인 배포에 변경 사항을 푸시합니다.
+  </Card>
+</CardGroup>

docs/ko/enterprise/integrations/google_contacts.mdx

@@ -200,6 +200,25 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `clientData` (array, 선택사항): 클라이언트별 데이터. 각 항목은 `key` (string)와 `value` (string)가 있는 객체.
 
   </Accordion>
+
+  <Accordion title="google_contacts/update_contact_group">
+    **설명:** 연락처 그룹의 정보를 업데이트합니다.
+
+    **매개변수:**
+    - `resourceName` (string, 필수): 연락처 그룹의 리소스 이름 (예: 'contactGroups/myContactGroup').
+    - `name` (string, 필수): 연락처 그룹의 이름.
+    - `clientData` (array, 선택사항): 클라이언트별 데이터. 각 항목은 `key` (string)와 `value` (string)가 있는 객체.
+
+  </Accordion>
+
+  <Accordion title="google_contacts/delete_contact_group">
+    **설명:** 연락처 그룹을 삭제합니다.
+
+    **매개변수:**
+    - `resourceName` (string, 필수): 삭제할 연락처 그룹의 리소스 이름 (예: 'contactGroups/myContactGroup').
+    - `deleteContacts` (boolean, 선택사항): 그룹 내 연락처도 삭제할지 여부. 기본값: false
+
+  </Accordion>
 </AccordionGroup>
 
 ## 사용 예제

docs/ko/enterprise/integrations/google_docs.mdx

@@ -131,6 +131,297 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `endIndex` (integer, 필수): 범위의 끝 인덱스.
 
   </Accordion>
+
+  <Accordion title="google_docs/create_document_with_content">
+    **설명:** 내용이 포함된 새 Google 문서를 한 번에 만듭니다.
+
+    **매개변수:**
+    - `title` (string, 필수): 새 문서의 제목. 문서 상단과 Google Drive에 표시됩니다.
+    - `content` (string, 선택사항): 문서에 삽입할 텍스트 내용. 새 단락에는 `\n`을 사용하세요.
+
+  </Accordion>
+
+  <Accordion title="google_docs/append_text">
+    **설명:** Google 문서의 끝에 텍스트를 추가합니다. 인덱스를 지정할 필요 없이 자동으로 문서 끝에 삽입됩니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): create_document 응답 또는 URL에서 가져온 문서 ID.
+    - `text` (string, 필수): 문서 끝에 추가할 텍스트. 새 단락에는 `\n`을 사용하세요.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_bold">
+    **설명:** Google 문서에서 텍스트를 굵게 만들거나 굵게 서식을 제거합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
+    - `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
+    - `bold` (boolean, 필수): 굵게 만들려면 `true`, 굵게를 제거하려면 `false`로 설정.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_italic">
+    **설명:** Google 문서에서 텍스트를 기울임꼴로 만들거나 기울임꼴 서식을 제거합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
+    - `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
+    - `italic` (boolean, 필수): 기울임꼴로 만들려면 `true`, 기울임꼴을 제거하려면 `false`로 설정.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_underline">
+    **설명:** Google 문서에서 텍스트에 밑줄 서식을 추가하거나 제거합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
+    - `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
+    - `underline` (boolean, 필수): 밑줄을 추가하려면 `true`, 밑줄을 제거하려면 `false`로 설정.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_strikethrough">
+    **설명:** Google 문서에서 텍스트에 취소선 서식을 추가하거나 제거합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
+    - `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
+    - `strikethrough` (boolean, 필수): 취소선을 추가하려면 `true`, 제거하려면 `false`로 설정.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_font_size">
+    **설명:** Google 문서에서 텍스트의 글꼴 크기를 변경합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
+    - `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
+    - `fontSize` (number, 필수): 포인트 단위의 글꼴 크기. 일반적인 크기: 10, 11, 12, 14, 16, 18, 24, 36.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_color">
+    **설명:** Google 문서에서 RGB 값(0-1 스케일)을 사용하여 텍스트 색상을 변경합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 서식을 지정할 텍스트의 시작 위치.
+    - `endIndex` (integer, 필수): 서식을 지정할 텍스트의 끝 위치 (배타적).
+    - `red` (number, 필수): 빨강 구성 요소 (0-1). 예: `1`은 완전한 빨강.
+    - `green` (number, 필수): 초록 구성 요소 (0-1). 예: `0.5`는 절반 초록.
+    - `blue` (number, 필수): 파랑 구성 요소 (0-1). 예: `0`은 파랑 없음.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_hyperlink">
+    **설명:** Google 문서에서 기존 텍스트를 클릭 가능한 하이퍼링크로 변환합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 링크로 만들 텍스트의 시작 위치.
+    - `endIndex` (integer, 필수): 링크로 만들 텍스트의 끝 위치 (배타적).
+    - `url` (string, 필수): 링크가 가리킬 URL. 예: `"https://example.com"`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/apply_heading_style">
+    **설명:** Google 문서에서 텍스트 범위에 제목 또는 단락 스타일을 적용합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 스타일을 적용할 단락의 시작 위치.
+    - `endIndex` (integer, 필수): 스타일을 적용할 단락의 끝 위치.
+    - `style` (string, 필수): 적용할 스타일. 옵션: `NORMAL_TEXT`, `TITLE`, `SUBTITLE`, `HEADING_1`, `HEADING_2`, `HEADING_3`, `HEADING_4`, `HEADING_5`, `HEADING_6`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_paragraph_alignment">
+    **설명:** Google 문서에서 단락의 텍스트 정렬을 설정합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 정렬할 단락의 시작 위치.
+    - `endIndex` (integer, 필수): 정렬할 단락의 끝 위치.
+    - `alignment` (string, 필수): 텍스트 정렬. 옵션: `START` (왼쪽), `CENTER`, `END` (오른쪽), `JUSTIFIED`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_line_spacing">
+    **설명:** Google 문서에서 단락의 줄 간격을 설정합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 단락의 시작 위치.
+    - `endIndex` (integer, 필수): 단락의 끝 위치.
+    - `lineSpacing` (number, 필수): 백분율로 나타낸 줄 간격. `100` = 단일, `115` = 1.15배, `150` = 1.5배, `200` = 이중.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_paragraph_bullets">
+    **설명:** Google 문서에서 단락을 글머리 기호 또는 번호 매기기 목록으로 변환합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 목록으로 변환할 단락의 시작 위치.
+    - `endIndex` (integer, 필수): 목록으로 변환할 단락의 끝 위치.
+    - `bulletPreset` (string, 필수): 글머리 기호/번호 매기기 스타일. 옵션: `BULLET_DISC_CIRCLE_SQUARE`, `BULLET_DIAMONDX_ARROW3D_SQUARE`, `BULLET_CHECKBOX`, `BULLET_ARROW_DIAMOND_DISC`, `BULLET_STAR_CIRCLE_SQUARE`, `NUMBERED_DECIMAL_ALPHA_ROMAN`, `NUMBERED_DECIMAL_ALPHA_ROMAN_PARENS`, `NUMBERED_DECIMAL_NESTED`, `NUMBERED_UPPERALPHA_ALPHA_ROMAN`, `NUMBERED_UPPERROMAN_UPPERALPHA_DECIMAL`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_paragraph_bullets">
+    **설명:** Google 문서에서 단락의 글머리 기호 또는 번호 매기기를 제거합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `startIndex` (integer, 필수): 목록 단락의 시작 위치.
+    - `endIndex` (integer, 필수): 목록 단락의 끝 위치.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_with_content">
+    **설명:** Google 문서에 내용이 포함된 표를 한 번에 삽입합니다. 내용은 2D 배열로 제공하세요.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `rows` (integer, 필수): 표의 행 수.
+    - `columns` (integer, 필수): 표의 열 수.
+    - `index` (integer, 선택사항): 표를 삽입할 위치. 제공하지 않으면 문서 끝에 삽입됩니다.
+    - `content` (array, 필수): 2D 배열로 된 표 내용. 각 내부 배열은 행입니다. 예: `[["Year", "Revenue"], ["2023", "$43B"], ["2024", "$45B"]]`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_row">
+    **설명:** 기존 표의 참조 셀 위 또는 아래에 새 행을 삽입합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `tableStartIndex` (integer, 필수): 표의 시작 인덱스. get_document에서 가져오세요.
+    - `rowIndex` (integer, 필수): 참조 셀의 행 인덱스 (0 기반).
+    - `columnIndex` (integer, 선택사항): 참조 셀의 열 인덱스 (0 기반). 기본값: `0`.
+    - `insertBelow` (boolean, 선택사항): `true`이면 참조 행 아래에, `false`이면 위에 삽입. 기본값: `true`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_column">
+    **설명:** 기존 표의 참조 셀 왼쪽 또는 오른쪽에 새 열을 삽입합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
+    - `rowIndex` (integer, 선택사항): 참조 셀의 행 인덱스 (0 기반). 기본값: `0`.
+    - `columnIndex` (integer, 필수): 참조 셀의 열 인덱스 (0 기반).
+    - `insertRight` (boolean, 선택사항): `true`이면 오른쪽에, `false`이면 왼쪽에 삽입. 기본값: `true`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_table_row">
+    **설명:** Google 문서의 기존 표에서 행을 삭제합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
+    - `rowIndex` (integer, 필수): 삭제할 행 인덱스 (0 기반).
+    - `columnIndex` (integer, 선택사항): 행의 아무 셀의 열 인덱스 (0 기반). 기본값: `0`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_table_column">
+    **설명:** Google 문서의 기존 표에서 열을 삭제합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
+    - `rowIndex` (integer, 선택사항): 열의 아무 셀의 행 인덱스 (0 기반). 기본값: `0`.
+    - `columnIndex` (integer, 필수): 삭제할 열 인덱스 (0 기반).
+
+  </Accordion>
+
+  <Accordion title="google_docs/merge_table_cells">
+    **설명:** 표 셀 범위를 단일 셀로 병합합니다. 모든 셀의 내용이 보존됩니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
+    - `rowIndex` (integer, 필수): 병합의 시작 행 인덱스 (0 기반).
+    - `columnIndex` (integer, 필수): 병합의 시작 열 인덱스 (0 기반).
+    - `rowSpan` (integer, 필수): 병합할 행 수.
+    - `columnSpan` (integer, 필수): 병합할 열 수.
+
+  </Accordion>
+
+  <Accordion title="google_docs/unmerge_table_cells">
+    **설명:** 이전에 병합된 표 셀을 개별 셀로 분리합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `tableStartIndex` (integer, 필수): 표의 시작 인덱스.
+    - `rowIndex` (integer, 필수): 병합된 셀의 행 인덱스 (0 기반).
+    - `columnIndex` (integer, 필수): 병합된 셀의 열 인덱스 (0 기반).
+    - `rowSpan` (integer, 필수): 병합된 셀이 차지하는 행 수.
+    - `columnSpan` (integer, 필수): 병합된 셀이 차지하는 열 수.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_inline_image">
+    **설명:** 공개 URL에서 Google 문서에 이미지를 삽입합니다. 이미지는 공개적으로 접근 가능해야 하고, 50MB 미만이며, PNG/JPEG/GIF 형식이어야 합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `uri` (string, 필수): 이미지의 공개 URL. 인증 없이 접근 가능해야 합니다.
+    - `index` (integer, 선택사항): 이미지를 삽입할 위치. 제공하지 않으면 문서 끝에 삽입됩니다. 기본값: `1`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_section_break">
+    **설명:** 서로 다른 서식을 가진 문서 섹션을 만들기 위해 섹션 나누기를 삽입합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `index` (integer, 필수): 섹션 나누기를 삽입할 위치.
+    - `sectionType` (string, 필수): 섹션 나누기의 유형. 옵션: `CONTINUOUS` (같은 페이지에 유지), `NEXT_PAGE` (새 페이지 시작).
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_header">
+    **설명:** 문서의 머리글을 만듭니다. insert_text를 사용하여 머리글 내용을 추가할 수 있는 headerId를 반환합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `type` (string, 선택사항): 머리글 유형. 옵션: `DEFAULT`. 기본값: `DEFAULT`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_footer">
+    **설명:** 문서의 바닥글을 만듭니다. insert_text를 사용하여 바닥글 내용을 추가할 수 있는 footerId를 반환합니다.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `type` (string, 선택사항): 바닥글 유형. 옵션: `DEFAULT`. 기본값: `DEFAULT`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_header">
+    **설명:** 문서에서 머리글을 삭제합니다. headerId를 찾으려면 get_document를 사용하세요.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `headerId` (string, 필수): 삭제할 머리글 ID. get_document 응답에서 가져오세요.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_footer">
+    **설명:** 문서에서 바닥글을 삭제합니다. footerId를 찾으려면 get_document를 사용하세요.
+
+    **매개변수:**
+    - `documentId` (string, 필수): 문서 ID.
+    - `footerId` (string, 필수): 삭제할 바닥글 ID. get_document 응답에서 가져오세요.
+
+  </Accordion>
 </AccordionGroup>
 
 ## 사용 예제

docs/ko/enterprise/integrations/google_slides.mdx

@@ -61,6 +61,22 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/get_presentation_metadata">
+    **설명:** 프레젠테이션에 대한 가벼운 메타데이터(제목, 슬라이드 수, 슬라이드 ID)를 가져옵니다. 전체 콘텐츠를 가져오기 전에 먼저 사용하세요.
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 검색할 프레젠테이션의 ID.
+
+  </Accordion>
+
+  <Accordion title="google_slides/get_presentation_text">
+    **설명:** 프레젠테이션에서 모든 텍스트 콘텐츠를 추출합니다. 슬라이드 ID와 도형 및 테이블의 텍스트만 반환합니다 (포맷팅 없음).
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+
+  </Accordion>
+
   <Accordion title="google_slides/get_presentation">
     **설명:** ID로 프레젠테이션을 검색합니다.
 
@@ -80,6 +96,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/get_slide_text">
+    **설명:** 단일 슬라이드에서 텍스트 콘텐츠를 추출합니다. 도형 및 테이블의 텍스트만 반환합니다 (포맷팅 또는 스타일 없음).
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `pageObjectId` (string, 필수): 텍스트를 가져올 슬라이드/페이지의 ID.
+
+  </Accordion>
+
   <Accordion title="google_slides/get_page">
     **설명:** ID로 특정 페이지를 검색합니다.
 
@@ -98,6 +123,120 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/create_slide">
+    **설명:** 프레젠테이션에 추가 빈 슬라이드를 추가합니다. 새 프레젠테이션에는 이미 빈 슬라이드가 하나 있습니다. 먼저 get_presentation_metadata를 확인하세요. 제목/본문 영역이 있는 슬라이드는 create_slide_with_layout을 사용하세요.
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `insertionIndex` (integer, 선택사항): 슬라이드를 삽입할 위치 (0 기반). 생략하면 맨 끝에 추가됩니다.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_slide_with_layout">
+    **설명:** 제목, 본문 등의 플레이스홀더 영역이 있는 미리 정의된 레이아웃으로 슬라이드를 만듭니다. 구조화된 콘텐츠에는 create_slide보다 적합합니다. 생성 후 get_page로 플레이스홀더 ID를 찾고, 그 안에 텍스트를 삽입하세요.
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `layout` (string, 필수): 레이아웃 유형. 옵션: `BLANK`, `TITLE`, `TITLE_AND_BODY`, `TITLE_AND_TWO_COLUMNS`, `TITLE_ONLY`, `SECTION_HEADER`, `ONE_COLUMN_TEXT`, `MAIN_POINT`, `BIG_NUMBER`. 제목+설명은 TITLE_AND_BODY, 제목만은 TITLE, 섹션 구분은 SECTION_HEADER가 적합합니다.
+    - `insertionIndex` (integer, 선택사항): 삽입할 위치 (0 기반). 생략하면 맨 끝에 추가됩니다.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_text_box">
+    **설명:** 콘텐츠가 있는 텍스트 상자를 슬라이드에 만듭니다. 제목, 설명, 단락에 사용합니다. 테이블에는 사용하지 마세요. 선택적으로 EMU 단위로 위치(x, y)와 크기(width, height)를 지정할 수 있습니다 (914400 EMU = 1 인치).
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideId` (string, 필수): 텍스트 상자를 추가할 슬라이드의 ID.
+    - `text` (string, 필수): 텍스트 상자의 텍스트 내용.
+    - `x` (integer, 선택사항): EMU 단위 X 위치 (914400 = 1 인치). 기본값: 914400 (왼쪽에서 1 인치).
+    - `y` (integer, 선택사항): EMU 단위 Y 위치 (914400 = 1 인치). 기본값: 914400 (위에서 1 인치).
+    - `width` (integer, 선택사항): EMU 단위 너비. 기본값: 7315200 (약 8 인치).
+    - `height` (integer, 선택사항): EMU 단위 높이. 기본값: 914400 (약 1 인치).
+
+  </Accordion>
+
+  <Accordion title="google_slides/delete_slide">
+    **설명:** 프레젠테이션에서 슬라이드를 제거합니다. 슬라이드 ID를 찾으려면 먼저 get_presentation을 사용하세요.
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideId` (string, 필수): 삭제할 슬라이드의 객체 ID. get_presentation에서 가져옵니다.
+
+  </Accordion>
+
+  <Accordion title="google_slides/duplicate_slide">
+    **설명:** 기존 슬라이드의 복사본을 만듭니다. 복사본은 원본 바로 다음에 삽입됩니다.
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideId` (string, 필수): 복제할 슬라이드의 객체 ID. get_presentation에서 가져옵니다.
+
+  </Accordion>
+
+  <Accordion title="google_slides/move_slides">
+    **설명:** 슬라이드를 새 위치로 이동하여 순서를 변경합니다. 슬라이드 ID는 현재 프레젠테이션 순서대로 있어야 합니다 (중복 없음).
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideIds` (string 배열, 필수): 이동할 슬라이드 ID 배열. 현재 프레젠테이션 순서대로 있어야 합니다.
+    - `insertionIndex` (integer, 필수): 대상 위치 (0 기반). 0 = 맨 앞, 슬라이드 수 = 맨 끝.
+
+  </Accordion>
+
+  <Accordion title="google_slides/insert_youtube_video">
+    **설명:** 슬라이드에 YouTube 동영상을 삽입합니다. 동영상 ID는 YouTube URL의 "v=" 다음 값입니다 (예: youtube.com/watch?v=abc123의 경우 "abc123" 사용).
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideId` (string, 필수): 동영상을 추가할 슬라이드의 ID. get_presentation에서 가져옵니다.
+    - `videoId` (string, 필수): YouTube 동영상 ID (URL의 v= 다음 값).
+
+  </Accordion>
+
+  <Accordion title="google_slides/insert_drive_video">
+    **설명:** 슬라이드에 Google Drive의 동영상을 삽입합니다. 파일 ID는 Drive 파일 URL에서 찾을 수 있습니다.
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideId` (string, 필수): 동영상을 추가할 슬라이드의 ID. get_presentation에서 가져옵니다.
+    - `fileId` (string, 필수): 동영상의 Google Drive 파일 ID.
+
+  </Accordion>
+
+  <Accordion title="google_slides/set_slide_background_image">
+    **설명:** 슬라이드의 배경 이미지를 설정합니다. 이미지 URL은 공개적으로 액세스 가능해야 합니다.
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideId` (string, 필수): 배경을 설정할 슬라이드의 ID. get_presentation에서 가져옵니다.
+    - `imageUrl` (string, 필수): 배경으로 사용할 이미지의 공개적으로 액세스 가능한 URL.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_table">
+    **설명:** 슬라이드에 빈 테이블을 만듭니다. 콘텐츠가 있는 테이블을 만들려면 create_table_with_content를 사용하세요.
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideId` (string, 필수): 테이블을 추가할 슬라이드의 ID. get_presentation에서 가져옵니다.
+    - `rows` (integer, 필수): 테이블의 행 수.
+    - `columns` (integer, 필수): 테이블의 열 수.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_table_with_content">
+    **설명:** 한 번의 작업으로 콘텐츠가 있는 테이블을 만듭니다. 콘텐츠는 2D 배열로 제공하며, 각 내부 배열은 행을 나타냅니다. 예: [["Header1", "Header2"], ["Row1Col1", "Row1Col2"]].
+
+    **매개변수:**
+    - `presentationId` (string, 필수): 프레젠테이션의 ID.
+    - `slideId` (string, 필수): 테이블을 추가할 슬라이드의 ID. get_presentation에서 가져옵니다.
+    - `rows` (integer, 필수): 테이블의 행 수.
+    - `columns` (integer, 필수): 테이블의 열 수.
+    - `content` (array, 필수): 2D 배열 형태의 테이블 콘텐츠. 각 내부 배열은 행입니다. 예: [["Year", "Revenue"], ["2023", "$10M"]].
+
+  </Accordion>
+
   <Accordion title="google_slides/import_data_from_sheet">
     **설명:** Google 시트에서 프레젠테이션으로 데이터를 가져옵니다.
 

docs/ko/enterprise/integrations/microsoft_excel.mdx

@@ -148,6 +148,16 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_excel/get_table_data">
+    **설명:** Excel 워크시트의 특정 테이블에서 데이터를 가져옵니다.
+
+    **매개변수:**
+    - `file_id` (string, 필수): Excel 파일의 ID.
+    - `worksheet_name` (string, 필수): 워크시트의 이름.
+    - `table_name` (string, 필수): 테이블의 이름.
+
+  </Accordion>
+
   <Accordion title="microsoft_excel/create_chart">
     **설명:** Excel 워크시트에 차트를 만듭니다.
 
@@ -180,6 +190,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_excel/get_used_range_metadata">
+    **설명:** Excel 워크시트의 사용된 범위 메타데이터(크기만, 데이터 없음)를 가져옵니다.
+
+    **매개변수:**
+    - `file_id` (string, 필수): Excel 파일의 ID.
+    - `worksheet_name` (string, 필수): 워크시트의 이름.
+
+  </Accordion>
+
   <Accordion title="microsoft_excel/list_charts">
     **설명:** Excel 워크시트의 모든 차트를 가져옵니다.
 

docs/ko/enterprise/integrations/microsoft_onedrive.mdx

@@ -150,6 +150,49 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `item_id` (string, 필수): 파일의 ID.
 
   </Accordion>
+
+  <Accordion title="microsoft_onedrive/list_files_by_path">
+    **설명:** 특정 OneDrive 경로의 파일과 폴더를 나열합니다.
+
+    **매개변수:**
+    - `folder_path` (string, 필수): 폴더 경로 (예: 'Documents/Reports').
+    - `top` (integer, 선택사항): 검색할 항목 수 (최대 1000). 기본값: 50.
+    - `orderby` (string, 선택사항): 필드별 정렬 (예: "name asc", "lastModifiedDateTime desc"). 기본값: "name asc".
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_recent_files">
+    **설명:** OneDrive에서 최근에 액세스한 파일을 가져옵니다.
+
+    **매개변수:**
+    - `top` (integer, 선택사항): 검색할 항목 수 (최대 200). 기본값: 25.
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_shared_with_me">
+    **설명:** 사용자와 공유된 파일과 폴더를 가져옵니다.
+
+    **매개변수:**
+    - `top` (integer, 선택사항): 검색할 항목 수 (최대 200). 기본값: 50.
+    - `orderby` (string, 선택사항): 필드별 정렬. 기본값: "name asc".
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_file_by_path">
+    **설명:** 경로로 특정 파일 또는 폴더에 대한 정보를 가져옵니다.
+
+    **매개변수:**
+    - `file_path` (string, 필수): 파일 또는 폴더 경로 (예: 'Documents/report.docx').
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/download_file_by_path">
+    **설명:** 경로로 OneDrive에서 파일을 다운로드합니다.
+
+    **매개변수:**
+    - `file_path` (string, 필수): 파일 경로 (예: 'Documents/report.docx').
+
+  </Accordion>
 </AccordionGroup>
 
 ## 사용 예제
@@ -183,6 +226,62 @@ crew = Crew(
 crew.kickoff()
 ```
 
+### 파일 업로드 및 관리
+
+```python
+from crewai import Agent, Task, Crew
+
+# 파일 작업에 특화된 에이전트 생성
+file_operator = Agent(
+    role="파일 운영자",
+    goal="파일을 정확하게 업로드, 다운로드 및 관리",
+    backstory="파일 처리 및 콘텐츠 관리에 능숙한 AI 어시스턴트.",
+    apps=['microsoft_onedrive/upload_file', 'microsoft_onedrive/download_file', 'microsoft_onedrive/get_file_info']
+)
+
+# 파일 업로드 및 관리 작업
+file_management_task = Task(
+    description="'report.txt'라는 이름의 텍스트 파일을 'This is a sample report for the project.' 내용으로 업로드한 다음 업로드된 파일에 대한 정보를 가져오세요.",
+    agent=file_operator,
+    expected_output="파일이 성공적으로 업로드되고 파일 정보가 검색됨."
+)
+
+crew = Crew(
+    agents=[file_operator],
+    tasks=[file_management_task]
+)
+
+crew.kickoff()
+```
+
+### 파일 정리 및 공유
+
+```python
+from crewai import Agent, Task, Crew
+
+# 파일 정리 및 공유를 위한 에이전트 생성
+file_organizer = Agent(
+    role="파일 정리자",
+    goal="파일을 정리하고 협업을 위한 공유 링크 생성",
+    backstory="파일 정리 및 공유 권한 관리에 뛰어난 AI 어시스턴트.",
+    apps=['microsoft_onedrive/search_files', 'microsoft_onedrive/move_item', 'microsoft_onedrive/share_item', 'microsoft_onedrive/create_folder']
+)
+
+# 파일 정리 및 공유 작업
+organize_share_task = Task(
+    description="이름에 'presentation'이 포함된 파일을 검색하고, '프레젠테이션'이라는 폴더를 만든 다음, 찾은 파일을 이 폴더로 이동하고 폴더에 대한 읽기 전용 공유 링크를 생성하세요.",
+    agent=file_organizer,
+    expected_output="파일이 '프레젠테이션' 폴더로 정리되고 공유 링크가 생성됨."
+)
+
+crew = Crew(
+    agents=[file_organizer],
+    tasks=[organize_share_task]
+)
+
+crew.kickoff()
+```
+
 ## 문제 해결
 
 ### 일반적인 문제
@@ -196,6 +295,30 @@ crew.kickoff()
 
 - 파일 업로드 시 `file_name`과 `content`가 제공되는지 확인하세요.
 - 바이너리 파일의 경우 내용이 Base64로 인코딩되어야 합니다.
+- OneDrive에 대한 쓰기 권한이 있는지 확인하세요.
+
+**파일/폴더 ID 문제**
+
+- 특정 파일 또는 폴더에 액세스할 때 항목 ID가 올바른지 다시 확인하세요.
+- 항목 ID는 `list_files` 또는 `search_files`와 같은 다른 작업에서 반환됩니다.
+- 참조하는 항목이 존재하고 액세스 가능한지 확인하세요.
+
+**검색 및 필터 작업**
+
+- `search_files` 작업에 적절한 검색어를 사용하세요.
+- `filter` 매개변수의 경우 올바른 OData 문법을 사용하세요.
+
+**파일 작업 (복사/이동)**
+
+- `move_item`의 경우 `item_id`와 `parent_id`가 모두 제공되는지 확인하세요.
+- `copy_item`의 경우 `item_id`만 필요합니다. `parent_id`는 지정하지 않으면 루트로 기본 설정됩니다.
+- 대상 폴더가 존재하고 액세스 가능한지 확인하세요.
+
+**공유 링크 생성**
+
+- 공유 링크를 만들기 전에 항목이 존재하는지 확인하세요.
+- 공유 요구 사항에 따라 적절한 `type`과 `scope`를 선택하세요.
+- `anonymous` 범위는 로그인 없이 액세스를 허용합니다. `organization`은 조직 계정이 필요합니다.
 
 ### 도움 받기
 

docs/ko/enterprise/integrations/microsoft_outlook.mdx

@@ -132,6 +132,74 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `companyName` (string, 선택사항): 연락처의 회사 이름.
 
   </Accordion>
+
+  <Accordion title="microsoft_outlook/get_message">
+    **설명:** ID로 특정 이메일 메시지를 가져옵니다.
+
+    **매개변수:**
+    - `message_id` (string, 필수): 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
+    - `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록. 예: "id,subject,body,from,receivedDateTime". 기본값: "id,subject,body,from,toRecipients,receivedDateTime".
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/reply_to_email">
+    **설명:** 이메일 메시지에 회신합니다.
+
+    **매개변수:**
+    - `message_id` (string, 필수): 회신할 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
+    - `comment` (string, 필수): 회신 메시지 내용. 일반 텍스트 또는 HTML 가능. 원본 메시지가 이 내용 아래에 인용됩니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/forward_email">
+    **설명:** 이메일 메시지를 전달합니다.
+
+    **매개변수:**
+    - `message_id` (string, 필수): 전달할 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
+    - `to_recipients` (array, 필수): 전달할 받는 사람의 이메일 주소 배열. 예: ["john@example.com", "jane@example.com"].
+    - `comment` (string, 선택사항): 전달된 콘텐츠 위에 포함할 선택적 메시지. 일반 텍스트 또는 HTML 가능.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/mark_message_read">
+    **설명:** 메시지를 읽음 또는 읽지 않음으로 표시합니다.
+
+    **매개변수:**
+    - `message_id` (string, 필수): 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
+    - `is_read` (boolean, 필수): 읽음으로 표시하려면 true, 읽지 않음으로 표시하려면 false로 설정합니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/delete_message">
+    **설명:** 이메일 메시지를 삭제합니다.
+
+    **매개변수:**
+    - `message_id` (string, 필수): 삭제할 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/update_event">
+    **설명:** 기존 캘린더 이벤트를 업데이트합니다.
+
+    **매개변수:**
+    - `event_id` (string, 필수): 이벤트의 고유 식별자. get_calendar_events 작업에서 얻을 수 있습니다.
+    - `subject` (string, 선택사항): 이벤트의 새 제목/제목.
+    - `start_time` (string, 선택사항): ISO 8601 형식의 새 시작 시간 (예: "2024-01-20T10:00:00"). 필수: 이 필드 사용 시 start_timezone도 제공해야 합니다.
+    - `start_timezone` (string, 선택사항): 시작 시간의 시간대. start_time 업데이트 시 필수. 예: "Pacific Standard Time", "Eastern Standard Time", "UTC".
+    - `end_time` (string, 선택사항): ISO 8601 형식의 새 종료 시간. 필수: 이 필드 사용 시 end_timezone도 제공해야 합니다.
+    - `end_timezone` (string, 선택사항): 종료 시간의 시간대. end_time 업데이트 시 필수. 예: "Pacific Standard Time", "Eastern Standard Time", "UTC".
+    - `location` (string, 선택사항): 이벤트의 새 위치.
+    - `body` (string, 선택사항): 이벤트의 새 본문/설명. HTML 형식 지원.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/delete_event">
+    **설명:** 캘린더 이벤트를 삭제합니다.
+
+    **매개변수:**
+    - `event_id` (string, 필수): 삭제할 이벤트의 고유 식별자. get_calendar_events 작업에서 얻을 수 있습니다.
+
+  </Accordion>
 </AccordionGroup>
 
 ## 사용 예제
@@ -165,6 +233,62 @@ crew = Crew(
 crew.kickoff()
 ```
 
+### 이메일 관리 및 검색
+
+```python
+from crewai import Agent, Task, Crew
+
+# 이메일 관리에 특화된 에이전트 생성
+email_manager = Agent(
+    role="이메일 관리자",
+    goal="이메일 메시지를 검색하고 가져와 정리",
+    backstory="이메일 정리 및 관리에 능숙한 AI 어시스턴트.",
+    apps=['microsoft_outlook/get_messages']
+)
+
+# 이메일 검색 및 가져오기 작업
+search_emails_task = Task(
+    description="최신 읽지 않은 이메일 20건을 가져와 가장 중요한 것들의 요약을 제공하세요.",
+    agent=email_manager,
+    expected_output="주요 읽지 않은 이메일의 요약과 핵심 세부 정보."
+)
+
+crew = Crew(
+    agents=[email_manager],
+    tasks=[search_emails_task]
+)
+
+crew.kickoff()
+```
+
+### 캘린더 및 연락처 관리
+
+```python
+from crewai import Agent, Task, Crew
+
+# 캘린더 및 연락처 관리를 위한 에이전트 생성
+scheduler = Agent(
+    role="캘린더 및 연락처 관리자",
+    goal="캘린더 이벤트를 관리하고 연락처 정보를 유지",
+    backstory="일정 관리 및 연락처 정리를 담당하는 AI 어시스턴트.",
+    apps=['microsoft_outlook/create_calendar_event', 'microsoft_outlook/get_calendar_events', 'microsoft_outlook/create_contact']
+)
+
+# 회의 생성 및 연락처 추가 작업
+schedule_task = Task(
+    description="내일 오후 2시 '팀 회의' 제목으로 '회의실 A' 장소의 캘린더 이벤트를 만들고, 'john.smith@example.com' 이메일과 '프로젝트 매니저' 직책으로 'John Smith'의 새 연락처를 추가하세요.",
+    agent=scheduler,
+    expected_output="캘린더 이벤트가 생성되고 새 연락처가 추가됨."
+)
+
+crew = Crew(
+    agents=[scheduler],
+    tasks=[schedule_task]
+)
+
+crew.kickoff()
+```
+
 ## 문제 해결
 
 ### 일반적인 문제
@@ -173,11 +297,29 @@ crew.kickoff()
 
 - Microsoft 계정이 이메일, 캘린더 및 연락처 액세스에 필요한 권한을 가지고 있는지 확인하세요.
 - 필요한 범위: `Mail.Read`, `Mail.Send`, `Calendars.Read`, `Calendars.ReadWrite`, `Contacts.Read`, `Contacts.ReadWrite`.
+- OAuth 연결에 필요한 모든 범위가 포함되어 있는지 확인하세요.
 
 **이메일 보내기 문제**
 
 - `send_email`에 `to_recipients`, `subject`, `body`가 제공되는지 확인하세요.
 - 이메일 주소가 올바르게 형식화되어 있는지 확인하세요.
+- 계정에 `Mail.Send` 권한이 있는지 확인하세요.
+
+**캘린더 이벤트 생성**
+
+- `subject`, `start_datetime`, `end_datetime`이 제공되는지 확인하세요.
+- 날짜/시간 필드에 적절한 ISO 8601 형식을 사용하세요 (예: '2024-01-20T10:00:00').
+- 이벤트가 잘못된 시간에 표시되는 경우 시간대 설정을 확인하세요.
+
+**연락처 관리**
+
+- `create_contact`의 경우 필수인 `displayName`이 제공되는지 확인하세요.
+- `emailAddresses`를 제공할 때 `address`와 `name` 속성이 있는 올바른 객체 형식을 사용하세요.
+
+**검색 및 필터 문제**
+
+- `filter` 매개변수에 올바른 OData 문법을 사용하세요.
+- 날짜 필터의 경우 ISO 8601 형식을 사용하세요 (예: "receivedDateTime ge '2024-01-01T00:00:00Z'").
 
 ### 도움 받기
 

docs/ko/enterprise/integrations/microsoft_sharepoint.mdx

@@ -77,6 +77,17 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_sharepoint/get_drives">
+    **설명:** SharePoint 사이트의 모든 문서 라이브러리(드라이브)를 나열합니다. 파일 작업을 사용하기 전에 사용 가능한 라이브러리를 찾으려면 이 작업을 사용하세요.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `top` (integer, 선택사항): 페이지당 반환할 최대 드라이브 수 (1-999). 기본값: 100
+    - `skip_token` (string, 선택사항): 다음 결과 페이지를 가져오기 위한 이전 응답의 페이지네이션 토큰.
+    - `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'id,name,webUrl,driveType').
+
+  </Accordion>
+
   <Accordion title="microsoft_sharepoint/get_site_lists">
     **설명:** SharePoint 사이트의 모든 목록을 가져옵니다.
 
@@ -145,20 +156,317 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
 
   </Accordion>
 
-  <Accordion title="microsoft_sharepoint/get_drive_items">
-    **설명:** SharePoint 문서 라이브러리에서 파일과 폴더를 가져옵니다.
+  <Accordion title="microsoft_sharepoint/list_files">
+    **설명:** SharePoint 문서 라이브러리에서 파일과 폴더를 가져옵니다. 기본적으로 루트 폴더를 나열하지만 folder_id를 제공하여 하위 폴더로 이동할 수 있습니다.
 
     **매개변수:**
-    - `site_id` (string, 필수): SharePoint 사이트의 ID.
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `folder_id` (string, 선택사항): 내용을 나열할 폴더의 ID. 루트 폴더의 경우 'root'를 사용하거나 이전 list_files 호출에서 가져온 폴더 ID를 제공하세요. 기본값: 'root'
+    - `top` (integer, 선택사항): 페이지당 반환할 최대 항목 수 (1-1000). 기본값: 50
+    - `skip_token` (string, 선택사항): 다음 결과 페이지를 가져오기 위한 이전 응답의 페이지네이션 토큰.
+    - `orderby` (string, 선택사항): 결과 정렬 순서 (예: 'name asc', 'size desc', 'lastModifiedDateTime desc'). 기본값: 'name asc'
+    - `filter` (string, 선택사항): 결과를 좁히기 위한 OData 필터 (예: 'file ne null'은 파일만, 'folder ne null'은 폴더만).
+    - `select` (string, 선택사항): 반환할 필드의 쉼표로 구분된 목록 (예: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
 
   </Accordion>
 
-  <Accordion title="microsoft_sharepoint/delete_drive_item">
-    **설명:** SharePoint 문서 라이브러리에서 파일 또는 폴더를 삭제합니다.
+  <Accordion title="microsoft_sharepoint/delete_file">
+    **설명:** SharePoint 문서 라이브러리에서 파일 또는 폴더를 삭제합니다. 폴더의 경우 모든 내용이 재귀적으로 삭제됩니다. 항목은 사이트 휴지통으로 이동됩니다.
 
     **매개변수:**
-    - `site_id` (string, 필수): SharePoint 사이트의 ID.
-    - `item_id` (string, 필수): 삭제할 파일 또는 폴더의 ID.
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): 삭제할 파일 또는 폴더의 고유 식별자. list_files에서 가져오세요.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_files_by_path">
+    **설명:** 경로로 SharePoint 문서 라이브러리 폴더의 파일과 폴더를 나열합니다. 깊은 탐색을 위해 여러 list_files 호출보다 더 효율적입니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `folder_path` (string, 필수): 앞뒤 슬래시 없이 폴더의 전체 경로 (예: 'Documents', 'Reports/2024/Q1').
+    - `top` (integer, 선택사항): 페이지당 반환할 최대 항목 수 (1-1000). 기본값: 50
+    - `skip_token` (string, 선택사항): 다음 결과 페이지를 가져오기 위한 이전 응답의 페이지네이션 토큰.
+    - `orderby` (string, 선택사항): 결과 정렬 순서 (예: 'name asc', 'size desc'). 기본값: 'name asc'
+    - `select` (string, 선택사항): 반환할 필드의 쉼표로 구분된 목록 (예: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/download_file">
+    **설명:** SharePoint 문서 라이브러리에서 원시 파일 내용을 다운로드합니다. 일반 텍스트 파일(.txt, .csv, .json)에만 사용하세요. Excel 파일의 경우 Excel 전용 작업을 사용하세요. Word 파일의 경우 get_word_document_content를 사용하세요.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): 다운로드할 파일의 고유 식별자. list_files 또는 list_files_by_path에서 가져오세요.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_file_info">
+    **설명:** SharePoint 문서 라이브러리의 특정 파일 또는 폴더에 대한 자세한 메타데이터를 가져옵니다. 이름, 크기, 생성/수정 날짜 및 작성자 정보가 포함됩니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): 파일 또는 폴더의 고유 식별자. list_files 또는 list_files_by_path에서 가져오세요.
+    - `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'id,name,size,createdDateTime,lastModifiedDateTime,webUrl,createdBy,lastModifiedBy').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_folder">
+    **설명:** SharePoint 문서 라이브러리에 새 폴더를 만듭니다. 기본적으로 루트에 폴더를 만들며 하위 폴더를 만들려면 parent_id를 사용하세요.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `folder_name` (string, 필수): 새 폴더의 이름. 사용할 수 없는 문자: \ / : * ? " < > |
+    - `parent_id` (string, 선택사항): 상위 폴더의 ID. 문서 라이브러리 루트의 경우 'root'를 사용하거나 list_files에서 가져온 폴더 ID를 제공하세요. 기본값: 'root'
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/search_files">
+    **설명:** 키워드로 SharePoint 문서 라이브러리에서 파일과 폴더를 검색합니다. 파일 이름, 폴더 이름 및 Office 문서의 파일 내용을 검색합니다. 와일드카드나 특수 문자를 사용하지 마세요.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `query` (string, 필수): 검색 키워드 (예: 'report', 'budget 2024'). *.txt와 같은 와일드카드는 지원되지 않습니다.
+    - `top` (integer, 선택사항): 페이지당 반환할 최대 결과 수 (1-1000). 기본값: 50
+    - `skip_token` (string, 선택사항): 다음 결과 페이지를 가져오기 위한 이전 응답의 페이지네이션 토큰.
+    - `select` (string, 선택사항): 반환할 필드의 쉼표로 구분된 목록 (예: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/copy_file">
+    **설명:** SharePoint 내에서 파일 또는 폴더를 새 위치로 복사합니다. 원본 항목은 변경되지 않습니다. 대용량 파일의 경우 복사 작업은 비동기적입니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): 복사할 파일 또는 폴더의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `destination_folder_id` (string, 필수): 대상 폴더의 ID. 루트 폴더의 경우 'root'를 사용하거나 list_files에서 가져온 폴더 ID를 사용하세요.
+    - `new_name` (string, 선택사항): 복사본의 새 이름. 제공하지 않으면 원래 이름이 사용됩니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/move_file">
+    **설명:** SharePoint 내에서 파일 또는 폴더를 새 위치로 이동합니다. 항목은 원래 위치에서 제거됩니다. 폴더의 경우 모든 내용도 함께 이동됩니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): 이동할 파일 또는 폴더의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `destination_folder_id` (string, 필수): 대상 폴더의 ID. 루트 폴더의 경우 'root'를 사용하거나 list_files에서 가져온 폴더 ID를 사용하세요.
+    - `new_name` (string, 선택사항): 이동된 항목의 새 이름. 제공하지 않으면 원래 이름이 유지됩니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_worksheets">
+    **설명:** SharePoint 문서 라이브러리에 저장된 Excel 통합 문서의 모든 워크시트(탭)를 나열합니다. 반환된 워크시트 이름을 다른 Excel 작업에 사용하세요.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'id,name,position,visibility').
+    - `filter` (string, 선택사항): OData 필터 표현식 (예: "visibility eq 'Visible'"로 숨겨진 시트 제외).
+    - `top` (integer, 선택사항): 반환할 최대 워크시트 수. 최소: 1, 최대: 999
+    - `orderby` (string, 선택사항): 정렬 순서 (예: 'position asc'로 탭 순서대로 반환).
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_excel_worksheet">
+    **설명:** SharePoint 문서 라이브러리에 저장된 Excel 통합 문서에 새 워크시트(탭)를 만듭니다. 새 시트는 탭 목록의 끝에 추가됩니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `name` (string, 필수): 새 워크시트의 이름. 최대 31자. 사용할 수 없는 문자: \ / * ? : [ ]. 통합 문서 내에서 고유해야 합니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_range_data">
+    **설명:** SharePoint에 저장된 Excel 워크시트의 특정 범위에서 셀 값을 가져옵니다. 크기를 모르는 상태에서 모든 데이터를 읽으려면 대신 get_excel_used_range를 사용하세요.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 읽을 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
+    - `range` (string, 필수): A1 표기법의 셀 범위 (예: 'A1:C10', 'A:C', '1:5', 'A1').
+    - `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'address,values,formulas,numberFormat,text').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/update_excel_range_data">
+    **설명:** SharePoint에 저장된 Excel 워크시트의 특정 범위에 값을 씁니다. 기존 셀 내용을 덮어씁니다. values 배열의 크기는 범위 크기와 정확히 일치해야 합니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 업데이트할 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
+    - `range` (string, 필수): 값을 쓸 A1 표기법의 셀 범위 (예: 'A1:C3'은 3x3 블록).
+    - `values` (array, 필수): 2D 값 배열 (셀을 포함하는 행). A1:B2의 예: [["Header1", "Header2"], ["Value1", "Value2"]]. 셀을 지우려면 null을 사용하세요.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_used_range_metadata">
+    **설명:** 실제 셀 값 없이 워크시트에서 사용된 범위의 메타데이터(주소 및 크기)만 반환합니다. 대용량 파일에서 데이터를 청크로 읽기 전에 스프레드시트 크기를 파악하는 데 이상적입니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 읽을 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_used_range">
+    **설명:** SharePoint에 저장된 워크시트에서 데이터가 포함된 모든 셀을 가져옵니다. 2MB보다 큰 파일에는 사용하지 마세요. 대용량 파일의 경우 먼저 get_excel_used_range_metadata를 사용한 다음 get_excel_range_data로 작은 청크로 읽으세요.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 읽을 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
+    - `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'address,values,formulas,numberFormat,text,rowCount,columnCount').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_cell">
+    **설명:** SharePoint의 Excel 파일에서 행과 열 인덱스로 단일 셀의 값을 가져옵니다. 인덱스는 0 기반입니다 (행 0 = Excel 행 1, 열 0 = 열 A).
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 워크시트(탭)의 이름. get_excel_worksheets에서 가져오세요. 대소문자를 구분합니다.
+    - `row` (integer, 필수): 0 기반 행 인덱스 (행 0 = Excel 행 1). 유효 범위: 0-1048575
+    - `column` (integer, 필수): 0 기반 열 인덱스 (열 0 = A, 열 1 = B). 유효 범위: 0-16383
+    - `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'address,values,formulas,numberFormat,text').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/add_excel_table">
+    **설명:** 셀 범위를 필터링, 정렬 및 구조화된 데이터 기능이 있는 서식이 지정된 Excel 테이블로 변환합니다. 테이블을 만들면 add_excel_table_row로 데이터를 추가할 수 있습니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 데이터 범위가 포함된 워크시트의 이름. get_excel_worksheets에서 가져오세요.
+    - `range` (string, 필수): 헤더와 데이터를 포함하여 테이블로 변환할 셀 범위 (예: 'A1:D10'에서 A1:D1은 열 헤더).
+    - `has_headers` (boolean, 선택사항): 첫 번째 행에 열 헤더가 포함되어 있으면 true로 설정. 기본값: true
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_tables">
+    **설명:** SharePoint에 저장된 특정 Excel 워크시트의 모든 테이블을 나열합니다. id, name, showHeaders 및 showTotals를 포함한 테이블 속성을 반환합니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 테이블을 가져올 워크시트의 이름. get_excel_worksheets에서 가져오세요.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/add_excel_table_row">
+    **설명:** SharePoint 파일의 Excel 테이블 끝에 새 행을 추가합니다. values 배열은 테이블의 열 수와 같은 수의 요소를 가져야 합니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 테이블이 포함된 워크시트의 이름. get_excel_worksheets에서 가져오세요.
+    - `table_name` (string, 필수): 행을 추가할 테이블의 이름 (예: 'Table1'). get_excel_tables에서 가져오세요. 대소문자를 구분합니다.
+    - `values` (array, 필수): 새 행의 셀 값 배열로 테이블 순서대로 열당 하나씩 (예: ["John Doe", "john@example.com", 25]).
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_table_data">
+    **설명:** SharePoint 파일의 Excel 테이블에서 모든 행을 데이터 범위로 가져옵니다. 정확한 범위를 알 필요가 없으므로 구조화된 테이블 작업 시 get_excel_range_data보다 쉽습니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 테이블이 포함된 워크시트의 이름. get_excel_worksheets에서 가져오세요.
+    - `table_name` (string, 필수): 데이터를 가져올 테이블의 이름 (예: 'Table1'). get_excel_tables에서 가져오세요. 대소문자를 구분합니다.
+    - `select` (string, 선택사항): 반환할 속성의 쉼표로 구분된 목록 (예: 'address,values,formulas,numberFormat,text').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_excel_chart">
+    **설명:** SharePoint에 저장된 Excel 워크시트에 데이터 범위에서 차트 시각화를 만듭니다. 차트는 워크시트에 포함됩니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 차트를 만들 워크시트의 이름. get_excel_worksheets에서 가져오세요.
+    - `chart_type` (string, 필수): 차트 유형 (예: 'ColumnClustered', 'ColumnStacked', 'Line', 'LineMarkers', 'Pie', 'Bar', 'BarClustered', 'Area', 'Scatter', 'Doughnut').
+    - `source_data` (string, 필수): 헤더를 포함한 A1 표기법의 차트 데이터 범위 (예: 'A1:B10').
+    - `series_by` (string, 선택사항): 데이터 계열 구성 방법: 'Auto', 'Columns' 또는 'Rows'. 기본값: 'Auto'
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_excel_charts">
+    **설명:** SharePoint에 저장된 Excel 워크시트에 포함된 모든 차트를 나열합니다. id, name, chartType, height, width 및 position을 포함한 차트 속성을 반환합니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 차트를 나열할 워크시트의 이름. get_excel_worksheets에서 가져오세요.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/delete_excel_worksheet">
+    **설명:** SharePoint에 저장된 Excel 통합 문서에서 워크시트(탭)와 모든 내용을 영구적으로 제거합니다. 실행 취소할 수 없습니다. 통합 문서에는 최소 하나의 워크시트가 있어야 합니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 삭제할 워크시트의 이름. 대소문자를 구분합니다. 이 시트의 모든 데이터, 테이블 및 차트가 영구적으로 제거됩니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/delete_excel_table">
+    **설명:** SharePoint의 Excel 워크시트에서 테이블을 제거합니다. 테이블 구조(필터링, 서식, 테이블 기능)는 삭제되지만 기본 셀 데이터는 보존됩니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+    - `worksheet_name` (string, 필수): 테이블이 포함된 워크시트의 이름. get_excel_worksheets에서 가져오세요.
+    - `table_name` (string, 필수): 삭제할 테이블의 이름 (예: 'Table1'). get_excel_tables에서 가져오세요. 테이블 삭제 후에도 셀의 데이터는 유지됩니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_excel_names">
+    **설명:** SharePoint에 저장된 Excel 통합 문서에 정의된 모든 명명된 범위를 가져옵니다. 명명된 범위는 셀 범위에 대한 사용자 정의 레이블입니다 (예: 'SalesData'는 A1:D100을 가리킴).
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Excel 파일의 고유 식별자. list_files 또는 search_files에서 가져오세요.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_word_document_content">
+    **설명:** SharePoint 문서 라이브러리에 저장된 Word 문서(.docx)에서 텍스트 내용을 다운로드하고 추출합니다. SharePoint에서 Word 문서를 읽는 권장 방법입니다.
+
+    **매개변수:**
+    - `site_id` (string, 필수): get_sites에서 가져온 전체 SharePoint 사이트 식별자.
+    - `drive_id` (string, 필수): 문서 라이브러리의 ID. 먼저 get_drives를 호출하여 유효한 드라이브 ID를 가져오세요.
+    - `item_id` (string, 필수): SharePoint에 있는 Word 문서(.docx)의 고유 식별자. list_files 또는 search_files에서 가져오세요.
 
   </Accordion>
 </AccordionGroup>

docs/ko/enterprise/integrations/microsoft_teams.mdx

@@ -107,6 +107,86 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `join_web_url` (string, 필수): 검색할 회의의 웹 참가 URL.
 
   </Accordion>
+
+  <Accordion title="microsoft_teams/search_online_meetings_by_meeting_id">
+    **설명:** 외부 Meeting ID로 온라인 회의를 검색합니다.
+
+    **매개변수:**
+    - `join_meeting_id` (string, 필수): 참석자가 참가할 때 사용하는 회의 ID(숫자 코드). 회의 초대에 표시되는 joinMeetingId이며, Graph API meeting id가 아닙니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_meeting">
+    **설명:** 특정 온라인 회의의 세부 정보를 가져옵니다.
+
+    **매개변수:**
+    - `meeting_id` (string, 필수): Graph API 회의 ID(긴 영숫자 문자열). create_meeting 또는 search_online_meetings 작업에서 얻을 수 있습니다. 숫자 joinMeetingId와 다릅니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_team_members">
+    **설명:** 특정 팀의 멤버를 가져옵니다.
+
+    **매개변수:**
+    - `team_id` (string, 필수): 팀의 고유 식별자. get_teams 작업에서 얻을 수 있습니다.
+    - `top` (integer, 선택사항): 페이지당 검색할 멤버 수 (1-999). 기본값: 100.
+    - `skip_token` (string, 선택사항): 이전 응답의 페이지네이션 토큰. 응답에 @odata.nextLink가 포함된 경우 $skiptoken 매개변수 값을 추출하여 여기에 전달하면 다음 페이지 결과를 가져올 수 있습니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/create_channel">
+    **설명:** 팀에 새 채널을 만듭니다.
+
+    **매개변수:**
+    - `team_id` (string, 필수): 팀의 고유 식별자. get_teams 작업에서 얻을 수 있습니다.
+    - `display_name` (string, 필수): Teams에 표시되는 채널 이름. 팀 내에서 고유해야 합니다. 최대 50자.
+    - `description` (string, 선택사항): 채널 목적을 설명하는 선택적 설명. 채널 세부 정보에 표시됩니다. 최대 1024자.
+    - `membership_type` (string, 선택사항): 채널 가시성. 옵션: standard, private. "standard" = 모든 팀 멤버에게 표시, "private" = 명시적으로 추가된 멤버에게만 표시. 기본값: standard.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_message_replies">
+    **설명:** 채널의 특정 메시지에 대한 회신을 가져옵니다.
+
+    **매개변수:**
+    - `team_id` (string, 필수): 팀의 고유 식별자. get_teams 작업에서 얻을 수 있습니다.
+    - `channel_id` (string, 필수): 채널의 고유 식별자. get_channels 작업에서 얻을 수 있습니다.
+    - `message_id` (string, 필수): 상위 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
+    - `top` (integer, 선택사항): 페이지당 검색할 회신 수 (1-50). 기본값: 50.
+    - `skip_token` (string, 선택사항): 이전 응답의 페이지네이션 토큰. 응답에 @odata.nextLink가 포함된 경우 $skiptoken 매개변수 값을 추출하여 여기에 전달하면 다음 페이지 결과를 가져올 수 있습니다.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/reply_to_message">
+    **설명:** Teams 채널의 메시지에 회신합니다.
+
+    **매개변수:**
+    - `team_id` (string, 필수): 팀의 고유 식별자. get_teams 작업에서 얻을 수 있습니다.
+    - `channel_id` (string, 필수): 채널의 고유 식별자. get_channels 작업에서 얻을 수 있습니다.
+    - `message_id` (string, 필수): 회신할 메시지의 고유 식별자. get_messages 작업에서 얻을 수 있습니다.
+    - `message` (string, 필수): 회신 내용. HTML의 경우 서식 태그 포함. 텍스트의 경우 일반 텍스트만.
+    - `content_type` (string, 선택사항): 콘텐츠 형식. 옵션: html, text. "text"는 일반 텍스트, "html"은 서식이 있는 리치 텍스트. 기본값: text.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/update_meeting">
+    **설명:** 기존 온라인 회의를 업데이트합니다.
+
+    **매개변수:**
+    - `meeting_id` (string, 필수): 회의의 고유 식별자. create_meeting 또는 search_online_meetings 작업에서 얻을 수 있습니다.
+    - `subject` (string, 선택사항): 새 회의 제목.
+    - `startDateTime` (string, 선택사항): 시간대가 포함된 ISO 8601 형식의 새 시작 시간. 예: "2024-01-20T10:00:00-08:00".
+    - `endDateTime` (string, 선택사항): 시간대가 포함된 ISO 8601 형식의 새 종료 시간.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/delete_meeting">
+    **설명:** 온라인 회의를 삭제합니다.
+
+    **매개변수:**
+    - `meeting_id` (string, 필수): 삭제할 회의의 고유 식별자. create_meeting 또는 search_online_meetings 작업에서 얻을 수 있습니다.
+
+  </Accordion>
 </AccordionGroup>
 
 ## 사용 예제
@@ -140,6 +220,62 @@ crew = Crew(
 crew.kickoff()
 ```
 
+### 메시징 및 커뮤니케이션
+
+```python
+from crewai import Agent, Task, Crew
+
+# 메시징에 특화된 에이전트 생성
+messenger = Agent(
+    role="Teams 메신저",
+    goal="Teams 채널에서 메시지 전송 및 검색",
+    backstory="팀 커뮤니케이션 및 메시지 관리에 능숙한 AI 어시스턴트.",
+    apps=['microsoft_teams/send_message', 'microsoft_teams/get_messages']
+)
+
+# 메시지 전송 및 최근 메시지 검색 작업
+messaging_task = Task(
+    description="'your_team_id' 팀의 General 채널에 'Hello team! This is an automated update from our AI assistant.' 메시지를 보낸 다음 해당 채널의 최근 10개 메시지를 검색하세요.",
+    agent=messenger,
+    expected_output="메시지가 성공적으로 전송되고 최근 메시지가 검색됨."
+)
+
+crew = Crew(
+    agents=[messenger],
+    tasks=[messaging_task]
+)
+
+crew.kickoff()
+```
+
+### 회의 관리
+
+```python
+from crewai import Agent, Task, Crew
+
+# 회의 관리를 위한 에이전트 생성
+meeting_scheduler = Agent(
+    role="회의 스케줄러",
+    goal="Teams 회의 생성 및 관리",
+    backstory="회의 일정 관리 및 정리를 담당하는 AI 어시스턴트.",
+    apps=['microsoft_teams/create_meeting', 'microsoft_teams/search_online_meetings_by_join_url']
+)
+
+# 회의 생성 작업
+schedule_meeting_task = Task(
+    description="내일 오전 10시에 1시간 동안 진행되는 '주간 팀 동기화' 제목의 Teams 회의를 생성하세요 (시간대가 포함된 적절한 ISO 8601 형식 사용).",
+    agent=meeting_scheduler,
+    expected_output="회의 세부 정보와 함께 Teams 회의가 성공적으로 생성됨."
+)
+
+crew = Crew(
+    agents=[meeting_scheduler],
+    tasks=[schedule_meeting_task]
+)
+
+crew.kickoff()
+```
+
 ## 문제 해결
 
 ### 일반적인 문제
@@ -148,11 +284,35 @@ crew.kickoff()
 
 - Microsoft 계정이 Teams 액세스에 필요한 권한을 가지고 있는지 확인하세요.
 - 필요한 범위: `Team.ReadBasic.All`, `Channel.ReadBasic.All`, `ChannelMessage.Send`, `ChannelMessage.Read.All`, `OnlineMeetings.ReadWrite`, `OnlineMeetings.Read`.
+- OAuth 연결에 필요한 모든 범위가 포함되어 있는지 확인하세요.
 
 **팀 및 채널 액세스**
 
 - 액세스하려는 팀의 멤버인지 확인하세요.
 - 팀 및 채널 ID가 올바른지 다시 확인하세요.
+- 팀 및 채널 ID는 `get_teams` 및 `get_channels` 작업을 사용하여 얻을 수 있습니다.
+
+**메시지 전송 문제**
+
+- `send_message`에 `team_id`, `channel_id`, `message`가 제공되는지 확인하세요.
+- 지정된 채널에 메시지를 보낼 권한이 있는지 확인하세요.
+- 메시지 형식에 따라 적절한 `content_type`(text 또는 html)을 선택하세요.
+
+**회의 생성**
+
+- `subject`, `startDateTime`, `endDateTime`이 제공되는지 확인하세요.
+- 날짜/시간 필드에 시간대가 포함된 적절한 ISO 8601 형식을 사용하세요 (예: '2024-01-20T10:00:00-08:00').
+- 회의 시간이 미래인지 확인하세요.
+
+**메시지 검색 제한**
+
+- `get_messages` 작업은 요청당 최대 50개 메시지만 검색할 수 있습니다.
+- 메시지는 역시간순(최신순)으로 반환됩니다.
+
+**회의 검색**
+
+- `search_online_meetings_by_join_url`의 경우 참가 URL이 정확하고 올바르게 형식화되어 있는지 확인하세요.
+- URL은 완전한 Teams 회의 참가 URL이어야 합니다.
 
 ### 도움 받기
 

docs/ko/enterprise/integrations/microsoft_word.mdx

@@ -97,6 +97,26 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=your_enterprise_token
     - `file_id` (string, 필수): 삭제할 문서의 ID.
 
   </Accordion>
+
+  <Accordion title="microsoft_word/copy_document">
+    **설명:** OneDrive의 새 위치에 문서를 복사합니다.
+
+    **매개변수:**
+    - `file_id` (string, 필수): 복사할 문서의 ID.
+    - `name` (string, 선택사항): 복사된 문서의 새 이름.
+    - `parent_id` (string, 선택사항): 대상 폴더의 ID (기본값: 루트).
+
+  </Accordion>
+
+  <Accordion title="microsoft_word/move_document">
+    **설명:** OneDrive의 새 위치로 문서를 이동합니다.
+
+    **매개변수:**
+    - `file_id` (string, 필수): 이동할 문서의 ID.
+    - `parent_id` (string, 필수): 대상 폴더의 ID.
+    - `name` (string, 선택사항): 이동된 문서의 새 이름.
+
+  </Accordion>
 </AccordionGroup>
 
 ## 사용 예제

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

@@ -73,6 +73,8 @@ flow.kickoff()
 | `default_outcome` | `str` | 아니오 | 피드백이 제공되지 않을 때 사용할 outcome. `emit`에 있어야 합니다 |
 | `metadata` | `dict` | 아니오 | 엔터프라이즈 통합을 위한 추가 데이터 |
 | `provider` | `HumanFeedbackProvider` | 아니오 | 비동기/논블로킹 피드백을 위한 커스텀 프로바이더. [비동기 인간 피드백](#비동기-인간-피드백-논블로킹) 참조 |
+| `learn` | `bool` | 아니오 | HITL 학습 활성화: 피드백에서 교훈을 추출하고 향후 출력을 사전 검토합니다. 기본값 `False`. [피드백에서 학습하기](#피드백에서-학습하기) 참조 |
+| `learn_limit` | `int` | 아니오 | 사전 검토를 위해 불러올 최대 과거 교훈 수. 기본값 `5` |
 
 ### 기본 사용법 (라우팅 없음)
 
@@ -96,33 +98,43 @@ def handle_feedback(self, result):
 `emit`을 지정하면, 데코레이터는 라우터가 됩니다. 인간의 자유 형식 피드백이 LLM에 의해 해석되어 지정된 outcome 중 하나로 매핑됩니다:
 
 ```python Code
-@start()
-@human_feedback(
-    message="이 콘텐츠의 출판을 승인하시겠습니까?",
-    emit=["approved", "rejected", "needs_revision"],
-    llm="gpt-4o-mini",
-    default_outcome="needs_revision",
-)
-def review_content(self):
-    return "블로그 게시물 초안 내용..."
+from crewai.flow.flow import Flow, start, listen, or_
+from crewai.flow.human_feedback import human_feedback
 
-@listen("approved")
-def publish(self, result):
-    print(f"출판 중! 사용자 의견: {result.feedback}")
+class ReviewFlow(Flow):
+    @start()
+    def generate_content(self):
+        return "블로그 게시물 초안 내용..."
 
-@listen("rejected")
-def discard(self, result):
-    print(f"폐기됨. 이유: {result.feedback}")
+    @human_feedback(
+        message="이 콘텐츠의 출판을 승인하시겠습니까?",
+        emit=["approved", "rejected", "needs_revision"],
+        llm="gpt-4o-mini",
+        default_outcome="needs_revision",
+    )
+    @listen(or_("generate_content", "needs_revision"))
+    def review_content(self):
+        return "블로그 게시물 초안 내용..."
 
-@listen("needs_revision")
-def revise(self, result):
-    print(f"다음을 기반으로 수정 중: {result.feedback}")
+    @listen("approved")
+    def publish(self, result):
+        print(f"출판 중! 사용자 의견: {result.feedback}")
+
+    @listen("rejected")
+    def discard(self, result):
+        print(f"폐기됨. 이유: {result.feedback}")
 ```
 
+사용자가 "더 자세한 내용이 필요합니다"와 같이 말하면, LLM이 이를 `"needs_revision"`으로 매핑하고, `or_()`를 통해 `review_content`가 다시 트리거됩니다 — 수정 루프가 생성됩니다. outcome이 `"approved"` 또는 `"rejected"`가 될 때까지 루프가 계속됩니다.
+
 <Tip>
 LLM은 가능한 경우 구조화된 출력(function calling)을 사용하여 응답이 지정된 outcome 중 하나임을 보장합니다. 이로 인해 라우팅이 신뢰할 수 있고 예측 가능해집니다.
 </Tip>
 
+<Warning>
+`@start()` 메서드는 flow 시작 시 한 번만 실행됩니다. 수정 루프가 필요한 경우, start 메서드를 review 메서드와 분리하고 review 메서드에 `@listen(or_("trigger", "revision_outcome"))`를 사용하여 self-loop을 활성화하세요.
+</Warning>
+
 ## HumanFeedbackResult
 
 `HumanFeedbackResult` 데이터클래스는 인간 피드백 상호작용에 대한 모든 정보를 포함합니다:
@@ -191,116 +203,162 @@ def summarize(self):
 <CodeGroup>
 
 ```python Code
-from crewai.flow.flow import Flow, start, listen
+from crewai.flow.flow import Flow, start, listen, or_
 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
+    status: str = "pending"
 
 
 class ContentApprovalFlow(Flow[ContentState]):
-    """콘텐츠를 생성하고 인간의 승인을 받는 Flow입니다."""
+    """콘텐츠를 생성하고 승인될 때까지 반복하는 Flow."""
 
     @start()
-    def get_topic(self):
-        self.state.topic = input("어떤 주제에 대해 글을 쓸까요? ")
-        return self.state.topic
-
-    @listen(get_topic)
-    def generate_draft(self, topic):
-        # 실제 사용에서는 LLM을 호출합니다
-        self.state.draft = f"# {topic}\n\n{topic}에 대한 초안입니다..."
+    def generate_draft(self):
+        self.state.draft = "# AI 안전\n\nAI 안전에 대한 초안..."
         return self.state.draft
 
-    @listen(generate_draft)
     @human_feedback(
-        message="이 초안을 검토해 주세요. 'approved', 'rejected'로 답하거나 수정 피드백을 제공해 주세요:",
+        message="이 초안을 검토해 주세요. 승인, 거부 또는 변경이 필요한 사항을 설명해 주세요:",
         emit=["approved", "rejected", "needs_revision"],
         llm="gpt-4o-mini",
         default_outcome="needs_revision",
     )
-    def review_draft(self, draft):
-        return draft
+    @listen(or_("generate_draft", "needs_revision"))
+    def review_draft(self):
+        self.state.revision_count += 1
+        return f"{self.state.draft} (v{self.state.revision_count})"
 
     @listen("approved")
     def publish_content(self, result: HumanFeedbackResult):
-        self.state.final_content = result.output
-        print("\n✅ 콘텐츠가 승인되어 출판되었습니다!")
-        print(f"검토자 코멘트: {result.feedback}")
+        self.state.status = "published"
+        print(f"콘텐츠 승인 및 게시! 리뷰어 의견: {result.feedback}")
         return "published"
 
     @listen("rejected")
     def handle_rejection(self, result: HumanFeedbackResult):
-        print("\n❌ 콘텐츠가 거부되었습니다")
-        print(f"이유: {result.feedback}")
+        self.state.status = "rejected"
+        print(f"콘텐츠 거부됨. 이유: {result.feedback}")
         return "rejected"
 
-    @listen("needs_revision")
-    def revise_content(self, result: HumanFeedbackResult):
-        self.state.revision_count += 1
-        print(f"\n📝 수정 #{self.state.revision_count} 요청됨")
-        print(f"피드백: {result.feedback}")
 
-        # 실제 Flow에서는 generate_draft로 돌아갈 수 있습니다
-        # 이 예제에서는 단순히 확인합니다
-        return "revision_requested"
-
-
-# Flow 실행
 flow = ContentApprovalFlow()
 result = flow.kickoff()
-print(f"\nFlow 완료. 요청된 수정: {flow.state.revision_count}")
+print(f"\nFlow 완료. 상태: {flow.state.status}, 검토 횟수: {flow.state.revision_count}")
 ```
 
 ```text Output
-어떤 주제에 대해 글을 쓸까요? AI 안전
+==================================================
+OUTPUT FOR REVIEW:
+==================================================
+# AI 안전
+
+AI 안전에 대한 초안... (v1)
+==================================================
+
+이 초안을 검토해 주세요. 승인, 거부 또는 변경이 필요한 사항을 설명해 주세요:
+(Press Enter to skip, or type your feedback)
+
+Your feedback: 더 자세한 내용이 필요합니다
 
 ==================================================
 OUTPUT FOR REVIEW:
 ==================================================
 # AI 안전
 
-AI 안전에 대한 초안입니다...
+AI 안전에 대한 초안... (v2)
 ==================================================
 
-이 초안을 검토해 주세요. 'approved', 'rejected'로 답하거나 수정 피드백을 제공해 주세요:
+이 초안을 검토해 주세요. 승인, 거부 또는 변경이 필요한 사항을 설명해 주세요:
 (Press Enter to skip, or type your feedback)
 
 Your feedback: 좋아 보입니다, 승인!
 
-✅ 콘텐츠가 승인되어 출판되었습니다!
-검토자 코멘트: 좋아 보입니다, 승인!
+콘텐츠 승인 및 게시! 리뷰어 의견: 좋아 보입니다, 승인!
 
-Flow 완료. 요청된 수정: 0
+Flow 완료. 상태: published, 검토 횟수: 2
 ```
 
 </CodeGroup>
 
 ## 다른 데코레이터와 결합하기
 
-`@human_feedback` 데코레이터는 다른 Flow 데코레이터와 함께 작동합니다. 가장 안쪽 데코레이터(함수에 가장 가까운)로 배치하세요:
+`@human_feedback` 데코레이터는 `@start()`, `@listen()`, `or_()`와 함께 작동합니다. 데코레이터 순서는 두 가지 모두 동작합니다—프레임워크가 양방향으로 속성을 전파합니다—하지만 권장 패턴은 다음과 같습니다:
 
 ```python Code
-# 올바름: @human_feedback이 가장 안쪽(함수에 가장 가까움)
+# Flow 시작 시 일회성 검토 (self-loop 없음)
 @start()
-@human_feedback(message="이것을 검토해 주세요:")
+@human_feedback(message="이것을 검토해 주세요:", emit=["approved", "rejected"], llm="gpt-4o-mini")
 def my_start_method(self):
     return "content"
 
+# 리스너에서 선형 검토 (self-loop 없음)
 @listen(other_method)
-@human_feedback(message="이것도 검토해 주세요:")
+@human_feedback(message="이것도 검토해 주세요:", emit=["good", "bad"], llm="gpt-4o-mini")
 def my_listener(self, data):
     return f"processed: {data}"
+
+# Self-loop: 수정을 위해 반복할 수 있는 검토
+@human_feedback(message="승인 또는 수정 요청?", emit=["approved", "revise"], llm="gpt-4o-mini")
+@listen(or_("upstream_method", "revise"))
+def review_with_loop(self):
+    return "content for review"
 ```
 
-<Tip>
-`@human_feedback`를 가장 안쪽 데코레이터(마지막/함수에 가장 가까움)로 배치하여 메서드를 직접 래핑하고 Flow 시스템에 전달하기 전에 반환 값을 캡처할 수 있도록 하세요.
-</Tip>
+### Self-loop 패턴
+
+수정 루프를 만들려면 `or_()`를 사용하여 검토 메서드가 **상위 트리거**와 **자체 수정 outcome**을 모두 리스닝해야 합니다:
+
+```python Code
+@start()
+def generate(self):
+    return "initial draft"
+
+@human_feedback(
+    message="승인하시겠습니까, 아니면 변경을 요청하시겠습니까?",
+    emit=["revise", "approved"],
+    llm="gpt-4o-mini",
+    default_outcome="approved",
+)
+@listen(or_("generate", "revise"))
+def review(self):
+    return "content"
+
+@listen("approved")
+def publish(self):
+    return "published"
+```
+
+outcome이 `"revise"`이면 flow가 `review`로 다시 라우팅됩니다 (`or_()`를 통해 `"revise"`를 리스닝하기 때문). outcome이 `"approved"`이면 flow가 `publish`로 계속됩니다. flow 엔진이 라우터를 "한 번만 실행" 규칙에서 제외하여 각 루프 반복마다 재실행할 수 있기 때문에 이 패턴이 동작합니다.
+
+### 체인된 라우터
+
+한 라우터의 outcome으로 트리거된 리스너가 그 자체로 라우터가 될 수 있습니다:
+
+```python Code
+@start()
+@human_feedback(message="첫 번째 검토:", emit=["approved", "rejected"], llm="gpt-4o-mini")
+def draft(self):
+    return "draft content"
+
+@listen("approved")
+@human_feedback(message="최종 검토:", emit=["publish", "revise"], llm="gpt-4o-mini")
+def final_review(self, prev):
+    return "final content"
+
+@listen("publish")
+def on_publish(self, prev):
+    return "published"
+```
+
+### 제한 사항
+
+- **`@start()` 메서드는 한 번만 실행**: `@start()` 메서드는 self-loop할 수 없습니다. 수정 주기가 필요하면 별도의 `@start()` 메서드를 진입점으로 사용하고 `@listen()` 메서드에 `@human_feedback`를 배치하세요.
+- **동일 메서드에 `@start()` + `@listen()` 불가**: 이는 Flow 프레임워크 제약입니다. 메서드는 시작점이거나 리스너여야 하며, 둘 다일 수 없습니다.
 
 ## 모범 사례
 
@@ -514,9 +572,9 @@ class ContentPipeline(Flow):
     @start()
     @human_feedback(
         message="이 콘텐츠의 출판을 승인하시겠습니까?",
-        emit=["approved", "rejected", "needs_revision"],
+        emit=["approved", "rejected"],
         llm="gpt-4o-mini",
-        default_outcome="needs_revision",
+        default_outcome="rejected",
         provider=SlackNotificationProvider("#content-reviews"),
     )
     def generate_content(self):
@@ -532,11 +590,6 @@ class ContentPipeline(Flow):
         print(f"보관됨. 이유: {result.feedback}")
         return {"status": "archived"}
 
-    @listen("needs_revision")
-    def queue_revision(self, result):
-        print(f"수정 대기열에 추가됨: {result.feedback}")
-        return {"status": "revision_needed"}
-
 
 # Flow 시작 (Slack 응답을 기다리며 일시 중지)
 def start_content_pipeline():
@@ -576,6 +629,64 @@ async def on_slack_feedback_async(flow_id: str, slack_message: str):
 5. **자동 영속성**: `HumanFeedbackPending`이 발생하면 상태가 자동으로 저장되며 기본적으로 `SQLiteFlowPersistence` 사용
 6. **커스텀 영속성**: 필요한 경우 `from_pending()`에 커스텀 영속성 인스턴스 전달
 
+## 피드백에서 학습하기
+
+`learn=True` 매개변수는 인간 검토자와 메모리 시스템 간의 피드백 루프를 활성화합니다. 활성화되면 시스템은 과거 인간의 수정 사항에서 학습하여 출력을 점진적으로 개선합니다.
+
+### 작동 방식
+
+1. **피드백 후**: LLM이 출력 + 피드백에서 일반화 가능한 교훈을 추출하고 `source="hitl"`로 메모리에 저장합니다. 피드백이 단순한 승인(예: "좋아 보입니다")인 경우 아무것도 저장하지 않습니다.
+2. **다음 검토 전**: 과거 HITL 교훈을 메모리에서 불러와 LLM이 인간이 보기 전에 출력을 개선하는 데 적용합니다.
+
+시간이 지남에 따라 각 수정 사항이 향후 검토에 반영되므로 인간은 점진적으로 더 나은 사전 검토된 출력을 보게 됩니다.
+
+### 예제
+
+```python Code
+class ArticleReviewFlow(Flow):
+    @start()
+    def generate_article(self):
+        return self.crew.kickoff(inputs={"topic": "AI Safety"}).raw
+
+    @human_feedback(
+        message="이 글 초안을 검토해 주세요:",
+        emit=["approved", "needs_revision"],
+        llm="gpt-4o-mini",
+        learn=True,
+    )
+    @listen(or_("generate_article", "needs_revision"))
+    def review_article(self):
+        return self.last_human_feedback.output if self.last_human_feedback else "article draft"
+
+    @listen("approved")
+    def publish(self):
+        print(f"Publishing: {self.last_human_feedback.output}")
+```
+
+**첫 번째 실행**: 인간이 원시 출력을 보고 "사실에 대한 주장에는 항상 인용을 포함하세요."라고 말합니다. 교훈이 추출되어 메모리에 저장됩니다.
+
+**두 번째 실행**: 시스템이 인용 교훈을 불러와 출력을 사전 검토하여 인용을 추가한 후 개선된 버전을 표시합니다. 인간의 역할이 "모든 것을 수정"에서 "시스템이 놓친 것을 찾기"로 전환됩니다.
+
+### 구성
+
+| 매개변수 | 기본값 | 설명 |
+|-----------|--------|------|
+| `learn` | `False` | HITL 학습 활성화 |
+| `learn_limit` | `5` | 사전 검토를 위해 불러올 최대 과거 교훈 수 |
+
+### 주요 설계 결정
+
+- **모든 것에 동일한 LLM 사용**: 데코레이터의 `llm` 매개변수는 outcome 매핑, 교훈 추출, 사전 검토에 공유됩니다. 여러 모델을 구성할 필요가 없습니다.
+- **구조화된 출력**: 추출과 사전 검토 모두 LLM이 지원하는 경우 Pydantic 모델과 함께 function calling을 사용하고, 그렇지 않으면 텍스트 파싱으로 폴백합니다.
+- **논블로킹 저장**: 교훈은 백그라운드 스레드에서 실행되는 `remember_many()`를 통해 저장됩니다 -- Flow는 즉시 계속됩니다.
+- **우아한 저하**: 추출 중 LLM이 실패하면 아무것도 저장하지 않습니다. 사전 검토 중 실패하면 원시 출력이 표시됩니다. 어느 쪽의 실패도 Flow를 차단하지 않습니다.
+- **범위/카테고리 불필요**: 교훈을 저장할 때 `source`만 전달됩니다. 인코딩 파이프라인이 범위, 카테고리, 중요도를 자동으로 추론합니다.
+
+<Note>
+`learn=True`는 Flow에 메모리가 사용 가능해야 합니다. Flow는 기본적으로 자동으로 메모리를 얻지만, `_skip_auto_memory`로 비활성화한 경우 HITL 학습은 조용히 건너뜁니다.
+</Note>
+
+
 ## 관련 문서
 
 - [Flow 개요](/ko/concepts/flows) - CrewAI Flow에 대해 알아보기
@@ -583,3 +694,4 @@ async def on_slack_feedback_async(flow_id: str, slack_message: str):
 - [Flow 영속성](/ko/concepts/flows#persistence) - Flow 상태 영속화
 - [@router를 사용한 라우팅](/ko/concepts/flows#router) - 조건부 라우팅에 대해 더 알아보기
 - [실행 시 인간 입력](/ko/learn/human-input-on-execution) - 태스크 수준 인간 입력
+- [메모리](/ko/concepts/memory) - HITL 학습에서 사용되는 통합 메모리 시스템

docs/pt-BR/enterprise/features/flow-hitl-management.mdx

@@ -38,22 +38,21 @@ O CrewAI Enterprise oferece um sistema abrangente de gerenciamento Human-in-the-
 Configure checkpoints de revisão humana em seus Flows usando o decorador `@human_feedback`. Quando a execução atinge um ponto de revisão, o sistema pausa, notifica o responsável via email e aguarda uma resposta.
 
 ```python
-from crewai.flow.flow import Flow, start, listen
+from crewai.flow.flow import Flow, start, listen, or_
 from crewai.flow.human_feedback import human_feedback, HumanFeedbackResult
 
 class ContentApprovalFlow(Flow):
     @start()
     def generate_content(self):
-        # IA gera conteúdo
         return "Texto de marketing gerado para campanha Q1..."
 
-    @listen(generate_content)
     @human_feedback(
         message="Por favor, revise este conteúdo para conformidade com a marca:",
         emit=["approved", "rejected", "needs_revision"],
     )
-    def review_content(self, content):
-        return content
+    @listen(or_("generate_content", "needs_revision"))
+    def review_content(self):
+        return "Texto de marketing para revisão..."
 
     @listen("approved")
     def publish_content(self, result: HumanFeedbackResult):
@@ -62,10 +61,6 @@ class ContentApprovalFlow(Flow):
     @listen("rejected")
     def archive_content(self, result: HumanFeedbackResult):
         print(f"Conteúdo rejeitado. Motivo: {result.feedback}")
-
-    @listen("needs_revision")
-    def revise_content(self, result: HumanFeedbackResult):
-        print(f"Revisão solicitada: {result.feedback}")
 ```
 
 Para detalhes completos de implementação, consulte o guia [Feedback Humano em Flows](/pt-BR/learn/human-feedback-in-flows).

docs/pt-BR/enterprise/guides/deploy-to-amp.mdx

@@ -176,6 +176,11 @@ Você precisa enviar seu crew para um repositório do GitHub. Caso ainda não te
       ![Definir Variáveis de Ambiente](/images/enterprise/set-env-variables.png)
     </Frame>
 
+    <Info>
+      Usando pacotes Python privados? Você também precisará adicionar suas credenciais de registro aqui.
+      Consulte [Registros de Pacotes Privados](/pt-BR/enterprise/guides/private-package-registry) para as variáveis necessárias.
+    </Info>
+
   </Step>
 
   <Step title="Implante Seu Crew">

docs/pt-BR/enterprise/guides/prepare-for-deployment.mdx

@@ -256,6 +256,12 @@ Antes da implantação, certifique-se de ter:
 1. **Chaves de API de LLM** prontas (OpenAI, Anthropic, Google, etc.)
 2. **Chaves de API de ferramentas** se estiver usando ferramentas externas (Serper, etc.)
 
+<Info>
+  Se seu projeto depende de pacotes de um **registro PyPI privado**, você também precisará configurar
+  credenciais de autenticação do registro como variáveis de ambiente. Consulte o guia
+  [Registros de Pacotes Privados](/pt-BR/enterprise/guides/private-package-registry) para mais detalhes.
+</Info>
+
 <Tip>
   Teste seu projeto localmente com as mesmas variáveis de ambiente antes de implantar
   para detectar problemas de configuração antecipadamente.

docs/pt-BR/enterprise/guides/private-package-registry.mdx

@@ -0,0 +1,263 @@
+---
+title: "Registros de Pacotes Privados"
+description: "Instale pacotes Python privados de registros PyPI autenticados no CrewAI AMP"
+icon: "lock"
+mode: "wide"
+---
+
+<Note>
+  Este guia aborda como configurar seu projeto CrewAI para instalar pacotes Python
+  de registros PyPI privados (Azure DevOps Artifacts, GitHub Packages, GitLab, AWS CodeArtifact, etc.)
+  ao implantar no CrewAI AMP.
+</Note>
+
+## Quando Você Precisa Disso
+
+Se seu projeto depende de pacotes Python internos ou proprietários hospedados em um registro privado
+em vez do PyPI público, você precisará:
+
+1. Informar ao UV **onde** encontrar o pacote (uma URL de index)
+2. Informar ao UV **quais** pacotes vêm desse index (um mapeamento de source)
+3. Fornecer **credenciais** para que o UV possa autenticar durante a instalação
+
+O CrewAI AMP usa [UV](https://docs.astral.sh/uv/) para resolução e instalação de dependências.
+O UV suporta registros privados autenticados por meio da configuração do `pyproject.toml` combinada
+com variáveis de ambiente para credenciais.
+
+## Passo 1: Configurar o pyproject.toml
+
+Três elementos trabalham juntos no seu `pyproject.toml`:
+
+### 1a. Declarar a dependência
+
+Adicione o pacote privado ao seu `[project.dependencies]` como qualquer outra dependência:
+
+```toml
+[project]
+dependencies = [
+    "crewai[tools]>=0.100.1,<1.0.0",
+    "my-private-package>=1.2.0",
+]
+```
+
+### 1b. Definir o index
+
+Registre seu registro privado como um index nomeado em `[[tool.uv.index]]`:
+
+```toml
+[[tool.uv.index]]
+name = "my-private-registry"
+url = "https://pkgs.dev.azure.com/my-org/_packaging/my-feed/pypi/simple/"
+explicit = true
+```
+
+<Info>
+  O campo `name` é importante — o UV o utiliza para construir os nomes das variáveis de ambiente
+  para autenticação (veja o [Passo 2](#passo-2-configurar-credenciais-de-autenticação) abaixo).
+
+  Definir `explicit = true` significa que o UV não consultará esse index para todos os pacotes — apenas
+  os que você mapear explicitamente em `[tool.uv.sources]`. Isso evita consultas desnecessárias
+  ao seu registro privado e protege contra ataques de confusão de dependências.
+</Info>
+
+### 1c. Mapear o pacote para o index
+
+Informe ao UV quais pacotes devem ser resolvidos a partir do seu index privado usando `[tool.uv.sources]`:
+
+```toml
+[tool.uv.sources]
+my-private-package = { index = "my-private-registry" }
+```
+
+### Exemplo completo
+
+```toml
+[project]
+name = "my-crew-project"
+version = "0.1.0"
+requires-python = ">=3.10,<=3.13"
+dependencies = [
+    "crewai[tools]>=0.100.1,<1.0.0",
+    "my-private-package>=1.2.0",
+]
+
+[tool.crewai]
+type = "crew"
+
+[[tool.uv.index]]
+name = "my-private-registry"
+url = "https://pkgs.dev.azure.com/my-org/_packaging/my-feed/pypi/simple/"
+explicit = true
+
+[tool.uv.sources]
+my-private-package = { index = "my-private-registry" }
+```
+
+Após atualizar o `pyproject.toml`, regenere seu arquivo lock:
+
+```bash
+uv lock
+```
+
+<Warning>
+  Sempre faça commit do `uv.lock` atualizado junto com as alterações no `pyproject.toml`.
+  O arquivo lock é obrigatório para implantação — veja [Preparar para Implantação](/pt-BR/enterprise/guides/prepare-for-deployment).
+</Warning>
+
+## Passo 2: Configurar Credenciais de Autenticação
+
+O UV autentica em indexes privados usando variáveis de ambiente que seguem uma convenção de nomenclatura
+baseada no nome do index que você definiu no `pyproject.toml`:
+
+```
+UV_INDEX_{UPPER_NAME}_USERNAME
+UV_INDEX_{UPPER_NAME}_PASSWORD
+```
+
+Onde `{UPPER_NAME}` é o nome do seu index convertido para **maiúsculas** com **hifens substituídos por underscores**.
+
+Por exemplo, um index chamado `my-private-registry` usa:
+
+| Variável | Valor |
+|----------|-------|
+| `UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME` | Seu nome de usuário ou nome do token do registro |
+| `UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD` | Sua senha ou token/PAT do registro |
+
+<Warning>
+  Essas variáveis de ambiente **devem** ser adicionadas pelas configurações de **Variáveis de Ambiente** do CrewAI AMP —
+  globalmente ou no nível da implantação. Elas não podem ser definidas em arquivos `.env` ou codificadas no seu projeto.
+
+  Veja [Configurar Variáveis de Ambiente no AMP](#configurar-variáveis-de-ambiente-no-amp) abaixo.
+</Warning>
+
+## Referência de Provedores de Registro
+
+A tabela abaixo mostra o formato da URL de index e os valores de credenciais para provedores de registro comuns.
+Substitua os valores de exemplo pelos detalhes reais da sua organização e feed.
+
+| Provedor | URL do Index | Usuário | Senha |
+|----------|-------------|---------|-------|
+| **Azure DevOps Artifacts** | `https://pkgs.dev.azure.com/{org}/_packaging/{feed}/pypi/simple/` | Qualquer string não vazia (ex: `token`) | Personal Access Token (PAT) com escopo Packaging Read |
+| **GitHub Packages** | `https://pypi.pkg.github.com/{owner}/simple/` | Nome de usuário do GitHub | Personal Access Token (classic) com escopo `read:packages` |
+| **GitLab Package Registry** | `https://gitlab.com/api/v4/projects/{project_id}/packages/pypi/simple/` | `__token__` | Project ou Personal Access Token com escopo `read_api` |
+| **AWS CodeArtifact** | Use a URL de `aws codeartifact get-repository-endpoint` | `aws` | Token de `aws codeartifact get-authorization-token` |
+| **Google Artifact Registry** | `https://{region}-python.pkg.dev/{project}/{repo}/simple/` | `_json_key_base64` | Chave de conta de serviço codificada em Base64 |
+| **JFrog Artifactory** | `https://{instance}.jfrog.io/artifactory/api/pypi/{repo}/simple/` | Nome de usuário ou email | Chave API ou token de identidade |
+| **Auto-hospedado (devpi, Nexus, etc.)** | URL da API simple do seu registro | Nome de usuário do registro | Senha do registro |
+
+<Tip>
+  Para **AWS CodeArtifact**, o token de autorização expira periodicamente.
+  Você precisará atualizar o valor de `UV_INDEX_*_PASSWORD` quando ele expirar.
+  Considere automatizar isso no seu pipeline de CI/CD.
+</Tip>
+
+## Configurar Variáveis de Ambiente no AMP
+
+As credenciais do registro privado devem ser configuradas como variáveis de ambiente no CrewAI AMP.
+Você tem duas opções:
+
+<Tabs>
+  <Tab title="Interface Web">
+    1. Faça login no [CrewAI AMP](https://app.crewai.com)
+    2. Navegue até sua automação
+    3. Abra a aba **Environment Variables**
+    4. Adicione cada variável (`UV_INDEX_*_USERNAME` e `UV_INDEX_*_PASSWORD`) com seu valor
+
+    Veja o passo [Deploy para AMP — Definir Variáveis de Ambiente](/pt-BR/enterprise/guides/deploy-to-amp#definir-as-variáveis-de-ambiente) para detalhes.
+  </Tab>
+  <Tab title="Implantação via CLI">
+    Adicione as variáveis ao seu arquivo `.env` local antes de executar `crewai deploy create`.
+    A CLI as transferirá com segurança para a plataforma:
+
+    ```bash
+    # .env
+    OPENAI_API_KEY=sk-...
+    UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME=token
+    UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD=your-pat-here
+    ```
+
+    ```bash
+    crewai deploy create
+    ```
+  </Tab>
+</Tabs>
+
+<Warning>
+  **Nunca** faça commit de credenciais no seu repositório. Use variáveis de ambiente do AMP para todos os segredos.
+  O arquivo `.env` deve estar listado no `.gitignore`.
+</Warning>
+
+Para atualizar credenciais em uma implantação existente, veja [Atualizar Seu Crew — Variáveis de Ambiente](/pt-BR/enterprise/guides/update-crew).
+
+## Como Tudo se Conecta
+
+Quando o CrewAI AMP faz o build da sua automação, o fluxo de resolução funciona assim:
+
+<Steps>
+  <Step title="Build inicia">
+    O AMP busca seu repositório e lê o `pyproject.toml` e o `uv.lock`.
+  </Step>
+  <Step title="UV resolve dependências">
+    O UV lê `[tool.uv.sources]` para determinar de qual index cada pacote deve vir.
+  </Step>
+  <Step title="UV autentica">
+    Para cada index privado, o UV busca `UV_INDEX_{NAME}_USERNAME` e `UV_INDEX_{NAME}_PASSWORD`
+    nas variáveis de ambiente que você configurou no AMP.
+  </Step>
+  <Step title="Pacotes são instalados">
+    O UV baixa e instala todos os pacotes — tanto públicos (do PyPI) quanto privados (do seu registro).
+  </Step>
+  <Step title="Automação executa">
+    Seu crew ou flow inicia com todas as dependências disponíveis.
+  </Step>
+</Steps>
+
+## Solução de Problemas
+
+### Erros de Autenticação Durante o Build
+
+**Sintoma**: Build falha com `401 Unauthorized` ou `403 Forbidden` ao resolver um pacote privado.
+
+**Verifique**:
+- Os nomes das variáveis de ambiente `UV_INDEX_*` correspondem exatamente ao nome do seu index (maiúsculas, hifens -> underscores)
+- As credenciais estão definidas nas variáveis de ambiente do AMP, não apenas em um `.env` local
+- Seu token/PAT tem as permissões de leitura necessárias para o feed de pacotes
+- O token não expirou (especialmente relevante para AWS CodeArtifact)
+
+### Pacote Não Encontrado
+
+**Sintoma**: `No matching distribution found for my-private-package`.
+
+**Verifique**:
+- A URL do index no `pyproject.toml` termina com `/simple/`
+- A entrada `[tool.uv.sources]` mapeia o nome correto do pacote para o nome correto do index
+- O pacote está realmente publicado no seu registro privado
+- Execute `uv lock` localmente com as mesmas credenciais para verificar se a resolução funciona
+
+### Conflitos no Arquivo Lock
+
+**Sintoma**: `uv lock` falha ou produz resultados inesperados após adicionar um index privado.
+
+**Solução**: Defina as credenciais localmente e regenere:
+
+```bash
+export UV_INDEX_MY_PRIVATE_REGISTRY_USERNAME=token
+export UV_INDEX_MY_PRIVATE_REGISTRY_PASSWORD=your-pat
+uv lock
+```
+
+Em seguida, faça commit do `uv.lock` atualizado.
+
+## Guias Relacionados
+
+<CardGroup cols={3}>
+  <Card title="Preparar para Implantação" icon="clipboard-check" href="/pt-BR/enterprise/guides/prepare-for-deployment">
+    Verifique a estrutura do projeto e as dependências antes de implantar.
+  </Card>
+  <Card title="Deploy para AMP" icon="rocket" href="/pt-BR/enterprise/guides/deploy-to-amp">
+    Implante seu crew ou flow e configure variáveis de ambiente.
+  </Card>
+  <Card title="Atualizar Seu Crew" icon="arrows-rotate" href="/pt-BR/enterprise/guides/update-crew">
+    Atualize variáveis de ambiente e envie alterações para uma implantação em execução.
+  </Card>
+</CardGroup>

docs/pt-BR/enterprise/integrations/google_contacts.mdx

@@ -200,6 +200,25 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
     - `clientData` (array, opcional): Dados específicos do cliente. Cada item é um objeto com `key` (string) e `value` (string).
 
   </Accordion>
+
+  <Accordion title="google_contacts/update_contact_group">
+    **Descrição:** Atualizar informações de um grupo de contatos.
+
+    **Parâmetros:**
+    - `resourceName` (string, obrigatório): O nome do recurso do grupo de contatos (ex: 'contactGroups/myContactGroup').
+    - `name` (string, obrigatório): O nome do grupo de contatos.
+    - `clientData` (array, opcional): Dados específicos do cliente. Cada item é um objeto com `key` (string) e `value` (string).
+
+  </Accordion>
+
+  <Accordion title="google_contacts/delete_contact_group">
+    **Descrição:** Excluir um grupo de contatos.
+
+    **Parâmetros:**
+    - `resourceName` (string, obrigatório): O nome do recurso do grupo de contatos a excluir (ex: 'contactGroups/myContactGroup').
+    - `deleteContacts` (boolean, opcional): Se os contatos do grupo também devem ser excluídos. Padrão: false
+
+  </Accordion>
 </AccordionGroup>
 
 ## Exemplos de Uso

docs/pt-BR/enterprise/integrations/google_docs.mdx

@@ -131,6 +131,297 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
     - `endIndex` (integer, obrigatório): O índice final do intervalo.
 
   </Accordion>
+
+  <Accordion title="google_docs/create_document_with_content">
+    **Descrição:** Criar um novo documento do Google com conteúdo em uma única ação.
+
+    **Parâmetros:**
+    - `title` (string, obrigatório): O título para o novo documento. Aparece no topo do documento e no Google Drive.
+    - `content` (string, opcional): O conteúdo de texto a inserir no documento. Use `\n` para novos parágrafos.
+
+  </Accordion>
+
+  <Accordion title="google_docs/append_text">
+    **Descrição:** Adicionar texto ao final de um documento do Google. Insere automaticamente no final do documento sem necessidade de especificar um índice.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento obtido da resposta de create_document ou URL.
+    - `text` (string, obrigatório): Texto a adicionar ao final do documento. Use `\n` para novos parágrafos.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_bold">
+    **Descrição:** Aplicar ou remover formatação de negrito em texto de um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
+    - `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
+    - `bold` (boolean, obrigatório): Defina `true` para aplicar negrito, `false` para remover negrito.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_italic">
+    **Descrição:** Aplicar ou remover formatação de itálico em texto de um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
+    - `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
+    - `italic` (boolean, obrigatório): Defina `true` para aplicar itálico, `false` para remover itálico.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_underline">
+    **Descrição:** Adicionar ou remover formatação de sublinhado em texto de um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
+    - `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
+    - `underline` (boolean, obrigatório): Defina `true` para sublinhar, `false` para remover sublinhado.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_strikethrough">
+    **Descrição:** Adicionar ou remover formatação de tachado em texto de um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
+    - `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
+    - `strikethrough` (boolean, obrigatório): Defina `true` para adicionar tachado, `false` para remover.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_font_size">
+    **Descrição:** Alterar o tamanho da fonte do texto em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
+    - `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
+    - `fontSize` (number, obrigatório): Tamanho da fonte em pontos. Tamanhos comuns: 10, 11, 12, 14, 16, 18, 24, 36.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_text_color">
+    **Descrição:** Alterar a cor do texto usando valores RGB (escala 0-1) em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do texto a formatar.
+    - `endIndex` (integer, obrigatório): Posição final do texto a formatar (exclusivo).
+    - `red` (number, obrigatório): Componente vermelho (0-1). Exemplo: `1` para vermelho total.
+    - `green` (number, obrigatório): Componente verde (0-1). Exemplo: `0.5` para metade verde.
+    - `blue` (number, obrigatório): Componente azul (0-1). Exemplo: `0` para sem azul.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_hyperlink">
+    **Descrição:** Transformar texto existente em um hyperlink clicável em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do texto a transformar em link.
+    - `endIndex` (integer, obrigatório): Posição final do texto a transformar em link (exclusivo).
+    - `url` (string, obrigatório): A URL para a qual o link deve apontar. Exemplo: `"https://example.com"`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/apply_heading_style">
+    **Descrição:** Aplicar um estilo de título ou parágrafo a um intervalo de texto em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do(s) parágrafo(s) a estilizar.
+    - `endIndex` (integer, obrigatório): Posição final do(s) parágrafo(s) a estilizar.
+    - `style` (string, obrigatório): O estilo a aplicar. Opções: `NORMAL_TEXT`, `TITLE`, `SUBTITLE`, `HEADING_1`, `HEADING_2`, `HEADING_3`, `HEADING_4`, `HEADING_5`, `HEADING_6`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_paragraph_alignment">
+    **Descrição:** Definir o alinhamento de texto para parágrafos em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do(s) parágrafo(s) a alinhar.
+    - `endIndex` (integer, obrigatório): Posição final do(s) parágrafo(s) a alinhar.
+    - `alignment` (string, obrigatório): Alinhamento do texto. Opções: `START` (esquerda), `CENTER`, `END` (direita), `JUSTIFIED`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/set_line_spacing">
+    **Descrição:** Definir o espaçamento entre linhas para parágrafos em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial do(s) parágrafo(s).
+    - `endIndex` (integer, obrigatório): Posição final do(s) parágrafo(s).
+    - `lineSpacing` (number, obrigatório): Espaçamento entre linhas como porcentagem. `100` = simples, `115` = 1.15x, `150` = 1.5x, `200` = duplo.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_paragraph_bullets">
+    **Descrição:** Converter parágrafos em uma lista com marcadores ou numerada em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial dos parágrafos a converter em lista.
+    - `endIndex` (integer, obrigatório): Posição final dos parágrafos a converter em lista.
+    - `bulletPreset` (string, obrigatório): Estilo de marcadores/numeração. Opções: `BULLET_DISC_CIRCLE_SQUARE`, `BULLET_DIAMONDX_ARROW3D_SQUARE`, `BULLET_CHECKBOX`, `BULLET_ARROW_DIAMOND_DISC`, `BULLET_STAR_CIRCLE_SQUARE`, `NUMBERED_DECIMAL_ALPHA_ROMAN`, `NUMBERED_DECIMAL_ALPHA_ROMAN_PARENS`, `NUMBERED_DECIMAL_NESTED`, `NUMBERED_UPPERALPHA_ALPHA_ROMAN`, `NUMBERED_UPPERROMAN_UPPERALPHA_DECIMAL`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_paragraph_bullets">
+    **Descrição:** Remover marcadores ou numeração de parágrafos em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `startIndex` (integer, obrigatório): Posição inicial dos parágrafos de lista.
+    - `endIndex` (integer, obrigatório): Posição final dos parágrafos de lista.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_with_content">
+    **Descrição:** Inserir uma tabela com conteúdo em um documento do Google em uma única ação. Forneça o conteúdo como um array 2D.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `rows` (integer, obrigatório): Número de linhas na tabela.
+    - `columns` (integer, obrigatório): Número de colunas na tabela.
+    - `index` (integer, opcional): Posição para inserir a tabela. Se não fornecido, a tabela é inserida no final do documento.
+    - `content` (array, obrigatório): Conteúdo da tabela como um array 2D. Cada array interno é uma linha. Exemplo: `[["Ano", "Receita"], ["2023", "$43B"], ["2024", "$45B"]]`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_row">
+    **Descrição:** Inserir uma nova linha acima ou abaixo de uma célula de referência em uma tabela existente.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `tableStartIndex` (integer, obrigatório): O índice inicial da tabela. Obtenha de get_document.
+    - `rowIndex` (integer, obrigatório): Índice da linha (baseado em 0) da célula de referência.
+    - `columnIndex` (integer, opcional): Índice da coluna (baseado em 0) da célula de referência. Padrão: `0`.
+    - `insertBelow` (boolean, opcional): Se `true`, insere abaixo da linha de referência. Se `false`, insere acima. Padrão: `true`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_table_column">
+    **Descrição:** Inserir uma nova coluna à esquerda ou à direita de uma célula de referência em uma tabela existente.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
+    - `rowIndex` (integer, opcional): Índice da linha (baseado em 0) da célula de referência. Padrão: `0`.
+    - `columnIndex` (integer, obrigatório): Índice da coluna (baseado em 0) da célula de referência.
+    - `insertRight` (boolean, opcional): Se `true`, insere à direita. Se `false`, insere à esquerda. Padrão: `true`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_table_row">
+    **Descrição:** Excluir uma linha de uma tabela existente em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
+    - `rowIndex` (integer, obrigatório): Índice da linha (baseado em 0) a excluir.
+    - `columnIndex` (integer, opcional): Índice da coluna (baseado em 0) de qualquer célula na linha. Padrão: `0`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_table_column">
+    **Descrição:** Excluir uma coluna de uma tabela existente em um documento do Google.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
+    - `rowIndex` (integer, opcional): Índice da linha (baseado em 0) de qualquer célula na coluna. Padrão: `0`.
+    - `columnIndex` (integer, obrigatório): Índice da coluna (baseado em 0) a excluir.
+
+  </Accordion>
+
+  <Accordion title="google_docs/merge_table_cells">
+    **Descrição:** Mesclar um intervalo de células de tabela em uma única célula. O conteúdo de todas as células é preservado.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
+    - `rowIndex` (integer, obrigatório): Índice da linha inicial (baseado em 0) para a mesclagem.
+    - `columnIndex` (integer, obrigatório): Índice da coluna inicial (baseado em 0) para a mesclagem.
+    - `rowSpan` (integer, obrigatório): Número de linhas a mesclar.
+    - `columnSpan` (integer, obrigatório): Número de colunas a mesclar.
+
+  </Accordion>
+
+  <Accordion title="google_docs/unmerge_table_cells">
+    **Descrição:** Desfazer a mesclagem de células de tabela previamente mescladas, retornando-as a células individuais.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `tableStartIndex` (integer, obrigatório): O índice inicial da tabela.
+    - `rowIndex` (integer, obrigatório): Índice da linha (baseado em 0) da célula mesclada.
+    - `columnIndex` (integer, obrigatório): Índice da coluna (baseado em 0) da célula mesclada.
+    - `rowSpan` (integer, obrigatório): Número de linhas que a célula mesclada abrange.
+    - `columnSpan` (integer, obrigatório): Número de colunas que a célula mesclada abrange.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_inline_image">
+    **Descrição:** Inserir uma imagem de uma URL pública em um documento do Google. A imagem deve ser publicamente acessível, ter menos de 50MB e estar no formato PNG/JPEG/GIF.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `uri` (string, obrigatório): URL pública da imagem. Deve ser acessível sem autenticação.
+    - `index` (integer, opcional): Posição para inserir a imagem. Se não fornecido, a imagem é inserida no final do documento. Padrão: `1`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/insert_section_break">
+    **Descrição:** Inserir uma quebra de seção para criar seções de documento com formatação diferente.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `index` (integer, obrigatório): Posição para inserir a quebra de seção.
+    - `sectionType` (string, obrigatório): O tipo de quebra de seção. Opções: `CONTINUOUS` (permanece na mesma página), `NEXT_PAGE` (inicia uma nova página).
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_header">
+    **Descrição:** Criar um cabeçalho para o documento. Retorna um headerId que pode ser usado com insert_text para adicionar conteúdo ao cabeçalho.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `type` (string, opcional): Tipo de cabeçalho. Opções: `DEFAULT`. Padrão: `DEFAULT`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/create_footer">
+    **Descrição:** Criar um rodapé para o documento. Retorna um footerId que pode ser usado com insert_text para adicionar conteúdo ao rodapé.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `type` (string, opcional): Tipo de rodapé. Opções: `DEFAULT`. Padrão: `DEFAULT`.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_header">
+    **Descrição:** Excluir um cabeçalho do documento. Use get_document para encontrar o headerId.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `headerId` (string, obrigatório): O ID do cabeçalho a excluir. Obtenha da resposta de get_document.
+
+  </Accordion>
+
+  <Accordion title="google_docs/delete_footer">
+    **Descrição:** Excluir um rodapé do documento. Use get_document para encontrar o footerId.
+
+    **Parâmetros:**
+    - `documentId` (string, obrigatório): O ID do documento.
+    - `footerId` (string, obrigatório): O ID do rodapé a excluir. Obtenha da resposta de get_document.
+
+  </Accordion>
 </AccordionGroup>
 
 ## Exemplos de Uso

docs/pt-BR/enterprise/integrations/google_slides.mdx

@@ -61,6 +61,22 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/get_presentation_metadata">
+    **Descrição:** Obter metadados leves de uma apresentação (título, número de slides, IDs dos slides). Use isso primeiro antes de recuperar o conteúdo completo.
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação a ser recuperada.
+
+  </Accordion>
+
+  <Accordion title="google_slides/get_presentation_text">
+    **Descrição:** Extrair todo o conteúdo de texto de uma apresentação. Retorna IDs dos slides e texto de formas e tabelas apenas (sem formatação).
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+
+  </Accordion>
+
   <Accordion title="google_slides/get_presentation">
     **Descrição:** Recupera uma apresentação por ID.
 
@@ -80,6 +96,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/get_slide_text">
+    **Descrição:** Extrair conteúdo de texto de um único slide. Retorna apenas texto de formas e tabelas (sem formatação ou estilo).
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `pageObjectId` (string, obrigatório): O ID do slide/página para obter o texto.
+
+  </Accordion>
+
   <Accordion title="google_slides/get_page">
     **Descrição:** Recupera uma página específica por seu ID.
 
@@ -98,6 +123,120 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
 
   </Accordion>
 
+  <Accordion title="google_slides/create_slide">
+    **Descrição:** Adicionar um slide em branco adicional a uma apresentação. Novas apresentações já possuem um slide em branco - verifique get_presentation_metadata primeiro. Para slides com áreas de título/corpo, use create_slide_with_layout.
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `insertionIndex` (integer, opcional): Onde inserir o slide (baseado em 0). Se omitido, adiciona no final.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_slide_with_layout">
+    **Descrição:** Criar um slide com layout predefinido contendo áreas de espaço reservado para título, corpo, etc. Melhor que create_slide para conteúdo estruturado. Após criar, use get_page para encontrar os IDs de espaço reservado, depois insira texto neles.
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `layout` (string, obrigatório): Tipo de layout. Um de: `BLANK`, `TITLE`, `TITLE_AND_BODY`, `TITLE_AND_TWO_COLUMNS`, `TITLE_ONLY`, `SECTION_HEADER`, `ONE_COLUMN_TEXT`, `MAIN_POINT`, `BIG_NUMBER`. TITLE_AND_BODY é melhor para título+descrição. TITLE para slides apenas com título. SECTION_HEADER para divisores de seção.
+    - `insertionIndex` (integer, opcional): Onde inserir (baseado em 0). Se omitido, adiciona no final.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_text_box">
+    **Descrição:** Criar uma caixa de texto em um slide com conteúdo. Use para títulos, descrições, parágrafos - não para tabelas. Opcionalmente especifique posição (x, y) e tamanho (width, height) em unidades EMU (914400 EMU = 1 polegada).
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideId` (string, obrigatório): O ID do slide para adicionar a caixa de texto.
+    - `text` (string, obrigatório): O conteúdo de texto da caixa de texto.
+    - `x` (integer, opcional): Posição X em EMU (914400 = 1 polegada). Padrão: 914400 (1 polegada da esquerda).
+    - `y` (integer, opcional): Posição Y em EMU (914400 = 1 polegada). Padrão: 914400 (1 polegada do topo).
+    - `width` (integer, opcional): Largura em EMU. Padrão: 7315200 (~8 polegadas).
+    - `height` (integer, opcional): Altura em EMU. Padrão: 914400 (~1 polegada).
+
+  </Accordion>
+
+  <Accordion title="google_slides/delete_slide">
+    **Descrição:** Remover um slide de uma apresentação. Use get_presentation primeiro para encontrar o ID do slide.
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideId` (string, obrigatório): O ID do objeto do slide a excluir. Obtenha de get_presentation.
+
+  </Accordion>
+
+  <Accordion title="google_slides/duplicate_slide">
+    **Descrição:** Criar uma cópia de um slide existente. A duplicata é inserida imediatamente após o original.
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideId` (string, obrigatório): O ID do objeto do slide a duplicar. Obtenha de get_presentation.
+
+  </Accordion>
+
+  <Accordion title="google_slides/move_slides">
+    **Descrição:** Reordenar slides movendo-os para uma nova posição. Os IDs dos slides devem estar na ordem atual da apresentação (sem duplicatas).
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideIds` (array de strings, obrigatório): Array de IDs dos slides a mover. Obrigatoriamente na ordem atual da apresentação.
+    - `insertionIndex` (integer, obrigatório): Posição de destino (baseado em 0). 0 = início, número de slides = final.
+
+  </Accordion>
+
+  <Accordion title="google_slides/insert_youtube_video">
+    **Descrição:** Incorporar um vídeo do YouTube em um slide. O ID do vídeo é o valor após "v=" nas URLs do YouTube (ex: para youtube.com/watch?v=abc123, use "abc123").
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideId` (string, obrigatório): O ID do slide para adicionar o vídeo. Obtenha de get_presentation.
+    - `videoId` (string, obrigatório): O ID do vídeo do YouTube (o valor após v= na URL).
+
+  </Accordion>
+
+  <Accordion title="google_slides/insert_drive_video">
+    **Descrição:** Incorporar um vídeo do Google Drive em um slide. O ID do arquivo pode ser encontrado na URL do arquivo no Drive.
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideId` (string, obrigatório): O ID do slide para adicionar o vídeo. Obtenha de get_presentation.
+    - `fileId` (string, obrigatório): O ID do arquivo do Google Drive do vídeo.
+
+  </Accordion>
+
+  <Accordion title="google_slides/set_slide_background_image">
+    **Descrição:** Definir uma imagem de fundo para um slide. A URL da imagem deve ser publicamente acessível.
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideId` (string, obrigatório): O ID do slide para definir o fundo. Obtenha de get_presentation.
+    - `imageUrl` (string, obrigatório): URL publicamente acessível da imagem a usar como fundo.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_table">
+    **Descrição:** Criar uma tabela vazia em um slide. Para criar uma tabela com conteúdo, use create_table_with_content.
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideId` (string, obrigatório): O ID do slide para adicionar a tabela. Obtenha de get_presentation.
+    - `rows` (integer, obrigatório): Número de linhas na tabela.
+    - `columns` (integer, obrigatório): Número de colunas na tabela.
+
+  </Accordion>
+
+  <Accordion title="google_slides/create_table_with_content">
+    **Descrição:** Criar uma tabela com conteúdo em uma única ação. Forneça o conteúdo como uma matriz 2D onde cada array interno é uma linha. Exemplo: [["Cabeçalho1", "Cabeçalho2"], ["Linha1Col1", "Linha1Col2"]].
+
+    **Parâmetros:**
+    - `presentationId` (string, obrigatório): O ID da apresentação.
+    - `slideId` (string, obrigatório): O ID do slide para adicionar a tabela. Obtenha de get_presentation.
+    - `rows` (integer, obrigatório): Número de linhas na tabela.
+    - `columns` (integer, obrigatório): Número de colunas na tabela.
+    - `content` (array, obrigatório): Conteúdo da tabela como matriz 2D. Cada array interno é uma linha. Exemplo: [["Ano", "Receita"], ["2023", "$10M"]].
+
+  </Accordion>
+
   <Accordion title="google_slides/import_data_from_sheet">
     **Descrição:** Importa dados de uma planilha do Google para uma apresentação.
 

docs/pt-BR/enterprise/integrations/microsoft_excel.mdx

@@ -148,6 +148,16 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_excel/get_table_data">
+    **Descrição:** Obter dados de uma tabela específica em uma planilha do Excel.
+
+    **Parâmetros:**
+    - `file_id` (string, obrigatório): O ID do arquivo Excel.
+    - `worksheet_name` (string, obrigatório): Nome da planilha.
+    - `table_name` (string, obrigatório): Nome da tabela.
+
+  </Accordion>
+
   <Accordion title="microsoft_excel/create_chart">
     **Descrição:** Criar um gráfico em uma planilha do Excel.
 
@@ -180,6 +190,15 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_excel/get_used_range_metadata">
+    **Descrição:** Obter os metadados do intervalo usado (apenas dimensões, sem dados) de uma planilha do Excel.
+
+    **Parâmetros:**
+    - `file_id` (string, obrigatório): O ID do arquivo Excel.
+    - `worksheet_name` (string, obrigatório): Nome da planilha.
+
+  </Accordion>
+
   <Accordion title="microsoft_excel/list_charts">
     **Descrição:** Obter todos os gráficos em uma planilha do Excel.
 

docs/pt-BR/enterprise/integrations/microsoft_onedrive.mdx

@@ -150,6 +150,49 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
     - `item_id` (string, obrigatório): O ID do arquivo.
 
   </Accordion>
+
+  <Accordion title="microsoft_onedrive/list_files_by_path">
+    **Descrição:** Listar arquivos e pastas em um caminho específico do OneDrive.
+
+    **Parâmetros:**
+    - `folder_path` (string, obrigatório): O caminho da pasta (ex: 'Documents/Reports').
+    - `top` (integer, opcional): Número de itens a recuperar (máx 1000). Padrão: 50.
+    - `orderby` (string, opcional): Ordenar por campo (ex: "name asc", "lastModifiedDateTime desc"). Padrão: "name asc".
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_recent_files">
+    **Descrição:** Obter arquivos acessados recentemente no OneDrive.
+
+    **Parâmetros:**
+    - `top` (integer, opcional): Número de itens a recuperar (máx 200). Padrão: 25.
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_shared_with_me">
+    **Descrição:** Obter arquivos e pastas compartilhados com o usuário.
+
+    **Parâmetros:**
+    - `top` (integer, opcional): Número de itens a recuperar (máx 200). Padrão: 50.
+    - `orderby` (string, opcional): Ordenar por campo. Padrão: "name asc".
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/get_file_by_path">
+    **Descrição:** Obter informações sobre um arquivo ou pasta específica pelo caminho.
+
+    **Parâmetros:**
+    - `file_path` (string, obrigatório): O caminho do arquivo ou pasta (ex: 'Documents/report.docx').
+
+  </Accordion>
+
+  <Accordion title="microsoft_onedrive/download_file_by_path">
+    **Descrição:** Baixar um arquivo do OneDrive pelo seu caminho.
+
+    **Parâmetros:**
+    - `file_path` (string, obrigatório): O caminho do arquivo (ex: 'Documents/report.docx').
+
+  </Accordion>
 </AccordionGroup>
 
 ## Exemplos de Uso

docs/pt-BR/enterprise/integrations/microsoft_outlook.mdx

@@ -132,6 +132,74 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
     - `companyName` (string, opcional): Nome da empresa do contato.
 
   </Accordion>
+
+  <Accordion title="microsoft_outlook/get_message">
+    **Descrição:** Obter uma mensagem de email específica por ID.
+
+    **Parâmetros:**
+    - `message_id` (string, obrigatório): O identificador único da mensagem. Obter pela ação get_messages.
+    - `select` (string, opcional): Lista separada por vírgulas de propriedades a retornar. Exemplo: "id,subject,body,from,receivedDateTime". Padrão: "id,subject,body,from,toRecipients,receivedDateTime".
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/reply_to_email">
+    **Descrição:** Responder a uma mensagem de email.
+
+    **Parâmetros:**
+    - `message_id` (string, obrigatório): O identificador único da mensagem a responder. Obter pela ação get_messages.
+    - `comment` (string, obrigatório): O conteúdo da mensagem de resposta. Pode ser texto simples ou HTML. A mensagem original será citada abaixo deste conteúdo.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/forward_email">
+    **Descrição:** Encaminhar uma mensagem de email.
+
+    **Parâmetros:**
+    - `message_id` (string, obrigatório): O identificador único da mensagem a encaminhar. Obter pela ação get_messages.
+    - `to_recipients` (array, obrigatório): Array de endereços de email dos destinatários. Exemplo: ["john@example.com", "jane@example.com"].
+    - `comment` (string, opcional): Mensagem opcional a incluir acima do conteúdo encaminhado. Pode ser texto simples ou HTML.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/mark_message_read">
+    **Descrição:** Marcar uma mensagem como lida ou não lida.
+
+    **Parâmetros:**
+    - `message_id` (string, obrigatório): O identificador único da mensagem. Obter pela ação get_messages.
+    - `is_read` (boolean, obrigatório): Definir como true para marcar como lida, false para marcar como não lida.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/delete_message">
+    **Descrição:** Excluir uma mensagem de email.
+
+    **Parâmetros:**
+    - `message_id` (string, obrigatório): O identificador único da mensagem a excluir. Obter pela ação get_messages.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/update_event">
+    **Descrição:** Atualizar um evento de calendário existente.
+
+    **Parâmetros:**
+    - `event_id` (string, obrigatório): O identificador único do evento. Obter pela ação get_calendar_events.
+    - `subject` (string, opcional): Novo assunto/título do evento.
+    - `start_time` (string, opcional): Nova hora de início no formato ISO 8601 (ex: "2024-01-20T10:00:00"). OBRIGATÓRIO: Também deve fornecer start_timezone ao usar este campo.
+    - `start_timezone` (string, opcional): Fuso horário da hora de início. OBRIGATÓRIO ao atualizar start_time. Exemplos: "Pacific Standard Time", "Eastern Standard Time", "UTC".
+    - `end_time` (string, opcional): Nova hora de término no formato ISO 8601. OBRIGATÓRIO: Também deve fornecer end_timezone ao usar este campo.
+    - `end_timezone` (string, opcional): Fuso horário da hora de término. OBRIGATÓRIO ao atualizar end_time. Exemplos: "Pacific Standard Time", "Eastern Standard Time", "UTC".
+    - `location` (string, opcional): Novo local do evento.
+    - `body` (string, opcional): Novo corpo/descrição do evento. Suporta formatação HTML.
+
+  </Accordion>
+
+  <Accordion title="microsoft_outlook/delete_event">
+    **Descrição:** Excluir um evento de calendário.
+
+    **Parâmetros:**
+    - `event_id` (string, obrigatório): O identificador único do evento a excluir. Obter pela ação get_calendar_events.
+
+  </Accordion>
 </AccordionGroup>
 
 ## Exemplos de Uso

docs/pt-BR/enterprise/integrations/microsoft_sharepoint.mdx

@@ -77,6 +77,17 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
 
   </Accordion>
 
+  <Accordion title="microsoft_sharepoint/get_drives">
+    **Descrição:** Listar todas as bibliotecas de documentos (drives) em um site do SharePoint. Use isto para descobrir bibliotecas disponíveis antes de usar operações de arquivo.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `top` (integer, opcional): Número máximo de drives a retornar por página (1-999). Padrão: 100
+    - `skip_token` (string, opcional): Token de paginação de uma resposta anterior para buscar a próxima página de resultados.
+    - `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'id,name,webUrl,driveType').
+
+  </Accordion>
+
   <Accordion title="microsoft_sharepoint/get_site_lists">
     **Descrição:** Obter todas as listas em um site do SharePoint.
 
@@ -145,20 +156,317 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
 
   </Accordion>
 
-  <Accordion title="microsoft_sharepoint/get_drive_items">
-    **Descrição:** Obter arquivos e pastas de uma biblioteca de documentos do SharePoint.
+  <Accordion title="microsoft_sharepoint/list_files">
+    **Descrição:** Recuperar arquivos e pastas de uma biblioteca de documentos do SharePoint. Por padrão, lista a pasta raiz, mas você pode navegar em subpastas fornecendo um folder_id.
 
     **Parâmetros:**
-    - `site_id` (string, obrigatório): O ID do site do SharePoint.
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `folder_id` (string, opcional): O ID da pasta para listar o conteúdo. Use 'root' para a pasta raiz, ou forneça um ID de pasta de uma chamada anterior de list_files. Padrão: 'root'
+    - `top` (integer, opcional): Número máximo de itens a retornar por página (1-1000). Padrão: 50
+    - `skip_token` (string, opcional): Token de paginação de uma resposta anterior para buscar a próxima página de resultados.
+    - `orderby` (string, opcional): Ordem de classificação dos resultados (ex: 'name asc', 'size desc', 'lastModifiedDateTime desc'). Padrão: 'name asc'
+    - `filter` (string, opcional): Filtro OData para restringir resultados (ex: 'file ne null' apenas para arquivos, 'folder ne null' apenas para pastas).
+    - `select` (string, opcional): Lista de campos separados por vírgula para retornar (ex: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
 
   </Accordion>
 
-  <Accordion title="microsoft_sharepoint/delete_drive_item">
-    **Descrição:** Excluir um arquivo ou pasta da biblioteca de documentos do SharePoint.
+  <Accordion title="microsoft_sharepoint/delete_file">
+    **Descrição:** Excluir um arquivo ou pasta de uma biblioteca de documentos do SharePoint. Para pastas, todo o conteúdo é excluído recursivamente. Os itens são movidos para a lixeira do site.
 
     **Parâmetros:**
-    - `site_id` (string, obrigatório): O ID do site do SharePoint.
-    - `item_id` (string, obrigatório): O ID do arquivo ou pasta a excluir.
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo ou pasta a excluir. Obtenha de list_files.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_files_by_path">
+    **Descrição:** Listar arquivos e pastas em uma pasta de biblioteca de documentos do SharePoint pelo caminho. Mais eficiente do que múltiplas chamadas list_files para navegação profunda.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `folder_path` (string, obrigatório): O caminho completo para a pasta sem barras iniciais/finais (ex: 'Documents', 'Reports/2024/Q1').
+    - `top` (integer, opcional): Número máximo de itens a retornar por página (1-1000). Padrão: 50
+    - `skip_token` (string, opcional): Token de paginação de uma resposta anterior para buscar a próxima página de resultados.
+    - `orderby` (string, opcional): Ordem de classificação dos resultados (ex: 'name asc', 'size desc'). Padrão: 'name asc'
+    - `select` (string, opcional): Lista de campos separados por vírgula para retornar (ex: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/download_file">
+    **Descrição:** Baixar conteúdo bruto de um arquivo de uma biblioteca de documentos do SharePoint. Use apenas para arquivos de texto simples (.txt, .csv, .json). Para arquivos Excel, use as ações específicas de Excel. Para arquivos Word, use get_word_document_content.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo a baixar. Obtenha de list_files ou list_files_by_path.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_file_info">
+    **Descrição:** Recuperar metadados detalhados de um arquivo ou pasta específico em uma biblioteca de documentos do SharePoint, incluindo nome, tamanho, datas de criação/modificação e informações do autor.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo ou pasta. Obtenha de list_files ou list_files_by_path.
+    - `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'id,name,size,createdDateTime,lastModifiedDateTime,webUrl,createdBy,lastModifiedBy').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_folder">
+    **Descrição:** Criar uma nova pasta em uma biblioteca de documentos do SharePoint. Por padrão, cria a pasta na raiz; use parent_id para criar subpastas.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `folder_name` (string, obrigatório): Nome para a nova pasta. Não pode conter: \ / : * ? " < > |
+    - `parent_id` (string, opcional): O ID da pasta pai. Use 'root' para a raiz da biblioteca de documentos, ou forneça um ID de pasta de list_files. Padrão: 'root'
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/search_files">
+    **Descrição:** Pesquisar arquivos e pastas em uma biblioteca de documentos do SharePoint por palavras-chave. Pesquisa nomes de arquivos, nomes de pastas e conteúdo de arquivos para documentos Office. Não use curingas ou caracteres especiais.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `query` (string, obrigatório): Palavras-chave de pesquisa (ex: 'relatório', 'orçamento 2024'). Curingas como *.txt não são suportados.
+    - `top` (integer, opcional): Número máximo de resultados a retornar por página (1-1000). Padrão: 50
+    - `skip_token` (string, opcional): Token de paginação de uma resposta anterior para buscar a próxima página de resultados.
+    - `select` (string, opcional): Lista de campos separados por vírgula para retornar (ex: 'id,name,size,folder,file,webUrl,lastModifiedDateTime').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/copy_file">
+    **Descrição:** Copiar um arquivo ou pasta para um novo local dentro do SharePoint. O item original permanece inalterado. A operação de cópia é assíncrona para arquivos grandes.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo ou pasta a copiar. Obtenha de list_files ou search_files.
+    - `destination_folder_id` (string, obrigatório): O ID da pasta de destino. Use 'root' para a pasta raiz, ou um ID de pasta de list_files.
+    - `new_name` (string, opcional): Novo nome para a cópia. Se não fornecido, o nome original é usado.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/move_file">
+    **Descrição:** Mover um arquivo ou pasta para um novo local dentro do SharePoint. O item é removido de sua localização original. Para pastas, todo o conteúdo é movido também.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo ou pasta a mover. Obtenha de list_files ou search_files.
+    - `destination_folder_id` (string, obrigatório): O ID da pasta de destino. Use 'root' para a pasta raiz, ou um ID de pasta de list_files.
+    - `new_name` (string, opcional): Novo nome para o item movido. Se não fornecido, o nome original é mantido.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_worksheets">
+    **Descrição:** Listar todas as planilhas (abas) em uma pasta de trabalho Excel armazenada em uma biblioteca de documentos do SharePoint. Use o nome da planilha retornado com outras ações de Excel.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'id,name,position,visibility').
+    - `filter` (string, opcional): Expressão de filtro OData (ex: "visibility eq 'Visible'" para excluir planilhas ocultas).
+    - `top` (integer, opcional): Número máximo de planilhas a retornar. Mínimo: 1, Máximo: 999
+    - `orderby` (string, opcional): Ordem de classificação (ex: 'position asc' para retornar planilhas na ordem das abas).
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_excel_worksheet">
+    **Descrição:** Criar uma nova planilha (aba) em uma pasta de trabalho Excel armazenada em uma biblioteca de documentos do SharePoint. A nova planilha é adicionada no final da lista de abas.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `name` (string, obrigatório): Nome para a nova planilha. Máximo de 31 caracteres. Não pode conter: \ / * ? : [ ]. Deve ser único na pasta de trabalho.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_range_data">
+    **Descrição:** Recuperar valores de células de um intervalo específico em uma planilha Excel armazenada no SharePoint. Para ler todos os dados sem saber as dimensões, use get_excel_used_range em vez disso.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha (aba) para leitura. Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
+    - `range` (string, obrigatório): Intervalo de células em notação A1 (ex: 'A1:C10', 'A:C', '1:5', 'A1').
+    - `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'address,values,formulas,numberFormat,text').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/update_excel_range_data">
+    **Descrição:** Escrever valores em um intervalo específico em uma planilha Excel armazenada no SharePoint. Sobrescreve o conteúdo existente das células. As dimensões do array de valores devem corresponder exatamente às dimensões do intervalo.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha (aba) a atualizar. Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
+    - `range` (string, obrigatório): Intervalo de células em notação A1 onde os valores serão escritos (ex: 'A1:C3' para um bloco 3x3).
+    - `values` (array, obrigatório): Array 2D de valores (linhas contendo células). Exemplo para A1:B2: [["Cabeçalho1", "Cabeçalho2"], ["Valor1", "Valor2"]]. Use null para limpar uma célula.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_used_range_metadata">
+    **Descrição:** Retornar apenas os metadados (endereço e dimensões) do intervalo utilizado em uma planilha, sem os valores reais das células. Ideal para arquivos grandes para entender o tamanho da planilha antes de ler dados em blocos.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha (aba) para leitura. Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_used_range">
+    **Descrição:** Recuperar todas as células contendo dados em uma planilha armazenada no SharePoint. Não use para arquivos maiores que 2MB. Para arquivos grandes, use get_excel_used_range_metadata primeiro, depois get_excel_range_data para ler em blocos menores.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha (aba) para leitura. Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
+    - `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'address,values,formulas,numberFormat,text,rowCount,columnCount').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_cell">
+    **Descrição:** Recuperar o valor de uma única célula por índice de linha e coluna de um arquivo Excel no SharePoint. Os índices são baseados em 0 (linha 0 = linha 1 do Excel, coluna 0 = coluna A).
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha (aba). Obtenha de get_excel_worksheets. Sensível a maiúsculas e minúsculas.
+    - `row` (integer, obrigatório): Índice de linha baseado em 0 (linha 0 = linha 1 do Excel). Intervalo válido: 0-1048575
+    - `column` (integer, obrigatório): Índice de coluna baseado em 0 (coluna 0 = A, coluna 1 = B). Intervalo válido: 0-16383
+    - `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'address,values,formulas,numberFormat,text').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/add_excel_table">
+    **Descrição:** Converter um intervalo de células em uma tabela Excel formatada com recursos de filtragem, classificação e dados estruturados. Tabelas habilitam add_excel_table_row para adicionar dados.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha contendo o intervalo de dados. Obtenha de get_excel_worksheets.
+    - `range` (string, obrigatório): Intervalo de células para converter em tabela, incluindo cabeçalhos e dados (ex: 'A1:D10' onde A1:D1 contém cabeçalhos de coluna).
+    - `has_headers` (boolean, opcional): Defina como true se a primeira linha contém cabeçalhos de coluna. Padrão: true
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_tables">
+    **Descrição:** Listar todas as tabelas em uma planilha Excel específica armazenada no SharePoint. Retorna propriedades da tabela incluindo id, name, showHeaders e showTotals.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha para obter tabelas. Obtenha de get_excel_worksheets.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/add_excel_table_row">
+    **Descrição:** Adicionar uma nova linha ao final de uma tabela Excel em um arquivo do SharePoint. O array de valores deve ter o mesmo número de elementos que o número de colunas da tabela.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha contendo a tabela. Obtenha de get_excel_worksheets.
+    - `table_name` (string, obrigatório): Nome da tabela para adicionar a linha (ex: 'Table1'). Obtenha de get_excel_tables. Sensível a maiúsculas e minúsculas.
+    - `values` (array, obrigatório): Array de valores de células para a nova linha, um por coluna na ordem da tabela (ex: ["João Silva", "joao@exemplo.com", 25]).
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_excel_table_data">
+    **Descrição:** Obter todas as linhas de uma tabela Excel em um arquivo do SharePoint como um intervalo de dados. Mais fácil do que get_excel_range_data ao trabalhar com tabelas estruturadas, pois não é necessário saber o intervalo exato.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha contendo a tabela. Obtenha de get_excel_worksheets.
+    - `table_name` (string, obrigatório): Nome da tabela para obter dados (ex: 'Table1'). Obtenha de get_excel_tables. Sensível a maiúsculas e minúsculas.
+    - `select` (string, opcional): Lista de propriedades separadas por vírgula para retornar (ex: 'address,values,formulas,numberFormat,text').
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/create_excel_chart">
+    **Descrição:** Criar uma visualização de gráfico em uma planilha Excel armazenada no SharePoint a partir de um intervalo de dados. O gráfico é incorporado na planilha.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha onde o gráfico será criado. Obtenha de get_excel_worksheets.
+    - `chart_type` (string, obrigatório): Tipo de gráfico (ex: 'ColumnClustered', 'ColumnStacked', 'Line', 'LineMarkers', 'Pie', 'Bar', 'BarClustered', 'Area', 'Scatter', 'Doughnut').
+    - `source_data` (string, obrigatório): Intervalo de dados para o gráfico em notação A1, incluindo cabeçalhos (ex: 'A1:B10').
+    - `series_by` (string, opcional): Como as séries de dados são organizadas: 'Auto', 'Columns' ou 'Rows'. Padrão: 'Auto'
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_excel_charts">
+    **Descrição:** Listar todos os gráficos incorporados em uma planilha Excel armazenada no SharePoint. Retorna propriedades do gráfico incluindo id, name, chartType, height, width e position.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha para listar gráficos. Obtenha de get_excel_worksheets.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/delete_excel_worksheet">
+    **Descrição:** Remover permanentemente uma planilha (aba) e todo seu conteúdo de uma pasta de trabalho Excel armazenada no SharePoint. Não pode ser desfeito. Uma pasta de trabalho deve ter pelo menos uma planilha.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha a excluir. Sensível a maiúsculas e minúsculas. Todos os dados, tabelas e gráficos nesta planilha serão permanentemente removidos.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/delete_excel_table">
+    **Descrição:** Remover uma tabela de uma planilha Excel no SharePoint. Isto exclui a estrutura da tabela (filtragem, formatação, recursos de tabela) mas preserva os dados subjacentes das células.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+    - `worksheet_name` (string, obrigatório): Nome da planilha contendo a tabela. Obtenha de get_excel_worksheets.
+    - `table_name` (string, obrigatório): Nome da tabela a excluir (ex: 'Table1'). Obtenha de get_excel_tables. Os dados nas células permanecerão após a exclusão da tabela.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/list_excel_names">
+    **Descrição:** Recuperar todos os intervalos nomeados definidos em uma pasta de trabalho Excel armazenada no SharePoint. Intervalos nomeados são rótulos definidos pelo usuário para intervalos de células (ex: 'DadosVendas' para A1:D100).
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do arquivo Excel no SharePoint. Obtenha de list_files ou search_files.
+
+  </Accordion>
+
+  <Accordion title="microsoft_sharepoint/get_word_document_content">
+    **Descrição:** Baixar e extrair conteúdo de texto de um documento Word (.docx) armazenado em uma biblioteca de documentos do SharePoint. Esta é a maneira recomendada de ler documentos Word do SharePoint.
+
+    **Parâmetros:**
+    - `site_id` (string, obrigatório): O identificador completo do site SharePoint obtido de get_sites.
+    - `drive_id` (string, obrigatório): O ID da biblioteca de documentos. Chame get_drives primeiro para obter IDs de drive válidos.
+    - `item_id` (string, obrigatório): O identificador único do documento Word (.docx) no SharePoint. Obtenha de list_files ou search_files.
 
   </Accordion>
 </AccordionGroup>

docs/pt-BR/enterprise/integrations/microsoft_teams.mdx

@@ -107,6 +107,86 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
     - `join_web_url` (string, obrigatório): A URL de participação na web da reunião a pesquisar.
 
   </Accordion>
+
+  <Accordion title="microsoft_teams/search_online_meetings_by_meeting_id">
+    **Descrição:** Pesquisar reuniões online por ID externo da reunião.
+
+    **Parâmetros:**
+    - `join_meeting_id` (string, obrigatório): O ID da reunião (código numérico) que os participantes usam para entrar. É o joinMeetingId exibido nos convites da reunião, não o meeting id da API Graph.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_meeting">
+    **Descrição:** Obter detalhes de uma reunião online específica.
+
+    **Parâmetros:**
+    - `meeting_id` (string, obrigatório): O ID da reunião na API Graph (string alfanumérica longa). Obter pelas ações create_meeting ou search_online_meetings. Diferente do joinMeetingId numérico.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_team_members">
+    **Descrição:** Obter membros de uma equipe específica.
+
+    **Parâmetros:**
+    - `team_id` (string, obrigatório): O identificador único da equipe. Obter pela ação get_teams.
+    - `top` (integer, opcional): Número máximo de membros a recuperar por página (1-999). Padrão: 100.
+    - `skip_token` (string, opcional): Token de paginação de uma resposta anterior. Quando a resposta incluir @odata.nextLink, extraia o valor do parâmetro $skiptoken e passe aqui para obter a próxima página de resultados.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/create_channel">
+    **Descrição:** Criar um novo canal em uma equipe.
+
+    **Parâmetros:**
+    - `team_id` (string, obrigatório): O identificador único da equipe. Obter pela ação get_teams.
+    - `display_name` (string, obrigatório): Nome do canal exibido no Teams. Deve ser único na equipe. Máx 50 caracteres.
+    - `description` (string, opcional): Descrição opcional explicando o propósito do canal. Visível nos detalhes do canal. Máx 1024 caracteres.
+    - `membership_type` (string, opcional): Visibilidade do canal. Opções: standard, private. "standard" = visível para todos os membros da equipe, "private" = visível apenas para membros adicionados especificamente. Padrão: standard.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/get_message_replies">
+    **Descrição:** Obter respostas a uma mensagem específica em um canal.
+
+    **Parâmetros:**
+    - `team_id` (string, obrigatório): O identificador único da equipe. Obter pela ação get_teams.
+    - `channel_id` (string, obrigatório): O identificador único do canal. Obter pela ação get_channels.
+    - `message_id` (string, obrigatório): O identificador único da mensagem pai. Obter pela ação get_messages.
+    - `top` (integer, opcional): Número máximo de respostas a recuperar por página (1-50). Padrão: 50.
+    - `skip_token` (string, opcional): Token de paginação de uma resposta anterior. Quando a resposta incluir @odata.nextLink, extraia o valor do parâmetro $skiptoken e passe aqui para obter a próxima página de resultados.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/reply_to_message">
+    **Descrição:** Responder a uma mensagem em um canal do Teams.
+
+    **Parâmetros:**
+    - `team_id` (string, obrigatório): O identificador único da equipe. Obter pela ação get_teams.
+    - `channel_id` (string, obrigatório): O identificador único do canal. Obter pela ação get_channels.
+    - `message_id` (string, obrigatório): O identificador único da mensagem a responder. Obter pela ação get_messages.
+    - `message` (string, obrigatório): O conteúdo da resposta. Para HTML, inclua tags de formatação. Para texto, use apenas texto simples.
+    - `content_type` (string, opcional): Formato do conteúdo. Opções: html, text. "text" para texto simples, "html" para texto rico com formatação. Padrão: text.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/update_meeting">
+    **Descrição:** Atualizar uma reunião online existente.
+
+    **Parâmetros:**
+    - `meeting_id` (string, obrigatório): O identificador único da reunião. Obter pelas ações create_meeting ou search_online_meetings.
+    - `subject` (string, opcional): Novo título da reunião.
+    - `startDateTime` (string, opcional): Nova hora de início no formato ISO 8601 com fuso horário. Exemplo: "2024-01-20T10:00:00-08:00".
+    - `endDateTime` (string, opcional): Nova hora de término no formato ISO 8601 com fuso horário.
+
+  </Accordion>
+
+  <Accordion title="microsoft_teams/delete_meeting">
+    **Descrição:** Excluir uma reunião online.
+
+    **Parâmetros:**
+    - `meeting_id` (string, obrigatório): O identificador único da reunião a excluir. Obter pelas ações create_meeting ou search_online_meetings.
+
+  </Accordion>
 </AccordionGroup>
 
 ## Exemplos de Uso

docs/pt-BR/enterprise/integrations/microsoft_word.mdx

@@ -97,6 +97,26 @@ CREWAI_PLATFORM_INTEGRATION_TOKEN=seu_enterprise_token
     - `file_id` (string, obrigatório): O ID do documento a excluir.
 
   </Accordion>
+
+  <Accordion title="microsoft_word/copy_document">
+    **Descrição:** Copiar um documento para um novo local no OneDrive.
+
+    **Parâmetros:**
+    - `file_id` (string, obrigatório): O ID do documento a copiar.
+    - `name` (string, opcional): Novo nome para o documento copiado.
+    - `parent_id` (string, opcional): O ID da pasta de destino (padrão: raiz).
+
+  </Accordion>
+
+  <Accordion title="microsoft_word/move_document">
+    **Descrição:** Mover um documento para um novo local no OneDrive.
+
+    **Parâmetros:**
+    - `file_id` (string, obrigatório): O ID do documento a mover.
+    - `parent_id` (string, obrigatório): O ID da pasta de destino.
+    - `name` (string, opcional): Novo nome para o documento movido.
+
+  </Accordion>
 </AccordionGroup>
 
 ## Exemplos de Uso

docs/pt-BR/learn/human-feedback-in-flows.mdx

@@ -73,6 +73,8 @@ Quando este flow é executado, ele irá:
 | `default_outcome` | `str` | Não | Outcome a usar se nenhum feedback for fornecido. Deve estar em `emit` |
 | `metadata` | `dict` | Não | Dados adicionais para integrações enterprise |
 | `provider` | `HumanFeedbackProvider` | Não | Provider customizado para feedback assíncrono/não-bloqueante. Veja [Feedback Humano Assíncrono](#feedback-humano-assíncrono-não-bloqueante) |
+| `learn` | `bool` | Não | Habilitar aprendizado HITL: destila lições do feedback e pré-revisa saídas futuras. Padrão `False`. Veja [Aprendendo com Feedback](#aprendendo-com-feedback) |
+| `learn_limit` | `int` | Não | Máximo de lições passadas para recuperar na pré-revisão. Padrão `5` |
 
 ### Uso Básico (Sem Roteamento)
 
@@ -96,33 +98,43 @@ def handle_feedback(self, result):
 Quando você especifica `emit`, o decorador se torna um roteador. O feedback livre do humano é interpretado por um LLM e mapeado para um dos outcomes especificados:
 
 ```python Code
-@start()
-@human_feedback(
-    message="Você aprova este conteúdo para publicação?",
-    emit=["approved", "rejected", "needs_revision"],
-    llm="gpt-4o-mini",
-    default_outcome="needs_revision",
-)
-def review_content(self):
-    return "Rascunho do post do blog aqui..."
+from crewai.flow.flow import Flow, start, listen, or_
+from crewai.flow.human_feedback import human_feedback
 
-@listen("approved")
-def publish(self, result):
-    print(f"Publicando! Usuário disse: {result.feedback}")
+class ReviewFlow(Flow):
+    @start()
+    def generate_content(self):
+        return "Rascunho do post do blog aqui..."
 
-@listen("rejected")
-def discard(self, result):
-    print(f"Descartando. Motivo: {result.feedback}")
+    @human_feedback(
+        message="Você aprova este conteúdo para publicação?",
+        emit=["approved", "rejected", "needs_revision"],
+        llm="gpt-4o-mini",
+        default_outcome="needs_revision",
+    )
+    @listen(or_("generate_content", "needs_revision"))
+    def review_content(self):
+        return "Rascunho do post do blog aqui..."
 
-@listen("needs_revision")
-def revise(self, result):
-    print(f"Revisando baseado em: {result.feedback}")
+    @listen("approved")
+    def publish(self, result):
+        print(f"Publicando! Usuário disse: {result.feedback}")
+
+    @listen("rejected")
+    def discard(self, result):
+        print(f"Descartando. Motivo: {result.feedback}")
 ```
 
+Quando o humano diz algo como "precisa de mais detalhes", o LLM mapeia para `"needs_revision"`, que dispara `review_content` novamente via `or_()` — criando um loop de revisão. O loop continua até que o outcome seja `"approved"` ou `"rejected"`.
+
 <Tip>
 O LLM usa saídas estruturadas (function calling) quando disponível para garantir que a resposta seja um dos seus outcomes especificados. Isso torna o roteamento confiável e previsível.
 </Tip>
 
+<Warning>
+Um método `@start()` só executa uma vez no início do flow. Se você precisa de um loop de revisão, separe o método start do método de revisão e use `@listen(or_("trigger", "revision_outcome"))` no método de revisão para habilitar o self-loop.
+</Warning>
+
 ## HumanFeedbackResult
 
 O dataclass `HumanFeedbackResult` contém todas as informações sobre uma interação de feedback humano:
@@ -191,116 +203,162 @@ Aqui está um exemplo completo implementando um fluxo de revisão e aprovação
 <CodeGroup>
 
 ```python Code
-from crewai.flow.flow import Flow, start, listen
+from crewai.flow.flow import Flow, start, listen, or_
 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
+    status: str = "pending"
 
 
 class ContentApprovalFlow(Flow[ContentState]):
-    """Um flow que gera conteúdo e obtém aprovação humana."""
+    """Um flow que gera conteúdo e faz loop até o humano aprovar."""
 
     @start()
-    def get_topic(self):
-        self.state.topic = input("Sobre qual tópico devo escrever? ")
-        return self.state.topic
-
-    @listen(get_topic)
-    def generate_draft(self, topic):
-        # Em uso real, isso chamaria um LLM
-        self.state.draft = f"# {topic}\n\nEste é um rascunho sobre {topic}..."
+    def generate_draft(self):
+        self.state.draft = "# IA Segura\n\nEste é um rascunho sobre IA Segura..."
         return self.state.draft
 
-    @listen(generate_draft)
     @human_feedback(
-        message="Por favor, revise este rascunho. Responda 'approved', 'rejected', ou forneça feedback de revisão:",
+        message="Por favor, revise este rascunho. Aprove, rejeite ou descreva o que precisa mudar:",
         emit=["approved", "rejected", "needs_revision"],
         llm="gpt-4o-mini",
         default_outcome="needs_revision",
     )
-    def review_draft(self, draft):
-        return draft
+    @listen(or_("generate_draft", "needs_revision"))
+    def review_draft(self):
+        self.state.revision_count += 1
+        return f"{self.state.draft} (v{self.state.revision_count})"
 
     @listen("approved")
     def publish_content(self, result: HumanFeedbackResult):
-        self.state.final_content = result.output
-        print("\n✅ Conteúdo aprovado e publicado!")
-        print(f"Comentário do revisor: {result.feedback}")
+        self.state.status = "published"
+        print(f"Conteúdo aprovado e publicado! Revisor disse: {result.feedback}")
         return "published"
 
     @listen("rejected")
     def handle_rejection(self, result: HumanFeedbackResult):
-        print("\n❌ Conteúdo rejeitado")
-        print(f"Motivo: {result.feedback}")
+        self.state.status = "rejected"
+        print(f"Conteúdo rejeitado. Motivo: {result.feedback}")
         return "rejected"
 
-    @listen("needs_revision")
-    def revise_content(self, result: HumanFeedbackResult):
-        self.state.revision_count += 1
-        print(f"\n📝 Revisão #{self.state.revision_count} solicitada")
-        print(f"Feedback: {result.feedback}")
 
-        # Em um flow real, você pode voltar para generate_draft
-        # Para este exemplo, apenas reconhecemos
-        return "revision_requested"
-
-
-# Executar o flow
 flow = ContentApprovalFlow()
 result = flow.kickoff()
-print(f"\nFlow concluído. Revisões solicitadas: {flow.state.revision_count}")
+print(f"\nFlow finalizado. Status: {flow.state.status}, Revisões: {flow.state.revision_count}")
 ```
 
 ```text Output
-Sobre qual tópico devo escrever? Segurança em IA
+==================================================
+OUTPUT FOR REVIEW:
+==================================================
+# IA Segura
+
+Este é um rascunho sobre IA Segura... (v1)
+==================================================
+
+Por favor, revise este rascunho. Aprove, rejeite ou descreva o que precisa mudar:
+(Press Enter to skip, or type your feedback)
+
+Your feedback: Preciso de mais detalhes sobre segurança em IA.
 
 ==================================================
 OUTPUT FOR REVIEW:
 ==================================================
-# Segurança em IA
+# IA Segura
 
-Este é um rascunho sobre Segurança em IA...
+Este é um rascunho sobre IA Segura... (v2)
 ==================================================
 
-Por favor, revise este rascunho. Responda 'approved', 'rejected', ou forneça feedback de revisão:
+Por favor, revise este rascunho. Aprove, rejeite ou descreva o que precisa mudar:
 (Press Enter to skip, or type your feedback)
 
 Your feedback: Parece bom, aprovado!
 
-✅ Conteúdo aprovado e publicado!
-Comentário do revisor: Parece bom, aprovado!
+Conteúdo aprovado e publicado! Revisor disse: Parece bom, aprovado!
 
-Flow concluído. Revisões solicitadas: 0
+Flow finalizado. Status: published, Revisões: 2
 ```
 
 </CodeGroup>
 
 ## Combinando com Outros Decoradores
 
-O decorador `@human_feedback` funciona com outros decoradores de flow. Coloque-o como o decorador mais interno (mais próximo da função):
+O decorador `@human_feedback` funciona com `@start()`, `@listen()` e `or_()`. Ambas as ordens de decoradores funcionam — o framework propaga atributos em ambas as direções — mas os padrões recomendados são:
 
 ```python Code
-# Correto: @human_feedback é o mais interno (mais próximo da função)
+# Revisão única no início do flow (sem self-loop)
 @start()
-@human_feedback(message="Revise isto:")
+@human_feedback(message="Revise isto:", emit=["approved", "rejected"], llm="gpt-4o-mini")
 def my_start_method(self):
     return "content"
 
+# Revisão linear em um listener (sem self-loop)
 @listen(other_method)
-@human_feedback(message="Revise isto também:")
+@human_feedback(message="Revise isto também:", emit=["good", "bad"], llm="gpt-4o-mini")
 def my_listener(self, data):
     return f"processed: {data}"
+
+# Self-loop: revisão que pode voltar para revisões
+@human_feedback(message="Aprovar ou revisar?", emit=["approved", "revise"], llm="gpt-4o-mini")
+@listen(or_("upstream_method", "revise"))
+def review_with_loop(self):
+    return "content for review"
 ```
 
-<Tip>
-Coloque `@human_feedback` como o decorador mais interno (último/mais próximo da função) para que ele envolva o método diretamente e possa capturar o valor de retorno antes de passar para o sistema de flow.
-</Tip>
+### Padrão de self-loop
+
+Para criar um loop de revisão, o método de revisão deve escutar **ambos** um gatilho upstream e seu próprio outcome de revisão usando `or_()`:
+
+```python Code
+@start()
+def generate(self):
+    return "initial draft"
+
+@human_feedback(
+    message="Aprovar ou solicitar alterações?",
+    emit=["revise", "approved"],
+    llm="gpt-4o-mini",
+    default_outcome="approved",
+)
+@listen(or_("generate", "revise"))
+def review(self):
+    return "content"
+
+@listen("approved")
+def publish(self):
+    return "published"
+```
+
+Quando o outcome é `"revise"`, o flow roteia de volta para `review` (porque ele escuta `"revise"` via `or_()`). Quando o outcome é `"approved"`, o flow continua para `publish`. Isso funciona porque o engine de flow isenta roteadores da regra "fire once", permitindo que eles re-executem em cada iteração do loop.
+
+### Roteadores encadeados
+
+Um listener disparado pelo outcome de um roteador pode ser ele mesmo um roteador:
+
+```python Code
+@start()
+@human_feedback(message="Primeira revisão:", emit=["approved", "rejected"], llm="gpt-4o-mini")
+def draft(self):
+    return "draft content"
+
+@listen("approved")
+@human_feedback(message="Revisão final:", emit=["publish", "revise"], llm="gpt-4o-mini")
+def final_review(self, prev):
+    return "final content"
+
+@listen("publish")
+def on_publish(self, prev):
+    return "published"
+```
+
+### Limitações
+
+- **Métodos `@start()` executam uma vez**: Um método `@start()` não pode fazer self-loop. Se você precisa de um ciclo de revisão, use um método `@start()` separado como ponto de entrada e coloque o `@human_feedback` em um método `@listen()`.
+- **Sem `@start()` + `@listen()` no mesmo método**: Esta é uma restrição do framework de Flow. Um método é ou um ponto de início ou um listener, não ambos.
 
 ## Melhores Práticas
 
@@ -514,9 +572,9 @@ class ContentPipeline(Flow):
     @start()
     @human_feedback(
         message="Aprova este conteúdo para publicação?",
-        emit=["approved", "rejected", "needs_revision"],
+        emit=["approved", "rejected"],
         llm="gpt-4o-mini",
-        default_outcome="needs_revision",
+        default_outcome="rejected",
         provider=SlackNotificationProvider("#content-reviews"),
     )
     def generate_content(self):
@@ -532,11 +590,6 @@ class ContentPipeline(Flow):
         print(f"Arquivado. Motivo: {result.feedback}")
         return {"status": "archived"}
 
-    @listen("needs_revision")
-    def queue_revision(self, result):
-        print(f"Na fila para revisão: {result.feedback}")
-        return {"status": "revision_needed"}
-
 
 # Iniciando o flow (vai pausar e aguardar resposta do Slack)
 def start_content_pipeline():
@@ -576,6 +629,64 @@ Se você está usando um framework web assíncrono (FastAPI, aiohttp, Slack Bolt
 5. **Persistência automática**: O estado é automaticamente salvo quando `HumanFeedbackPending` é lançado e usa `SQLiteFlowPersistence` por padrão
 6. **Persistência customizada**: Passe uma instância de persistência customizada para `from_pending()` se necessário
 
+## Aprendendo com Feedback
+
+O parâmetro `learn=True` habilita um ciclo de feedback entre revisores humanos e o sistema de memória. Quando habilitado, o sistema melhora progressivamente suas saídas aprendendo com correções humanas anteriores.
+
+### Como Funciona
+
+1. **Após o feedback**: O LLM extrai lições generalizáveis da saída + feedback e as armazena na memória com `source="hitl"`. Se o feedback for apenas aprovação (ex: "parece bom"), nada é armazenado.
+2. **Antes da próxima revisão**: Lições HITL passadas são recuperadas da memória e aplicadas pelo LLM para melhorar a saída antes que o humano a veja.
+
+Com o tempo, o humano vê saídas pré-revisadas progressivamente melhores porque cada correção informa revisões futuras.
+
+### Exemplo
+
+```python Code
+class ArticleReviewFlow(Flow):
+    @start()
+    def generate_article(self):
+        return self.crew.kickoff(inputs={"topic": "AI Safety"}).raw
+
+    @human_feedback(
+        message="Revise este rascunho do artigo:",
+        emit=["approved", "needs_revision"],
+        llm="gpt-4o-mini",
+        learn=True,  # enable HITL learning
+    )
+    @listen(or_("generate_article", "needs_revision"))
+    def review_article(self):
+        return self.last_human_feedback.output if self.last_human_feedback else "article draft"
+
+    @listen("approved")
+    def publish(self):
+        print(f"Publishing: {self.last_human_feedback.output}")
+```
+
+**Primeira execução**: O humano vê a saída bruta e diz "Sempre inclua citações para afirmações factuais." A lição é destilada e armazenada na memória.
+
+**Segunda execução**: O sistema recupera a lição sobre citações, pré-revisa a saída para adicionar citações e então mostra a versão melhorada. O trabalho do humano muda de "corrigir tudo" para "identificar o que o sistema deixou passar."
+
+### Configuração
+
+| Parâmetro | Padrão | Descrição |
+|-----------|--------|-----------|
+| `learn` | `False` | Habilitar aprendizado HITL |
+| `learn_limit` | `5` | Máximo de lições passadas para recuperar na pré-revisão |
+
+### Decisões de Design Principais
+
+- **Mesmo LLM para tudo**: O parâmetro `llm` no decorador é compartilhado pelo mapeamento de outcome, destilação de lições e pré-revisão. Não é necessário configurar múltiplos modelos.
+- **Saída estruturada**: Tanto a destilação quanto a pré-revisão usam function calling com modelos Pydantic quando o LLM suporta, com fallback para parsing de texto caso contrário.
+- **Armazenamento não-bloqueante**: Lições são armazenadas via `remember_many()` que executa em uma thread em segundo plano -- o flow continua imediatamente.
+- **Degradação graciosa**: Se o LLM falhar durante a destilação, nada é armazenado. Se falhar durante a pré-revisão, a saída bruta é mostrada. Nenhuma falha bloqueia o flow.
+- **Sem escopo/categorias necessários**: Ao armazenar lições, apenas `source` é passado. O pipeline de codificação infere escopo, categorias e importância automaticamente.
+
+<Note>
+`learn=True` requer que o Flow tenha memória disponível. Flows obtêm memória automaticamente por padrão, mas se você a desabilitou com `_skip_auto_memory`, o aprendizado HITL será silenciosamente ignorado.
+</Note>
+
+
 ## Documentação Relacionada
 
 - [Visão Geral de Flows](/pt-BR/concepts/flows) - Aprenda sobre CrewAI Flows
@@ -583,3 +694,4 @@ Se você está usando um framework web assíncrono (FastAPI, aiohttp, Slack Bolt
 - [Persistência de Flows](/pt-BR/concepts/flows#persistence) - Persistindo estado de flows
 - [Roteamento com @router](/pt-BR/concepts/flows#router) - Mais sobre roteamento condicional
 - [Input Humano na Execução](/pt-BR/learn/human-input-on-execution) - Input humano no nível de task
+- [Memória](/pt-BR/concepts/memory) - O sistema unificado de memória usado pelo aprendizado HITL

lib/crewai-tools/src/crewai_tools/tools/nl2sql/README.md

@@ -8,6 +8,29 @@ This enables multiple workflows like having an Agent to access the database fetc
 
 **Attention**: Make sure that the Agent has access to a Read-Replica or that is okay for the Agent to run insert/update queries on the database.
 
+## Security Model
+
+`NL2SQLTool` is an execution-capable tool. It runs model-generated SQL directly against the configured database connection.
+
+Risk depends on deployment choices:
+
+- Which credentials are used in `db_uri`
+- Whether untrusted input can influence prompts
+- Whether tool-call guardrails are enforced before execution
+
+If untrusted input can reach this tool, treat the integration as high risk.
+
+## Hardening Recommendations
+
+Use all of the following in production:
+
+- Use a read-only database user whenever possible
+- Prefer a read replica for analytics/retrieval workloads
+- Grant least privilege (no superuser/admin roles, no file/system-level capabilities)
+- Apply database-side resource limits (statement timeout, lock timeout, cost/row limits)
+- Add `before_tool_call` hooks to enforce allowed query patterns
+- Enable query logging and alerting for destructive statements
+
 ## Requirements
 
 - SqlAlchemy

lib/crewai-tools/tests/tools/brave_search_tool_test.py

@@ -33,8 +33,11 @@ def test_brave_tool_search(mock_get, brave_tool):
     mock_get.return_value.json.return_value = mock_response
 
     result = brave_tool.run(query="test")
-    assert "Test Title" in result
-    assert "http://test.com" in result
+    data = json.loads(result)
+    assert isinstance(data, list)
+    assert len(data) >= 1
+    assert data[0]["title"] == "Test Title"
+    assert data[0]["url"] == "http://test.com"
 
 
 @patch("requests.get")

lib/crewai/pyproject.toml

@@ -26,6 +26,8 @@ dependencies = [
     # Authentication and Security
     "python-dotenv~=1.1.1",
     "pyjwt>=2.9.0,<3",
+    # TUI
+    "textual>=7.5.0",
     # Configuration and Utils
     "click~=8.1.7",
     "appdirs~=1.4.4",
@@ -36,9 +38,11 @@ dependencies = [
     "json5~=0.10.0",
     "portalocker~=2.7.0",
     "pydantic-settings~=2.10.1",
+    "httpx~=0.28.1",
     "mcp~=1.26.0",
     "uv~=0.9.13",
     "aiosqlite~=0.21.0",
+    "lancedb>=0.4.0",
 ]
 
 [project.urls]

lib/crewai/src/crewai/__init__.py

@@ -10,6 +10,7 @@ from crewai.flow.flow import Flow
 from crewai.knowledge.knowledge import Knowledge
 from crewai.llm import LLM
 from crewai.llms.base_llm import BaseLLM
+from crewai.memory.unified_memory import Memory
 from crewai.process import Process
 from crewai.task import Task
 from crewai.tasks.llm_guardrail import LLMGuardrail
@@ -80,6 +81,7 @@ __all__ = [
     "Flow",
     "Knowledge",
     "LLMGuardrail",
+    "Memory",
     "Process",
     "Task",
     "TaskOutput",

lib/crewai/src/crewai/agent/core.py

@@ -71,7 +71,6 @@ from crewai.mcp import (
 from crewai.mcp.transports.http import HTTPTransport
 from crewai.mcp.transports.sse import SSETransport
 from crewai.mcp.transports.stdio import StdioTransport
-from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.rag.embeddings.types import EmbedderConfig
 from crewai.security.fingerprint import Fingerprint
 from crewai.tools.agent_tools.agent_tools import AgentTools
@@ -311,19 +310,12 @@ class Agent(BaseAgent):
             raise ValueError(f"Invalid Knowledge Configuration: {e!s}") from e
 
     def _is_any_available_memory(self) -> bool:
-        """Check if any memory is available."""
-        if not self.crew:
-            return False
-
-        memory_attributes = [
-            "memory",
-            "_short_term_memory",
-            "_long_term_memory",
-            "_entity_memory",
-            "_external_memory",
-        ]
-
-        return any(getattr(self.crew, attr) for attr in memory_attributes)
+        """Check if unified memory is available (agent or crew)."""
+        if getattr(self, "memory", None):
+            return True
+        if self.crew and getattr(self.crew, "_memory", None):
+            return True
+        return False
 
     def _supports_native_tool_calling(self, tools: list[BaseTool]) -> bool:
         """Check if the LLM supports native function calling with the given tools.
@@ -387,15 +379,16 @@ class Agent(BaseAgent):
             memory = ""
 
             try:
-                contextual_memory = ContextualMemory(
-                    self.crew._short_term_memory,
-                    self.crew._long_term_memory,
-                    self.crew._entity_memory,
-                    self.crew._external_memory,
-                    agent=self,
-                    task=task,
+                unified_memory = getattr(self, "memory", None) or (
+                    getattr(self.crew, "_memory", None) if self.crew else None
                 )
-                memory = contextual_memory.build_context_for_task(task, context or "")
+                if unified_memory is not None:
+                    query = task.description
+                    matches = unified_memory.recall(query, limit=10)
+                    if matches:
+                        memory = "Relevant memories:\n" + "\n".join(
+                            f"- {m.record.content}" for m in matches
+                        )
                 if memory.strip() != "":
                     task_prompt += self.i18n.slice("memory").format(memory=memory)
 
@@ -624,17 +617,16 @@ class Agent(BaseAgent):
             memory = ""
 
             try:
-                contextual_memory = ContextualMemory(
-                    self.crew._short_term_memory,
-                    self.crew._long_term_memory,
-                    self.crew._entity_memory,
-                    self.crew._external_memory,
-                    agent=self,
-                    task=task,
-                )
-                memory = await contextual_memory.abuild_context_for_task(
-                    task, context or ""
+                unified_memory = getattr(self, "memory", None) or (
+                    getattr(self.crew, "_memory", None) if self.crew else None
                 )
+                if unified_memory is not None:
+                    query = task.description
+                    matches = unified_memory.recall(query, limit=10)
+                    if matches:
+                        memory = "Relevant memories:\n" + "\n".join(
+                            f"- {m.record.content}" for m in matches
+                        )
                 if memory.strip() != "":
                     task_prompt += self.i18n.slice("memory").format(memory=memory)
 
@@ -1712,6 +1704,18 @@ class Agent(BaseAgent):
 
         # Prepare tools
         raw_tools: list[BaseTool] = self.tools or []
+
+        # Inject memory tools for standalone kickoff (crew path handles its own)
+        agent_memory = getattr(self, "memory", None)
+        if agent_memory is not None:
+            from crewai.tools.memory_tools import create_memory_tools
+
+            existing_names = {sanitize_tool_name(t.name) for t in raw_tools}
+            raw_tools.extend(
+                mt for mt in create_memory_tools(agent_memory)
+                if sanitize_tool_name(mt.name) not in existing_names
+            )
+
         parsed_tools = parse_tools(raw_tools)
 
         # Build agent_info for backward-compatible event emission
@@ -1786,6 +1790,49 @@ class Agent(BaseAgent):
         if input_files:
             all_files.update(input_files)
 
+        # Inject memory context for standalone kickoff (recall before execution)
+        if agent_memory is not None:
+            try:
+                crewai_event_bus.emit(
+                    self,
+                    event=MemoryRetrievalStartedEvent(
+                        task_id=None,
+                        source_type="agent_kickoff",
+                        from_agent=self,
+                    ),
+                )
+                start_time = time.time()
+                matches = agent_memory.recall(formatted_messages, limit=10)
+                memory_block = ""
+                if matches:
+                    memory_block = "Relevant memories:\n" + "\n".join(
+                        f"- {m.record.content}" for m in matches
+                    )
+                if memory_block:
+                    formatted_messages += "\n\n" + self.i18n.slice("memory").format(
+                        memory=memory_block
+                    )
+                crewai_event_bus.emit(
+                    self,
+                    event=MemoryRetrievalCompletedEvent(
+                        task_id=None,
+                        memory_content=memory_block,
+                        retrieval_time_ms=(time.time() - start_time) * 1000,
+                        source_type="agent_kickoff",
+                        from_agent=self,
+                    ),
+                )
+            except Exception as e:
+                crewai_event_bus.emit(
+                    self,
+                    event=MemoryRetrievalFailedEvent(
+                        task_id=None,
+                        source_type="agent_kickoff",
+                        from_agent=self,
+                        error=str(e),
+                    ),
+                )
+
         # Build the input dict for the executor
         inputs: dict[str, Any] = {
             "input": formatted_messages,
@@ -1856,6 +1903,9 @@ class Agent(BaseAgent):
                     response_format=response_format,
                 )
 
+            # Save to memory after execution (passive save)
+            self._save_kickoff_to_memory(messages, output.raw)
+
             crewai_event_bus.emit(
                 self,
                 event=LiteAgentExecutionCompletedEvent(
@@ -1876,6 +1926,31 @@ class Agent(BaseAgent):
             )
             raise
 
+    def _save_kickoff_to_memory(
+        self, messages: str | list[LLMMessage], output_text: str
+    ) -> None:
+        """Save kickoff result to memory. No-op if agent has no memory."""
+        agent_memory = getattr(self, "memory", None)
+        if agent_memory is None:
+            return
+        try:
+            if isinstance(messages, str):
+                input_str = messages
+            else:
+                input_str = "\n".join(
+                    str(msg.get("content", "")) for msg in messages if msg.get("content")
+                ) or "User request"
+            raw = (
+                f"Input: {input_str}\n"
+                f"Agent: {self.role}\n"
+                f"Result: {output_text}"
+            )
+            extracted = agent_memory.extract_memories(raw)
+            if extracted:
+                agent_memory.remember_many(extracted)
+        except Exception as e:
+            self._logger.log("error", f"Failed to save kickoff result to memory: {e}")
+
     def _execute_and_build_output(
         self,
         executor: AgentExecutor,
@@ -2158,6 +2233,9 @@ class Agent(BaseAgent):
                     response_format=response_format,
                 )
 
+            # Save to memory after async execution (passive save)
+            self._save_kickoff_to_memory(messages, output.raw)
+
             crewai_event_bus.emit(
                 self,
                 event=LiteAgentExecutionCompletedEvent(

lib/crewai/src/crewai/agents/agent_builder/base_agent.py

@@ -199,6 +199,14 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         default=None,
         description="List of MCP server references. Supports 'https://server.com/path' for external servers and 'crewai-amp:mcp-name' for AMP marketplace. Use '#tool_name' suffix for specific tools.",
     )
+    memory: Any = Field(
+        default=None,
+        description=(
+            "Enable agent memory. Pass True for default Memory(), "
+            "or a Memory/MemoryScope/MemorySlice instance for custom configuration. "
+            "If not set, falls back to crew memory."
+        ),
+    )
 
     @model_validator(mode="before")
     @classmethod
@@ -329,6 +337,17 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
             self._token_process = TokenProcess()
         return self
 
+    @model_validator(mode="after")
+    def resolve_memory(self) -> Self:
+        """Resolve memory field: True creates a default Memory(), instance is used as-is."""
+        if self.memory is True:
+            from crewai.memory.unified_memory import Memory
+
+            self.memory = Memory()
+        elif self.memory is False:
+            self.memory = None
+        return self
+
     @property
     def key(self) -> str:
         source = [

lib/crewai/src/crewai/agents/agent_builder/base_agent_executor_mixin.py

@@ -1,13 +1,8 @@
 from __future__ import annotations
 
-import time
 from typing import TYPE_CHECKING
 
 from crewai.agents.parser import AgentFinish
-from crewai.memory.entity.entity_memory_item import EntityMemoryItem
-from crewai.memory.long_term.long_term_memory_item import LongTermMemoryItem
-from crewai.utilities.converter import ConverterError
-from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
 from crewai.utilities.printer import Printer
 from crewai.utilities.string_utils import sanitize_tool_name
 
@@ -30,110 +25,29 @@ class CrewAgentExecutorMixin:
     _i18n: I18N
     _printer: Printer = Printer()
 
-    def _create_short_term_memory(self, output: AgentFinish) -> None:
-        """Create and save a short-term memory item if conditions are met."""
+    def _save_to_memory(self, output: AgentFinish) -> None:
+        """Save task result to unified memory (memory or crew._memory)."""
+        memory = getattr(self.agent, "memory", None) or (
+            getattr(self.crew, "_memory", None) if self.crew else None
+        )
+        if memory is None or not self.task:
+            return
         if (
-            self.crew
-            and self.agent
-            and self.task
-            and f"Action: {sanitize_tool_name('Delegate work to coworker')}"
-            not in output.text
+            f"Action: {sanitize_tool_name('Delegate work to coworker')}"
+            in output.text
         ):
-            try:
-                if (
-                    hasattr(self.crew, "_short_term_memory")
-                    and self.crew._short_term_memory
-                ):
-                    self.crew._short_term_memory.save(
-                        value=output.text,
-                        metadata={
-                            "observation": self.task.description,
-                        },
-                    )
-            except Exception as e:
-                self.agent._logger.log(
-                    "error", f"Failed to add to short term memory: {e}"
-                )
-
-    def _create_external_memory(self, output: AgentFinish) -> None:
-        """Create and save a external-term memory item if conditions are met."""
-        if (
-            self.crew
-            and self.agent
-            and self.task
-            and hasattr(self.crew, "_external_memory")
-            and self.crew._external_memory
-        ):
-            try:
-                self.crew._external_memory.save(
-                    value=output.text,
-                    metadata={
-                        "description": self.task.description,
-                        "messages": self.messages,
-                    },
-                )
-            except Exception as e:
-                self.agent._logger.log(
-                    "error", f"Failed to add to external memory: {e}"
-                )
-
-    def _create_long_term_memory(self, output: AgentFinish) -> None:
-        """Create and save long-term and entity memory items based on evaluation."""
-        if (
-            self.crew
-            and self.crew._long_term_memory
-            and self.crew._entity_memory
-            and self.task
-            and self.agent
-        ):
-            try:
-                ltm_agent = TaskEvaluator(self.agent)
-                evaluation = ltm_agent.evaluate(self.task, output.text)
-
-                if isinstance(evaluation, ConverterError):
-                    return
-
-                long_term_memory = LongTermMemoryItem(
-                    task=self.task.description,
-                    agent=self.agent.role,
-                    quality=evaluation.quality,
-                    datetime=str(time.time()),
-                    expected_output=self.task.expected_output,
-                    metadata={
-                        "suggestions": evaluation.suggestions,
-                        "quality": evaluation.quality,
-                    },
-                )
-                self.crew._long_term_memory.save(long_term_memory)
-
-                entity_memories = [
-                    EntityMemoryItem(
-                        name=entity.name,
-                        type=entity.type,
-                        description=entity.description,
-                        relationships="\n".join(
-                            [f"- {r}" for r in entity.relationships]
-                        ),
-                    )
-                    for entity in evaluation.entities
-                ]
-                if entity_memories:
-                    self.crew._entity_memory.save(entity_memories)
-            except AttributeError as e:
-                self.agent._logger.log(
-                    "error", f"Missing attributes for long term memory: {e}"
-                )
-            except Exception as e:
-                self.agent._logger.log(
-                    "error", f"Failed to add to long term memory: {e}"
-                )
-        elif (
-            self.crew
-            and self.crew._long_term_memory
-            and self.crew._entity_memory is None
-        ):
-            if self.agent and self.agent.verbose:
-                self._printer.print(
-                    content="Long term memory is enabled, but entity memory is not enabled. Please configure entity memory or set memory=True to automatically enable it.",
-                    color="bold_yellow",
-                )
+            return
+        try:
+            raw = (
+                f"Task: {self.task.description}\n"
+                f"Agent: {self.agent.role}\n"
+                f"Expected result: {self.task.expected_output}\n"
+                f"Result: {output.text}"
+            )
+            extracted = memory.extract_memories(raw)
+            if extracted:
+                memory.remember_many(extracted, agent_role=self.agent.role)
+        except Exception as e:
+            self.agent._logger.log(
+                "error", f"Failed to save to memory: {e}"
+            )

lib/crewai/src/crewai/agents/crew_agent_executor.py

@@ -6,7 +6,10 @@ and memory management.
 
 from __future__ import annotations
 
+import asyncio
 from collections.abc import Callable
+from concurrent.futures import ThreadPoolExecutor, as_completed
+import inspect
 import logging
 from typing import TYPE_CHECKING, Any, Literal, cast
 
@@ -47,6 +50,7 @@ from crewai.utilities.agent_utils import (
     handle_unknown_error,
     has_reached_max_iterations,
     is_context_length_exceeded,
+    parse_tool_call_args,
     process_llm_response,
     track_delegation_if_needed,
 )
@@ -234,9 +238,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         if self.ask_for_human_input:
             formatted_answer = self._handle_human_feedback(formatted_answer)
 
-        self._create_short_term_memory(formatted_answer)
-        self._create_long_term_memory(formatted_answer)
-        self._create_external_memory(formatted_answer)
+        self._save_to_memory(formatted_answer)
         return {"output": formatted_answer.output}
 
     def _inject_multimodal_files(self, inputs: dict[str, Any] | None = None) -> None:
@@ -687,30 +689,142 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         Returns:
             AgentFinish if tool has result_as_answer=True, None otherwise.
         """
-        from datetime import datetime
-        import json
-
-        from crewai.events import crewai_event_bus
-        from crewai.events.types.tool_usage_events import (
-            ToolUsageErrorEvent,
-            ToolUsageFinishedEvent,
-            ToolUsageStartedEvent,
-        )
-
         if not tool_calls:
             return None
 
-        # Only process the FIRST tool call for sequential execution with reflection
-        tool_call = tool_calls[0]
+        parsed_calls = [
+            parsed
+            for tool_call in tool_calls
+            if (parsed := self._parse_native_tool_call(tool_call)) is not None
+        ]
+        if not parsed_calls:
+            return None
 
-        # Extract tool call info - handle OpenAI-style, Anthropic-style, and Gemini-style
+        original_tools_by_name: dict[str, Any] = {}
+        for tool in self.original_tools or []:
+            original_tools_by_name[sanitize_tool_name(tool.name)] = tool
+
+        if len(parsed_calls) > 1:
+            has_result_as_answer_in_batch = any(
+                bool(
+                    original_tools_by_name.get(func_name)
+                    and getattr(
+                        original_tools_by_name.get(func_name), "result_as_answer", False
+                    )
+                )
+                for _, func_name, _ in parsed_calls
+            )
+            has_max_usage_count_in_batch = any(
+                bool(
+                    original_tools_by_name.get(func_name)
+                    and getattr(
+                        original_tools_by_name.get(func_name),
+                        "max_usage_count",
+                        None,
+                    )
+                    is not None
+                )
+                for _, func_name, _ in parsed_calls
+            )
+
+            # Preserve historical sequential behavior for result_as_answer batches.
+            # Also avoid threading around usage counters for max_usage_count tools.
+            if has_result_as_answer_in_batch or has_max_usage_count_in_batch:
+                logger.debug(
+                    "Skipping parallel native execution because batch includes result_as_answer or max_usage_count tool"
+                )
+            else:
+                execution_plan: list[
+                    tuple[str, str, str | dict[str, Any], Any | None]
+                ] = []
+                for call_id, func_name, func_args in parsed_calls:
+                    original_tool = original_tools_by_name.get(func_name)
+                    execution_plan.append(
+                        (call_id, func_name, func_args, original_tool)
+                    )
+
+                self._append_assistant_tool_calls_message(
+                    [
+                        (call_id, func_name, func_args)
+                        for call_id, func_name, func_args, _ in execution_plan
+                    ]
+                )
+
+                max_workers = min(8, len(execution_plan))
+                ordered_results: list[dict[str, Any] | None] = [None] * len(
+                    execution_plan
+                )
+                with ThreadPoolExecutor(max_workers=max_workers) as pool:
+                    futures = {
+                        pool.submit(
+                            self._execute_single_native_tool_call,
+                            call_id=call_id,
+                            func_name=func_name,
+                            func_args=func_args,
+                            available_functions=available_functions,
+                            original_tool=original_tool,
+                            should_execute=True,
+                        ): idx
+                        for idx, (
+                            call_id,
+                            func_name,
+                            func_args,
+                            original_tool,
+                        ) in enumerate(execution_plan)
+                    }
+                    for future in as_completed(futures):
+                        idx = futures[future]
+                        ordered_results[idx] = future.result()
+
+                for execution_result in ordered_results:
+                    if not execution_result:
+                        continue
+                    tool_finish = self._append_tool_result_and_check_finality(
+                        execution_result
+                    )
+                    if tool_finish:
+                        return tool_finish
+
+                reasoning_prompt = self._i18n.slice("post_tool_reasoning")
+                reasoning_message: LLMMessage = {
+                    "role": "user",
+                    "content": reasoning_prompt,
+                }
+                self.messages.append(reasoning_message)
+                return None
+
+        # Sequential behavior: process only first tool call, then force reflection.
+        call_id, func_name, func_args = parsed_calls[0]
+        self._append_assistant_tool_calls_message([(call_id, func_name, func_args)])
+
+        execution_result = self._execute_single_native_tool_call(
+            call_id=call_id,
+            func_name=func_name,
+            func_args=func_args,
+            available_functions=available_functions,
+            original_tool=original_tools_by_name.get(func_name),
+            should_execute=True,
+        )
+        tool_finish = self._append_tool_result_and_check_finality(execution_result)
+        if tool_finish:
+            return tool_finish
+
+        reasoning_prompt = self._i18n.slice("post_tool_reasoning")
+        reasoning_message = {
+            "role": "user",
+            "content": reasoning_prompt,
+        }
+        self.messages.append(reasoning_message)
+        return None
+
+    def _parse_native_tool_call(
+        self, tool_call: Any
+    ) -> tuple[str, str, str | dict[str, Any]] | None:
         if hasattr(tool_call, "function"):
-            # OpenAI-style: has .function.name and .function.arguments
             call_id = getattr(tool_call, "id", f"call_{id(tool_call)}")
             func_name = sanitize_tool_name(tool_call.function.name)
-            func_args = tool_call.function.arguments
-        elif hasattr(tool_call, "function_call") and tool_call.function_call:
-            # Gemini-style: has .function_call.name and .function_call.args
+            return call_id, func_name, tool_call.function.arguments
+        if hasattr(tool_call, "function_call") and tool_call.function_call:
             call_id = f"call_{id(tool_call)}"
             func_name = sanitize_tool_name(tool_call.function_call.name)
             func_args = (
@@ -718,13 +832,12 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                 if tool_call.function_call.args
                 else {}
             )
-        elif hasattr(tool_call, "name") and hasattr(tool_call, "input"):
-            # Anthropic format: has .name and .input (ToolUseBlock)
+            return call_id, func_name, func_args
+        if hasattr(tool_call, "name") and hasattr(tool_call, "input"):
             call_id = getattr(tool_call, "id", f"call_{id(tool_call)}")
             func_name = sanitize_tool_name(tool_call.name)
-            func_args = tool_call.input  # Already a dict in Anthropic
-        elif isinstance(tool_call, dict):
-            # Support OpenAI "id", Bedrock "toolUseId", or generate one
+            return call_id, func_name, tool_call.input
+        if isinstance(tool_call, dict):
             call_id = (
                 tool_call.get("id")
                 or tool_call.get("toolUseId")
@@ -735,10 +848,15 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                 func_info.get("name", "") or tool_call.get("name", "")
             )
             func_args = func_info.get("arguments", "{}") or tool_call.get("input", {})
-        else:
-            return None
+            return call_id, func_name, func_args
+        return None
+
+    def _append_assistant_tool_calls_message(
+        self,
+        parsed_calls: list[tuple[str, str, str | dict[str, Any]]],
+    ) -> None:
+        import json
 
-        # Append assistant message with single tool call
         assistant_message: LLMMessage = {
             "role": "assistant",
             "content": None,
@@ -753,42 +871,54 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                         else json.dumps(func_args),
                     },
                 }
+                for call_id, func_name, func_args in parsed_calls
             ],
         }
-
         self.messages.append(assistant_message)
 
-        # Parse arguments for the single tool call
-        if isinstance(func_args, str):
-            try:
-                args_dict = json.loads(func_args)
-            except json.JSONDecodeError:
-                args_dict = {}
-        else:
-            args_dict = func_args
+    def _execute_single_native_tool_call(
+        self,
+        *,
+        call_id: str,
+        func_name: str,
+        func_args: str | dict[str, Any],
+        available_functions: dict[str, Callable[..., Any]],
+        original_tool: Any | None = None,
+        should_execute: bool = True,
+    ) -> dict[str, Any]:
+        from datetime import datetime
+        import json
 
-        agent_key = getattr(self.agent, "key", "unknown") if self.agent else "unknown"
+        from crewai.events.types.tool_usage_events import (
+            ToolUsageErrorEvent,
+            ToolUsageFinishedEvent,
+            ToolUsageStartedEvent,
+        )
 
-        # Find original tool by matching sanitized name (needed for cache_function and result_as_answer)
+        args_dict, parse_error = parse_tool_call_args(func_args, func_name, call_id, original_tool)
+        if parse_error is not None:
+            return parse_error
 
-        original_tool = None
-        for tool in self.original_tools or []:
-            if sanitize_tool_name(tool.name) == func_name:
-                original_tool = tool
-                break
+        if original_tool is None:
+            for tool in self.original_tools or []:
+                if sanitize_tool_name(tool.name) == func_name:
+                    original_tool = tool
+                    break
 
-        # Check if tool has reached max usage count
         max_usage_reached = False
-        if original_tool:
-            if (
-                hasattr(original_tool, "max_usage_count")
-                and original_tool.max_usage_count is not None
-                and original_tool.current_usage_count >= original_tool.max_usage_count
-            ):
-                max_usage_reached = True
+        if not should_execute and original_tool:
+            max_usage_reached = True
+        elif (
+            should_execute
+            and original_tool
+            and (max_count := getattr(original_tool, "max_usage_count", None))
+            is not None
+            and getattr(original_tool, "current_usage_count", 0) >= max_count
+        ):
+            max_usage_reached = True
 
-        # Check cache before executing
         from_cache = False
+        result: str = "Tool not found"
         input_str = json.dumps(args_dict) if args_dict else ""
         if self.tools_handler and self.tools_handler.cache:
             cached_result = self.tools_handler.cache.read(
@@ -802,7 +932,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                 )
                 from_cache = True
 
-        # Emit tool usage started event
+        agent_key = getattr(self.agent, "key", "unknown") if self.agent else "unknown"
         started_at = datetime.now()
         crewai_event_bus.emit(
             self,
@@ -818,14 +948,12 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
 
         track_delegation_if_needed(func_name, args_dict, self.task)
 
-        # Find the structured tool for hook context
         structured_tool: CrewStructuredTool | None = None
         for structured in self.tools or []:
             if sanitize_tool_name(structured.name) == func_name:
                 structured_tool = structured
                 break
 
-        # Execute before_tool_call hooks
         hook_blocked = False
         before_hook_context = ToolCallHookContext(
             tool_name=func_name,
@@ -849,58 +977,48 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                     color="red",
                 )
 
-        # If hook blocked execution, set result and skip tool execution
         if hook_blocked:
             result = f"Tool execution blocked by hook. Tool: {func_name}"
-        # Execute the tool (only if not cached, not at max usage, and not blocked by hook)
-        elif not from_cache and not max_usage_reached:
-            result = "Tool not found"
-            if func_name in available_functions:
-                try:
-                    tool_func = available_functions[func_name]
-                    raw_result = tool_func(**args_dict)
-
-                    # Add to cache after successful execution (before string conversion)
-                    if self.tools_handler and self.tools_handler.cache:
-                        should_cache = True
-                        if (
-                            original_tool
-                            and hasattr(original_tool, "cache_function")
-                            and callable(original_tool.cache_function)
-                        ):
-                            should_cache = original_tool.cache_function(
-                                args_dict, raw_result
-                            )
-                        if should_cache:
-                            self.tools_handler.cache.add(
-                                tool=func_name, input=input_str, output=raw_result
-                            )
-
-                    # Convert to string for message
-                    result = (
-                        str(raw_result)
-                        if not isinstance(raw_result, str)
-                        else raw_result
-                    )
-                except Exception as e:
-                    result = f"Error executing tool: {e}"
-                    if self.task:
-                        self.task.increment_tools_errors()
-                    crewai_event_bus.emit(
-                        self,
-                        event=ToolUsageErrorEvent(
-                            tool_name=func_name,
-                            tool_args=args_dict,
-                            from_agent=self.agent,
-                            from_task=self.task,
-                            agent_key=agent_key,
-                            error=e,
-                        ),
-                    )
-                    error_event_emitted = True
         elif max_usage_reached and original_tool:
-            # Return error message when max usage limit is reached
             result = f"Tool '{func_name}' has reached its usage limit of {original_tool.max_usage_count} times and cannot be used anymore."
+        elif not from_cache and func_name in available_functions:
+            try:
+                raw_result = available_functions[func_name](**args_dict)
+
+                if self.tools_handler and self.tools_handler.cache:
+                    should_cache = True
+                    if (
+                        original_tool
+                        and hasattr(original_tool, "cache_function")
+                        and callable(original_tool.cache_function)
+                    ):
+                        should_cache = original_tool.cache_function(
+                            args_dict, raw_result
+                        )
+                    if should_cache:
+                        self.tools_handler.cache.add(
+                            tool=func_name, input=input_str, output=raw_result
+                        )
+
+                result = (
+                    str(raw_result) if not isinstance(raw_result, str) else raw_result
+                )
+            except Exception as e:
+                result = f"Error executing tool: {e}"
+                if self.task:
+                    self.task.increment_tools_errors()
+                crewai_event_bus.emit(
+                    self,
+                    event=ToolUsageErrorEvent(
+                        tool_name=func_name,
+                        tool_args=args_dict,
+                        from_agent=self.agent,
+                        from_task=self.task,
+                        agent_key=agent_key,
+                        error=e,
+                    ),
+                )
+                error_event_emitted = True
 
         after_hook_context = ToolCallHookContext(
             tool_name=func_name,
@@ -940,7 +1058,23 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                 ),
             )
 
-        # Append tool result message
+        return {
+            "call_id": call_id,
+            "func_name": func_name,
+            "result": result,
+            "from_cache": from_cache,
+            "original_tool": original_tool,
+        }
+
+    def _append_tool_result_and_check_finality(
+        self, execution_result: dict[str, Any]
+    ) -> AgentFinish | None:
+        call_id = cast(str, execution_result["call_id"])
+        func_name = cast(str, execution_result["func_name"])
+        result = cast(str, execution_result["result"])
+        from_cache = cast(bool, execution_result["from_cache"])
+        original_tool = execution_result["original_tool"]
+
         tool_message: LLMMessage = {
             "role": "tool",
             "tool_call_id": call_id,
@@ -949,7 +1083,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         }
         self.messages.append(tool_message)
 
-        # Log the tool execution
         if self.agent and self.agent.verbose:
             cache_info = " (from cache)" if from_cache else ""
             self._printer.print(
@@ -962,20 +1095,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             and hasattr(original_tool, "result_as_answer")
             and original_tool.result_as_answer
         ):
-            # Return immediately with tool result as final answer
             return AgentFinish(
                 thought="Tool result is the final answer",
                 output=result,
                 text=result,
             )
-
-        # Inject post-tool reasoning prompt to enforce analysis
-        reasoning_prompt = self._i18n.slice("post_tool_reasoning")
-        reasoning_message: LLMMessage = {
-            "role": "user",
-            "content": reasoning_prompt,
-        }
-        self.messages.append(reasoning_message)
         return None
 
     async def ainvoke(self, inputs: dict[str, Any]) -> dict[str, Any]:
@@ -1011,9 +1135,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         if self.ask_for_human_input:
             formatted_answer = await self._ahandle_human_feedback(formatted_answer)
 
-        self._create_short_term_memory(formatted_answer)
-        self._create_long_term_memory(formatted_answer)
-        self._create_external_memory(formatted_answer)
+        self._save_to_memory(formatted_answer)
         return {"output": formatted_answer.output}
 
     async def _ainvoke_loop(self) -> AgentFinish:
@@ -1375,7 +1497,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             formatted_answer: Current agent response.
         """
         if self.step_callback:
-            self.step_callback(formatted_answer)
+            cb_result = self.step_callback(formatted_answer)
+            if inspect.iscoroutine(cb_result):
+                asyncio.run(cb_result)
 
     def _append_message(
         self, text: str, role: Literal["user", "assistant", "system"] = "assistant"

lib/crewai/src/crewai/cli/authentication/main.py

@@ -2,8 +2,8 @@ import time
 from typing import TYPE_CHECKING, Any, TypeVar, cast
 import webbrowser
 
+import httpx
 from pydantic import BaseModel, Field
-import requests
 from rich.console import Console
 
 from crewai.cli.authentication.utils import validate_jwt_token
@@ -98,7 +98,7 @@ class AuthenticationCommand:
             "scope": " ".join(self.oauth2_provider.get_oauth_scopes()),
             "audience": self.oauth2_provider.get_audience(),
         }
-        response = requests.post(
+        response = httpx.post(
             url=self.oauth2_provider.get_authorize_url(),
             data=device_code_payload,
             timeout=20,
@@ -130,7 +130,7 @@ class AuthenticationCommand:
 
         attempts = 0
         while True and attempts < 10:
-            response = requests.post(
+            response = httpx.post(
                 self.oauth2_provider.get_token_url(), data=token_payload, timeout=30
             )
             token_data = response.json()
@@ -149,7 +149,7 @@ class AuthenticationCommand:
                 return
 
             if token_data["error"] not in ("authorization_pending", "slow_down"):
-                raise requests.HTTPError(
+                raise httpx.HTTPError(
                     token_data.get("error_description") or token_data.get("error")
                 )
 

lib/crewai/src/crewai/cli/cli.py

@@ -1,6 +1,7 @@
 from importlib.metadata import version as get_version
 import os
 import subprocess
+from typing import Any
 
 import click
 
@@ -179,9 +180,19 @@ def log_tasks_outputs() -> None:
 
 
 @crewai.command()
-@click.option("-l", "--long", is_flag=True, help="Reset LONG TERM memory")
-@click.option("-s", "--short", is_flag=True, help="Reset SHORT TERM memory")
-@click.option("-e", "--entities", is_flag=True, help="Reset ENTITIES memory")
+@click.option("-m", "--memory", is_flag=True, help="Reset MEMORY")
+@click.option(
+    "-l", "--long", is_flag=True, hidden=True,
+    help="[Deprecated: use --memory] Reset memory",
+)
+@click.option(
+    "-s", "--short", is_flag=True, hidden=True,
+    help="[Deprecated: use --memory] Reset memory",
+)
+@click.option(
+    "-e", "--entities", is_flag=True, hidden=True,
+    help="[Deprecated: use --memory] Reset memory",
+)
 @click.option("-kn", "--knowledge", is_flag=True, help="Reset KNOWLEDGE storage")
 @click.option(
     "-akn", "--agent-knowledge", is_flag=True, help="Reset AGENT KNOWLEDGE storage"
@@ -191,6 +202,7 @@ def log_tasks_outputs() -> None:
 )
 @click.option("-a", "--all", is_flag=True, help="Reset ALL memories")
 def reset_memories(
+    memory: bool,
     long: bool,
     short: bool,
     entities: bool,
@@ -200,13 +212,22 @@ def reset_memories(
     all: bool,
 ) -> None:
     """
-    Reset the crew memories (long, short, entity, latest_crew_kickoff_ouputs, knowledge, agent_knowledge). This will delete all the data saved.
+    Reset the crew memories (memory, knowledge, agent_knowledge, kickoff_outputs). This will delete all the data saved.
     """
     try:
+        # Treat legacy flags as --memory with a deprecation warning
+        if long or short or entities:
+            legacy_used = [
+                f for f, v in [("--long", long), ("--short", short), ("--entities", entities)] if v
+            ]
+            click.echo(
+                f"Warning: {', '.join(legacy_used)} {'is' if len(legacy_used) == 1 else 'are'} "
+                "deprecated. Use --memory (-m) instead. All memory is now unified."
+            )
+            memory = True
+
         memory_types = [
-            long,
-            short,
-            entities,
+            memory,
             knowledge,
             agent_knowledge,
             kickoff_outputs,
@@ -218,12 +239,73 @@ def reset_memories(
             )
             return
         reset_memories_command(
-            long, short, entities, knowledge, agent_knowledge, kickoff_outputs, all
+            memory, knowledge, agent_knowledge, kickoff_outputs, all
         )
     except Exception as e:
         click.echo(f"An error occurred while resetting memories: {e}", err=True)
 
 
+@crewai.command()
+@click.option(
+    "--storage-path",
+    type=str,
+    default=None,
+    help="Path to LanceDB memory directory. If omitted, uses ./.crewai/memory.",
+)
+@click.option(
+    "--embedder-provider",
+    type=str,
+    default=None,
+    help="Embedder provider for recall queries (e.g. openai, google-vertex, cohere, ollama).",
+)
+@click.option(
+    "--embedder-model",
+    type=str,
+    default=None,
+    help="Embedder model name (e.g. text-embedding-3-small, gemini-embedding-001).",
+)
+@click.option(
+    "--embedder-config",
+    type=str,
+    default=None,
+    help='Full embedder config as JSON (e.g. \'{"provider": "cohere", "config": {"model_name": "embed-v4.0"}}\').',
+)
+def memory(
+    storage_path: str | None,
+    embedder_provider: str | None,
+    embedder_model: str | None,
+    embedder_config: str | None,
+) -> None:
+    """Open the Memory TUI to browse scopes and recall memories."""
+    try:
+        from crewai.cli.memory_tui import MemoryTUI
+    except ImportError as exc:
+        click.echo(
+            "Textual is required for the memory TUI but could not be imported. "
+            "Try reinstalling crewai or: pip install textual"
+        )
+        raise SystemExit(1) from exc
+
+    # Build embedder spec from CLI flags.
+    embedder_spec: dict[str, Any] | None = None
+    if embedder_config:
+        import json as _json
+
+        try:
+            embedder_spec = _json.loads(embedder_config)
+        except _json.JSONDecodeError as exc:
+            click.echo(f"Invalid --embedder-config JSON: {exc}")
+            raise SystemExit(1) from exc
+    elif embedder_provider:
+        cfg: dict[str, str] = {}
+        if embedder_model:
+            cfg["model_name"] = embedder_model
+        embedder_spec = {"provider": embedder_provider, "config": cfg}
+
+    app = MemoryTUI(storage_path=storage_path, embedder_config=embedder_spec)
+    app.run()
+
+
 @crewai.command()
 @click.option(
     "-n",

lib/crewai/src/crewai/cli/command.py

@@ -1,5 +1,6 @@
-import requests
-from requests.exceptions import JSONDecodeError
+import json
+
+import httpx
 from rich.console import Console
 
 from crewai.cli.authentication.token import get_auth_token
@@ -30,16 +31,16 @@ class PlusAPIMixin:
             console.print("Run 'crewai login' to sign up/login.", style="bold green")
             raise SystemExit from None
 
-    def _validate_response(self, response: requests.Response) -> None:
+    def _validate_response(self, response: httpx.Response) -> None:
         """
         Handle and display error messages from API responses.
 
         Args:
-            response (requests.Response): The response from the Plus API
+            response (httpx.Response): The response from the Plus API
         """
         try:
             json_response = response.json()
-        except (JSONDecodeError, ValueError):
+        except (json.JSONDecodeError, ValueError):
             console.print(
                 "Failed to parse response from Enterprise API failed. Details:",
                 style="bold red",
@@ -62,7 +63,7 @@ class PlusAPIMixin:
                     )
             raise SystemExit
 
-        if not response.ok:
+        if not response.is_success:
             console.print(
                 "Request to Enterprise API failed. Details:", style="bold red"
             )

lib/crewai/src/crewai/cli/constants.py

@@ -69,7 +69,7 @@ ENV_VARS: dict[str, list[dict[str, Any]]] = {
         },
         {
             "prompt": "Enter your AWS Region Name (press Enter to skip)",
-            "key_name": "AWS_REGION_NAME",
+            "key_name": "AWS_DEFAULT_REGION",
         },
     ],
     "azure": [

lib/crewai/src/crewai/cli/create_crew.py

@@ -143,6 +143,12 @@ def create_folder_structure(
         (folder_path / "src" / folder_name).mkdir(parents=True)
         (folder_path / "src" / folder_name / "tools").mkdir(parents=True)
         (folder_path / "src" / folder_name / "config").mkdir(parents=True)
+        
+        # Copy AGENTS.md to project root (top-level projects only)
+        package_dir = Path(__file__).parent
+        agents_md_src = package_dir / "templates" / "AGENTS.md"
+        if agents_md_src.exists():
+            shutil.copy2(agents_md_src, folder_path / "AGENTS.md")
 
     return folder_path, folder_name, class_name
 

lib/crewai/src/crewai/cli/create_flow.py

@@ -1,3 +1,4 @@
+import shutil
 from pathlib import Path
 
 import click
@@ -34,6 +35,11 @@ def create_flow(name):
     package_dir = Path(__file__).parent
     templates_dir = package_dir / "templates" / "flow"
 
+    # Copy AGENTS.md to project root
+    agents_md_src = package_dir / "templates" / "AGENTS.md"
+    if agents_md_src.exists():
+        shutil.copy2(agents_md_src, project_root / "AGENTS.md")
+
     # List of template files to copy
     root_template_files = [".gitignore", "pyproject.toml", "README.md"]
     src_template_files = ["__init__.py", "main.py"]

lib/crewai/src/crewai/cli/enterprise/main.py

@@ -1,7 +1,7 @@
+import json
 from typing import Any, cast
 
-import requests
-from requests.exceptions import JSONDecodeError, RequestException
+import httpx
 from rich.console import Console
 
 from crewai.cli.authentication.main import Oauth2Settings, ProviderFactory
@@ -47,12 +47,12 @@ class EnterpriseConfigureCommand(BaseCommand):
                 "User-Agent": f"CrewAI-CLI/{get_crewai_version()}",
                 "X-Crewai-Version": get_crewai_version(),
             }
-            response = requests.get(oauth_endpoint, timeout=30, headers=headers)
+            response = httpx.get(oauth_endpoint, timeout=30, headers=headers)
             response.raise_for_status()
 
             try:
                 oauth_config = response.json()
-            except JSONDecodeError as e:
+            except json.JSONDecodeError as e:
                 raise ValueError(f"Invalid JSON response from {oauth_endpoint}") from e
 
             self._validate_oauth_config(oauth_config)
@@ -62,7 +62,7 @@ class EnterpriseConfigureCommand(BaseCommand):
             )
             return cast(dict[str, Any], oauth_config)
 
-        except RequestException as e:
+        except httpx.HTTPError as e:
             raise ValueError(f"Failed to connect to enterprise URL: {e!s}") from e
         except Exception as e:
             raise ValueError(f"Error fetching OAuth2 configuration: {e!s}") from e

lib/crewai/src/crewai/cli/memory_tui.py

@@ -0,0 +1,398 @@
+"""Textual TUI for browsing and recalling unified memory."""
+
+from __future__ import annotations
+
+import asyncio
+from typing import Any
+
+from textual.app import App, ComposeResult
+from textual.containers import Horizontal, Vertical
+from textual.widgets import Footer, Header, Input, OptionList, Static, Tree
+
+
+# -- CrewAI brand palette --
+_PRIMARY = "#eb6658"  # coral
+_SECONDARY = "#1F7982"  # teal
+_TERTIARY = "#ffffff"  # white
+
+
+def _format_scope_info(info: Any) -> str:
+    """Format ScopeInfo with Rich markup."""
+    return (
+        f"[bold {_PRIMARY}]{info.path}[/]\n\n"
+        f"[dim]Records:[/]     [bold]{info.record_count}[/]\n"
+        f"[dim]Categories:[/]  {', '.join(info.categories) or 'none'}\n"
+        f"[dim]Oldest:[/]      {info.oldest_record or '-'}\n"
+        f"[dim]Newest:[/]      {info.newest_record or '-'}\n"
+        f"[dim]Children:[/]    {', '.join(info.child_scopes) or 'none'}"
+    )
+
+
+class MemoryTUI(App[None]):
+    """TUI to browse memory scopes and run recall queries."""
+
+    TITLE = "CrewAI Memory"
+    SUB_TITLE = "Browse scopes and recall memories"
+
+    CSS = f"""
+    Header {{
+        background: {_PRIMARY};
+        color: {_TERTIARY};
+    }}
+    Footer {{
+        background: {_SECONDARY};
+        color: {_TERTIARY};
+    }}
+    Footer > .footer-key--key {{
+        background: {_PRIMARY};
+        color: {_TERTIARY};
+    }}
+    Horizontal {{
+        height: 1fr;
+    }}
+    #scope-tree {{
+        width: 30%;
+        padding: 1 2;
+        background: {_SECONDARY} 8%;
+        border-right: solid {_SECONDARY};
+    }}
+    #scope-tree:focus > .tree--cursor {{
+        background: {_SECONDARY};
+        color: {_TERTIARY};
+    }}
+    #scope-tree > .tree--guides {{
+        color: {_SECONDARY} 50%;
+    }}
+    #scope-tree > .tree--guides-hover {{
+        color: {_PRIMARY};
+    }}
+    #scope-tree > .tree--guides-selected {{
+        color: {_SECONDARY};
+    }}
+    #right-panel {{
+        width: 70%;
+        padding: 0 1;
+    }}
+    #info-panel {{
+        height: 2fr;
+        padding: 1 2;
+        overflow-y: auto;
+        border: round {_SECONDARY};
+    }}
+    #info-panel:focus {{
+        border: round {_PRIMARY};
+    }}
+    #info-panel LoadingIndicator {{
+        color: {_PRIMARY};
+    }}
+    #entry-list {{
+        height: 1fr;
+        border: round {_SECONDARY};
+        padding: 0 1;
+        scrollbar-color: {_PRIMARY};
+    }}
+    #entry-list:focus {{
+        border: round {_PRIMARY};
+    }}
+    #entry-list > .option-list--option-highlighted {{
+        background: {_SECONDARY};
+        color: {_TERTIARY};
+    }}
+    #recall-input {{
+        margin: 0 1 1 1;
+        border: tall {_SECONDARY};
+    }}
+    #recall-input:focus {{
+        border: tall {_PRIMARY};
+    }}
+    """
+
+    def __init__(
+        self,
+        storage_path: str | None = None,
+        embedder_config: dict[str, Any] | None = None,
+    ) -> None:
+        super().__init__()
+        self._memory: Any = None
+        self._init_error: str | None = None
+        self._selected_scope: str = "/"
+        self._entries: list[Any] = []
+        self._view_mode: str = "list"  # "list" | "recall"
+        self._recall_matches: list[Any] = []
+        self._last_scope_info: Any = None
+        self._custom_embedder = embedder_config is not None
+        try:
+            from crewai.memory.storage.lancedb_storage import LanceDBStorage
+            from crewai.memory.unified_memory import Memory
+
+            storage = LanceDBStorage(path=storage_path) if storage_path else LanceDBStorage()
+            embedder = None
+            if embedder_config is not None:
+                from crewai.rag.embeddings.factory import build_embedder
+
+                embedder = build_embedder(embedder_config)
+            self._memory = Memory(storage=storage, embedder=embedder) if embedder else Memory(storage=storage)
+        except Exception as e:
+            self._init_error = str(e)
+
+    def compose(self) -> ComposeResult:
+        yield Header(show_clock=False)
+        with Horizontal():
+            yield self._build_scope_tree()
+            initial = (
+                self._init_error
+                if self._init_error
+                else "Select a scope or type a recall query."
+            )
+            with Vertical(id="right-panel"):
+                yield Static(initial, id="info-panel")
+                yield OptionList(id="entry-list")
+        yield Input(
+            placeholder="Type a query and press Enter to recall...",
+            id="recall-input",
+        )
+        yield Footer()
+
+    def on_mount(self) -> None:
+        """Set initial border titles on mounted widgets."""
+        self.query_one("#info-panel", Static).border_title = "Detail"
+        self.query_one("#entry-list", OptionList).border_title = "Entries"
+
+    def _build_scope_tree(self) -> Tree[str]:
+        tree: Tree[str] = Tree("/", id="scope-tree")
+        if self._memory is None:
+            tree.root.data = "/"
+            tree.root.label = "/ (0 records)"
+            return tree
+        info = self._memory.info("/")
+        tree.root.label = f"/ ({info.record_count} records)"
+        tree.root.data = "/"
+        self._add_children(tree.root, "/", depth=0, max_depth=3)
+        tree.root.expand()
+        return tree
+
+    def _add_children(
+        self,
+        parent_node: Tree.Node[str],
+        path: str,
+        depth: int,
+        max_depth: int,
+    ) -> None:
+        if depth >= max_depth or self._memory is None:
+            return
+        info = self._memory.info(path)
+        for child in info.child_scopes:
+            child_info = self._memory.info(child)
+            label = f"{child} ({child_info.record_count})"
+            node = parent_node.add(label, data=child)
+            self._add_children(node, child, depth + 1, max_depth)
+
+    # -- Populating the OptionList -------------------------------------------
+
+    def _populate_entry_list(self) -> None:
+        """Clear the OptionList and fill it with the current scope's entries."""
+        option_list = self.query_one("#entry-list", OptionList)
+        option_list.clear_options()
+        for record in self._entries:
+            date_str = record.created_at.strftime("%Y-%m-%d")
+            preview = (
+                (record.content[:80] + "…")
+                if len(record.content) > 80
+                else record.content
+            )
+            label = (
+                f"{date_str}  "
+                f"[bold]{record.importance:.1f}[/]  "
+                f"{preview}"
+            )
+            option_list.add_option(label)
+
+    def _populate_recall_list(self) -> None:
+        """Clear the OptionList and fill it with the current recall matches."""
+        option_list = self.query_one("#entry-list", OptionList)
+        option_list.clear_options()
+        if not self._recall_matches:
+            return
+        for m in self._recall_matches:
+            preview = (
+                (m.record.content[:80] + "…")
+                if len(m.record.content) > 80
+                else m.record.content
+            )
+            label = (
+                f"[bold]\\[{m.score:.2f}][/]  "
+                f"{preview}  "
+                f"[dim]scope={m.record.scope}[/]"
+            )
+            option_list.add_option(label)
+
+    # -- Detail rendering ----------------------------------------------------
+
+    def _format_record_detail(self, record: Any, context_line: str = "") -> str:
+        """Format a full MemoryRecord as Rich markup for the detail view.
+
+        Args:
+            record: A MemoryRecord instance.
+            context_line: Optional header line shown above the fields
+                (e.g. "Entry 3 of 47").
+
+        Returns:
+            A Rich-markup string with all meaningful record fields.
+        """
+        sep = f"[bold {_PRIMARY}]{'─' * 44}[/]"
+        lines: list[str] = []
+
+        if context_line:
+            lines.append(context_line)
+            lines.append("")
+
+        # -- Fields block --
+        lines.append(f"[dim]ID:[/]             {record.id}")
+        lines.append(f"[dim]Scope:[/]          [bold]{record.scope}[/]")
+        lines.append(f"[dim]Importance:[/]      [bold]{record.importance:.2f}[/]")
+        lines.append(
+            f"[dim]Created:[/]        "
+            f"{record.created_at.strftime('%Y-%m-%d %H:%M:%S')}"
+        )
+        lines.append(
+            f"[dim]Last accessed:[/]  "
+            f"{record.last_accessed.strftime('%Y-%m-%d %H:%M:%S')}"
+        )
+        lines.append(
+            f"[dim]Categories:[/]     "
+            f"{', '.join(record.categories) if record.categories else 'none'}"
+        )
+        lines.append(f"[dim]Source:[/]         {record.source or '-'}")
+        lines.append(f"[dim]Private:[/]        {'Yes' if record.private else 'No'}")
+
+        # -- Content block --
+        lines.append(f"\n{sep}")
+        lines.append("[bold]Content[/]\n")
+        lines.append(record.content)
+
+        # -- Metadata block --
+        if record.metadata:
+            lines.append(f"\n{sep}")
+            lines.append("[bold]Metadata[/]\n")
+            for k, v in record.metadata.items():
+                lines.append(f"[dim]{k}:[/] {v}")
+
+        return "\n".join(lines)
+
+    # -- Event handlers ------------------------------------------------------
+
+    def on_tree_node_selected(self, event: Tree.NodeSelected[str]) -> None:
+        """Load entries for the selected scope and populate the OptionList."""
+        path = event.node.data if event.node.data is not None else "/"
+        self._selected_scope = path
+        self._view_mode = "list"
+        panel = self.query_one("#info-panel", Static)
+        if self._memory is None:
+            panel.update(self._init_error or "No memory loaded.")
+            return
+        info = self._memory.info(path)
+        self._last_scope_info = info
+        self._entries = self._memory.list_records(scope=path, limit=200)
+        panel.update(_format_scope_info(info))
+        panel.border_title = "Detail"
+        entry_list = self.query_one("#entry-list", OptionList)
+        entry_list.border_title = f"Entries ({len(self._entries)})"
+        self._populate_entry_list()
+
+    def on_option_list_option_highlighted(
+        self, event: OptionList.OptionHighlighted
+    ) -> None:
+        """Live-update the info panel with the detail of the highlighted entry."""
+        panel = self.query_one("#info-panel", Static)
+        idx = event.option_index
+
+        if self._view_mode == "list":
+            if idx < len(self._entries):
+                record = self._entries[idx]
+                total = len(self._entries)
+                context = (
+                    f"[bold {_PRIMARY}]Entry {idx + 1} of {total}[/]  "
+                    f"[dim]in[/] [bold]{self._selected_scope}[/]"
+                )
+                panel.border_title = f"Entry {idx + 1} of {total}"
+                panel.update(self._format_record_detail(record, context_line=context))
+
+        elif self._view_mode == "recall":
+            if idx < len(self._recall_matches):
+                match = self._recall_matches[idx]
+                total = len(self._recall_matches)
+                panel.border_title = f"Match {idx + 1} of {total}"
+                score_color = _PRIMARY if match.score >= 0.5 else "dim"
+                header_lines: list[str] = [
+                    f"[bold {_PRIMARY}]Recall Match {idx + 1} of {total}[/]\n",
+                    f"[dim]Score:[/]          [{score_color}][bold]{match.score:.2f}[/][/]",
+                    (
+                        f"[dim]Match reasons:[/]  "
+                        f"{', '.join(match.match_reasons) if match.match_reasons else '-'}"
+                    ),
+                    (
+                        f"[dim]Evidence gaps:[/]  "
+                        f"{', '.join(match.evidence_gaps) if match.evidence_gaps else 'none'}"
+                    ),
+                    f"\n[bold {_PRIMARY}]{'─' * 44}[/]",
+                ]
+                record_detail = self._format_record_detail(match.record)
+                header_lines.append(record_detail)
+                panel.update("\n".join(header_lines))
+
+    def on_input_submitted(self, event: Input.Submitted) -> None:
+        query = event.value.strip()
+        if not query:
+            return
+        if self._memory is None:
+            panel = self.query_one("#info-panel", Static)
+            panel.update(self._init_error or "No memory loaded. Cannot recall.")
+            return
+        self.run_worker(self._do_recall(query), exclusive=True)
+
+    async def _do_recall(self, query: str) -> None:
+        """Execute a recall query and display results in the OptionList."""
+        panel = self.query_one("#info-panel", Static)
+        panel.loading = True
+        try:
+            scope = (
+                self._selected_scope
+                if self._selected_scope != "/"
+                else None
+            )
+            loop = asyncio.get_event_loop()
+            matches = await loop.run_in_executor(
+                None,
+                lambda: self._memory.recall(
+                    query, scope=scope, limit=10, depth="deep"
+                ),
+            )
+            self._recall_matches = matches or []
+            self._view_mode = "recall"
+
+            if not self._recall_matches:
+                panel.update("[dim]No memories found.[/]")
+                self.query_one("#entry-list", OptionList).clear_options()
+                return
+
+            info_lines: list[str] = []
+            if not self._custom_embedder:
+                info_lines.append(
+                    "[dim italic]Note: Using default OpenAI embedder. "
+                    "If memories were created with a different embedder, "
+                    "pass --embedder-provider to match.[/]\n"
+                )
+            info_lines.append(
+                f"[bold]Recall Results[/] [dim]"
+                f"({len(self._recall_matches)} matches)[/]\n"
+                f"[dim]Navigate the list below to view details.[/]"
+            )
+            panel.update("\n".join(info_lines))
+            panel.border_title = "Recall Detail"
+            entry_list = self.query_one("#entry-list", OptionList)
+            entry_list.border_title = f"Recall Results ({len(self._recall_matches)})"
+            self._populate_recall_list()
+        except Exception as e:
+            panel.update(f"[bold red]Error:[/] {e}")
+        finally:
+            panel.loading = False

lib/crewai/src/crewai/cli/organization/main.py

@@ -1,4 +1,4 @@
-from requests import HTTPError
+from httpx import HTTPStatusError
 from rich.console import Console
 from rich.table import Table
 
@@ -10,11 +10,11 @@ console = Console()
 
 
 class OrganizationCommand(BaseCommand, PlusAPIMixin):
-    def __init__(self):
+    def __init__(self) -> None:
         BaseCommand.__init__(self)
         PlusAPIMixin.__init__(self, telemetry=self._telemetry)
 
-    def list(self):
+    def list(self) -> None:
         try:
             response = self.plus_api_client.get_organizations()
             response.raise_for_status()
@@ -33,7 +33,7 @@ class OrganizationCommand(BaseCommand, PlusAPIMixin):
                 table.add_row(org["name"], org["uuid"])
 
             console.print(table)
-        except HTTPError as e:
+        except HTTPStatusError as e:
             if e.response.status_code == 401:
                 console.print(
                     "You are not logged in to any organization. Use 'crewai login' to login.",
@@ -50,7 +50,7 @@ class OrganizationCommand(BaseCommand, PlusAPIMixin):
             )
             raise SystemExit(1) from e
 
-    def switch(self, org_id):
+    def switch(self, org_id: str) -> None:
         try:
             response = self.plus_api_client.get_organizations()
             response.raise_for_status()
@@ -72,7 +72,7 @@ class OrganizationCommand(BaseCommand, PlusAPIMixin):
                 f"Successfully switched to {org['name']} ({org['uuid']})",
                 style="bold green",
             )
-        except HTTPError as e:
+        except HTTPStatusError as e:
             if e.response.status_code == 401:
                 console.print(
                     "You are not logged in to any organization. Use 'crewai login' to login.",
@@ -87,7 +87,7 @@ class OrganizationCommand(BaseCommand, PlusAPIMixin):
             console.print(f"Failed to switch organization: {e!s}", style="bold red")
             raise SystemExit(1) from e
 
-    def current(self):
+    def current(self) -> None:
         settings = Settings()
         if settings.org_uuid:
             console.print(

lib/crewai/src/crewai/cli/plus_api.py

@@ -3,7 +3,6 @@ from typing import Any
 from urllib.parse import urljoin
 
 import httpx
-import requests
 
 from crewai.cli.config import Settings
 from crewai.cli.constants import DEFAULT_CREWAI_ENTERPRISE_URL
@@ -43,16 +42,16 @@ class PlusAPI:
 
     def _make_request(
         self, method: str, endpoint: str, **kwargs: Any
-    ) -> requests.Response:
+    ) -> httpx.Response:
         url = urljoin(self.base_url, endpoint)
-        session = requests.Session()
-        session.trust_env = False
-        return session.request(method, url, headers=self.headers, **kwargs)
+        verify = kwargs.pop("verify", True)
+        with httpx.Client(trust_env=False, verify=verify) as client:
+            return client.request(method, url, headers=self.headers, **kwargs)
 
-    def login_to_tool_repository(self) -> requests.Response:
+    def login_to_tool_repository(self) -> httpx.Response:
         return self._make_request("POST", f"{self.TOOLS_RESOURCE}/login")
 
-    def get_tool(self, handle: str) -> requests.Response:
+    def get_tool(self, handle: str) -> httpx.Response:
         return self._make_request("GET", f"{self.TOOLS_RESOURCE}/{handle}")
 
     async def get_agent(self, handle: str) -> httpx.Response:
@@ -68,7 +67,7 @@ class PlusAPI:
         description: str | None,
         encoded_file: str,
         available_exports: list[dict[str, Any]] | None = None,
-    ) -> requests.Response:
+    ) -> httpx.Response:
         params = {
             "handle": handle,
             "public": is_public,
@@ -79,54 +78,52 @@ class PlusAPI:
         }
         return self._make_request("POST", f"{self.TOOLS_RESOURCE}", json=params)
 
-    def deploy_by_name(self, project_name: str) -> requests.Response:
+    def deploy_by_name(self, project_name: str) -> httpx.Response:
         return self._make_request(
             "POST", f"{self.CREWS_RESOURCE}/by-name/{project_name}/deploy"
         )
 
-    def deploy_by_uuid(self, uuid: str) -> requests.Response:
+    def deploy_by_uuid(self, uuid: str) -> httpx.Response:
         return self._make_request("POST", f"{self.CREWS_RESOURCE}/{uuid}/deploy")
 
-    def crew_status_by_name(self, project_name: str) -> requests.Response:
+    def crew_status_by_name(self, project_name: str) -> httpx.Response:
         return self._make_request(
             "GET", f"{self.CREWS_RESOURCE}/by-name/{project_name}/status"
         )
 
-    def crew_status_by_uuid(self, uuid: str) -> requests.Response:
+    def crew_status_by_uuid(self, uuid: str) -> httpx.Response:
         return self._make_request("GET", f"{self.CREWS_RESOURCE}/{uuid}/status")
 
     def crew_by_name(
         self, project_name: str, log_type: str = "deployment"
-    ) -> requests.Response:
+    ) -> httpx.Response:
         return self._make_request(
             "GET", f"{self.CREWS_RESOURCE}/by-name/{project_name}/logs/{log_type}"
         )
 
-    def crew_by_uuid(
-        self, uuid: str, log_type: str = "deployment"
-    ) -> requests.Response:
+    def crew_by_uuid(self, uuid: str, log_type: str = "deployment") -> httpx.Response:
         return self._make_request(
             "GET", f"{self.CREWS_RESOURCE}/{uuid}/logs/{log_type}"
         )
 
-    def delete_crew_by_name(self, project_name: str) -> requests.Response:
+    def delete_crew_by_name(self, project_name: str) -> httpx.Response:
         return self._make_request(
             "DELETE", f"{self.CREWS_RESOURCE}/by-name/{project_name}"
         )
 
-    def delete_crew_by_uuid(self, uuid: str) -> requests.Response:
+    def delete_crew_by_uuid(self, uuid: str) -> httpx.Response:
         return self._make_request("DELETE", f"{self.CREWS_RESOURCE}/{uuid}")
 
-    def list_crews(self) -> requests.Response:
+    def list_crews(self) -> httpx.Response:
         return self._make_request("GET", self.CREWS_RESOURCE)
 
-    def create_crew(self, payload: dict[str, Any]) -> requests.Response:
+    def create_crew(self, payload: dict[str, Any]) -> httpx.Response:
         return self._make_request("POST", self.CREWS_RESOURCE, json=payload)
 
-    def get_organizations(self) -> requests.Response:
+    def get_organizations(self) -> httpx.Response:
         return self._make_request("GET", self.ORGANIZATIONS_RESOURCE)
 
-    def initialize_trace_batch(self, payload: dict[str, Any]) -> requests.Response:
+    def initialize_trace_batch(self, payload: dict[str, Any]) -> httpx.Response:
         return self._make_request(
             "POST",
             f"{self.TRACING_RESOURCE}/batches",
@@ -136,7 +133,7 @@ class PlusAPI:
 
     def initialize_ephemeral_trace_batch(
         self, payload: dict[str, Any]
-    ) -> requests.Response:
+    ) -> httpx.Response:
         return self._make_request(
             "POST",
             f"{self.EPHEMERAL_TRACING_RESOURCE}/batches",
@@ -145,7 +142,7 @@ class PlusAPI:
 
     def send_trace_events(
         self, trace_batch_id: str, payload: dict[str, Any]
-    ) -> requests.Response:
+    ) -> httpx.Response:
         return self._make_request(
             "POST",
             f"{self.TRACING_RESOURCE}/batches/{trace_batch_id}/events",
@@ -155,7 +152,7 @@ class PlusAPI:
 
     def send_ephemeral_trace_events(
         self, trace_batch_id: str, payload: dict[str, Any]
-    ) -> requests.Response:
+    ) -> httpx.Response:
         return self._make_request(
             "POST",
             f"{self.EPHEMERAL_TRACING_RESOURCE}/batches/{trace_batch_id}/events",
@@ -165,7 +162,7 @@ class PlusAPI:
 
     def finalize_trace_batch(
         self, trace_batch_id: str, payload: dict[str, Any]
-    ) -> requests.Response:
+    ) -> httpx.Response:
         return self._make_request(
             "PATCH",
             f"{self.TRACING_RESOURCE}/batches/{trace_batch_id}/finalize",
@@ -175,7 +172,7 @@ class PlusAPI:
 
     def finalize_ephemeral_trace_batch(
         self, trace_batch_id: str, payload: dict[str, Any]
-    ) -> requests.Response:
+    ) -> httpx.Response:
         return self._make_request(
             "PATCH",
             f"{self.EPHEMERAL_TRACING_RESOURCE}/batches/{trace_batch_id}/finalize",
@@ -185,7 +182,7 @@ class PlusAPI:
 
     def mark_trace_batch_as_failed(
         self, trace_batch_id: str, error_message: str
-    ) -> requests.Response:
+    ) -> httpx.Response:
         return self._make_request(
             "PATCH",
             f"{self.TRACING_RESOURCE}/batches/{trace_batch_id}",
@@ -193,13 +190,11 @@ class PlusAPI:
             timeout=30,
         )
 
-    def get_triggers(self) -> requests.Response:
+    def get_triggers(self) -> httpx.Response:
         """Get all available triggers from integrations."""
         return self._make_request("GET", f"{self.INTEGRATIONS_RESOURCE}/apps")
 
-    def get_trigger_payload(
-        self, app_slug: str, trigger_slug: str
-    ) -> requests.Response:
+    def get_trigger_payload(self, app_slug: str, trigger_slug: str) -> httpx.Response:
         """Get sample payload for a specific trigger."""
         return self._make_request(
             "GET", f"{self.INTEGRATIONS_RESOURCE}/{app_slug}/{trigger_slug}/payload"

lib/crewai/src/crewai/cli/provider.py

@@ -8,7 +8,7 @@ from typing import Any
 
 import certifi
 import click
-import requests
+import httpx
 
 from crewai.cli.constants import JSON_URL, MODELS, PROVIDERS
 
@@ -165,20 +165,20 @@ def fetch_provider_data(cache_file: Path) -> dict[str, Any] | None:
     ssl_config = os.environ["SSL_CERT_FILE"] = certifi.where()
 
     try:
-        response = requests.get(JSON_URL, stream=True, timeout=60, verify=ssl_config)
-        response.raise_for_status()
-        data = download_data(response)
-        with open(cache_file, "w") as f:
-            json.dump(data, f)
-        return data
-    except requests.RequestException as e:
+        with httpx.stream("GET", JSON_URL, timeout=60, verify=ssl_config) as response:
+            response.raise_for_status()
+            data = download_data(response)
+            with open(cache_file, "w") as f:
+                json.dump(data, f)
+            return data
+    except httpx.HTTPError as e:
         click.secho(f"Error fetching provider data: {e}", fg="red")
     except json.JSONDecodeError:
         click.secho("Error parsing provider data. Invalid JSON format.", fg="red")
     return None
 
 
-def download_data(response: requests.Response) -> dict[str, Any]:
+def download_data(response: httpx.Response) -> dict[str, Any]:
     """Downloads data from a given HTTP response and returns the JSON content.
 
     Args:
@@ -194,7 +194,7 @@ def download_data(response: requests.Response) -> dict[str, Any]:
     with click.progressbar(
         length=total_size, label="Downloading", show_pos=True
     ) as bar:
-        for chunk in response.iter_content(block_size):
+        for chunk in response.iter_bytes(block_size):
             if chunk:
                 data_chunks.append(chunk)
                 bar.update(len(chunk))

lib/crewai/src/crewai/cli/reset_memories_command.py

@@ -2,43 +2,61 @@ import subprocess
 
 import click
 
-from crewai.cli.utils import get_crews
+from crewai.cli.utils import get_crews, get_flows
+from crewai.flow import Flow
+
+
+def _reset_flow_memory(flow: Flow) -> None:
+    """Reset memory for a single flow instance.
+
+    Handles Memory, MemoryScope (both have .reset()), and MemorySlice
+    (delegates to the underlying ._memory).  Silently succeeds when the
+    storage directory does not exist yet (nothing to reset).
+
+    Args:
+        flow: The flow instance whose memory should be reset.
+    """
+    mem = flow.memory
+    if mem is None:
+        return
+    try:
+        if hasattr(mem, "reset"):
+            mem.reset()
+        elif hasattr(mem, "_memory") and hasattr(mem._memory, "reset"):
+            mem._memory.reset()
+    except (FileNotFoundError, OSError):
+        pass
 
 
 def reset_memories_command(
-    long,
-    short,
-    entity,
-    knowledge,
-    agent_knowledge,
-    kickoff_outputs,
-    all,
+    memory: bool,
+    knowledge: bool,
+    agent_knowledge: bool,
+    kickoff_outputs: bool,
+    all: bool,
 ) -> None:
-    """
-    Reset the crew memories.
+    """Reset the crew and flow memories.
 
     Args:
-      long (bool): Whether to reset the long-term memory.
-      short (bool): Whether to reset the short-term memory.
-      entity (bool): Whether to reset the entity memory.
-      kickoff_outputs (bool): Whether to reset the latest kickoff task outputs.
-      all (bool): Whether to reset all memories.
-      knowledge (bool): Whether to reset the knowledge.
-      agent_knowledge (bool): Whether to reset the agents knowledge.
+        memory: Whether to reset the unified memory.
+        knowledge: Whether to reset the knowledge.
+        agent_knowledge: Whether to reset the agents knowledge.
+        kickoff_outputs: Whether to reset the latest kickoff task outputs.
+        all: Whether to reset all memories.
     """
-
     try:
-        if not any(
-            [long, short, entity, kickoff_outputs, knowledge, agent_knowledge, all]
-        ):
+        if not any([memory, kickoff_outputs, knowledge, agent_knowledge, all]):
             click.echo(
                 "No memory type specified. Please specify at least one type to reset."
             )
             return
 
         crews = get_crews()
-        if not crews:
-            raise ValueError("No crew found.")
+        flows = get_flows()
+
+        if not crews and not flows:
+            raise ValueError("No crew or flow found.")
+
         for crew in crews:
             if all:
                 crew.reset_memories(command_type="all")
@@ -46,20 +64,10 @@ def reset_memories_command(
                     f"[Crew ({crew.name if crew.name else crew.id})] Reset memories command has been completed."
                 )
                 continue
-            if long:
-                crew.reset_memories(command_type="long")
+            if memory:
+                crew.reset_memories(command_type="memory")
                 click.echo(
-                    f"[Crew ({crew.name if crew.name else crew.id})] Long term memory has been reset."
-                )
-            if short:
-                crew.reset_memories(command_type="short")
-                click.echo(
-                    f"[Crew ({crew.name if crew.name else crew.id})] Short term memory has been reset."
-                )
-            if entity:
-                crew.reset_memories(command_type="entity")
-                click.echo(
-                    f"[Crew ({crew.name if crew.name else crew.id})] Entity memory has been reset."
+                    f"[Crew ({crew.name if crew.name else crew.id})] Memory has been reset."
                 )
             if kickoff_outputs:
                 crew.reset_memories(command_type="kickoff_outputs")
@@ -77,6 +85,20 @@ def reset_memories_command(
                     f"[Crew ({crew.name if crew.name else crew.id})] Agents knowledge has been reset."
                 )
 
+        for flow in flows:
+            flow_name = flow.name or flow.__class__.__name__
+            if all:
+                _reset_flow_memory(flow)
+                click.echo(
+                    f"[Flow ({flow_name})] Reset memories command has been completed."
+                )
+                continue
+            if memory:
+                _reset_flow_memory(flow)
+                click.echo(
+                    f"[Flow ({flow_name})] Memory has been reset."
+                )
+
     except subprocess.CalledProcessError as e:
         click.echo(f"An error occurred while resetting the memories: {e}", err=True)
         click.echo(e.output, err=True)

lib/crewai/src/crewai/cli/templates/crew/crew.py

@@ -1,7 +1,6 @@
 from crewai import Agent, Crew, Process, Task
 from crewai.project import CrewBase, agent, crew, task
 from crewai.agents.agent_builder.base_agent import BaseAgent
-from typing import List
 # If you want to run a snippet of code before or after the crew starts,
 # you can use the @before_kickoff and @after_kickoff decorators
 # https://docs.crewai.com/concepts/crews#example-crew-class-with-decorators
@@ -10,8 +9,8 @@ from typing import List
 class {{crew_name}}():
     """{{crew_name}} crew"""
 
-    agents: List[BaseAgent]
-    tasks: List[Task]
+    agents: list[BaseAgent]
+    tasks: list[Task]
 
     # Learn more about YAML configuration files here:
     # Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended

lib/crewai/src/crewai/cli/templates/flow/crews/poem_crew/poem_crew.py

@@ -1,5 +1,3 @@
-from typing import List
-
 from crewai import Agent, Crew, Process, Task
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.project import CrewBase, agent, crew, task
@@ -13,8 +11,8 @@ from crewai.project import CrewBase, agent, crew, task
 class PoemCrew:
     """Poem Crew"""
 
-    agents: List[BaseAgent]
-    tasks: List[Task]
+    agents: list[BaseAgent]
+    tasks: list[Task]
 
     # Learn more about YAML configuration files here:
     # Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended

lib/crewai/src/crewai/cli/tools/main.py

@@ -2,6 +2,7 @@ import base64
 from json import JSONDecodeError
 import os
 from pathlib import Path
+import shutil
 import subprocess
 import tempfile
 from typing import Any
@@ -55,6 +56,11 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
         tree_find_and_replace(project_root, "{{folder_name}}", folder_name)
         tree_find_and_replace(project_root, "{{class_name}}", class_name)
 
+        # Copy AGENTS.md to project root
+        agents_md_src = Path(__file__).parent.parent / "templates" / "AGENTS.md"
+        if agents_md_src.exists():
+            shutil.copy2(agents_md_src, project_root / "AGENTS.md")
+
         old_directory = os.getcwd()
         os.chdir(project_root)
         try:

lib/crewai/src/crewai/cli/utils.py

@@ -386,6 +386,109 @@ def fetch_crews(module_attr: Any) -> list[Crew]:
     return crew_instances
 
 
+def get_flow_instance(module_attr: Any) -> Flow | None:
+    """Check if a module attribute is a user-defined Flow subclass and return an instance.
+
+    Args:
+        module_attr: An attribute from a loaded module.
+
+    Returns:
+        A Flow instance if the attribute is a valid user-defined Flow subclass,
+        None otherwise.
+    """
+    if (
+        isinstance(module_attr, type)
+        and issubclass(module_attr, Flow)
+        and module_attr is not Flow
+    ):
+        try:
+            return module_attr()
+        except Exception:
+            return None
+    return None
+
+
+_SKIP_DIRS = frozenset(
+    {".venv", "venv", ".git", "__pycache__", "node_modules", ".tox", ".nox"}
+)
+
+
+def get_flows(flow_path: str = "main.py") -> list[Flow]:
+    """Get the flow instances from project files.
+
+    Walks the project directory looking for files matching ``flow_path``
+    (default ``main.py``), loads each module, and extracts Flow subclass
+    instances.  Directories that are clearly not user source code (virtual
+    environments, ``.git``, etc.) are pruned to avoid noisy import errors.
+
+    Args:
+        flow_path: Filename to search for (default ``main.py``).
+
+    Returns:
+        A list of discovered Flow instances.
+    """
+    flow_instances: list[Flow] = []
+    try:
+        current_dir = os.getcwd()
+        if current_dir not in sys.path:
+            sys.path.insert(0, current_dir)
+
+        src_dir = os.path.join(current_dir, "src")
+        if os.path.isdir(src_dir) and src_dir not in sys.path:
+            sys.path.insert(0, src_dir)
+
+        search_paths = [".", "src"] if os.path.isdir("src") else ["."]
+
+        for search_path in search_paths:
+            for root, dirs, files in os.walk(search_path):
+                dirs[:] = [
+                    d
+                    for d in dirs
+                    if d not in _SKIP_DIRS and not d.startswith(".")
+                ]
+                if flow_path in files and "cli/templates" not in root:
+                    file_os_path = os.path.join(root, flow_path)
+                    try:
+                        spec = importlib.util.spec_from_file_location(
+                            "flow_module", file_os_path
+                        )
+                        if not spec or not spec.loader:
+                            continue
+
+                        module = importlib.util.module_from_spec(spec)
+                        sys.modules[spec.name] = module
+
+                        try:
+                            spec.loader.exec_module(module)
+
+                            for attr_name in dir(module):
+                                module_attr = getattr(module, attr_name)
+                                try:
+                                    if flow_instance := get_flow_instance(
+                                        module_attr
+                                    ):
+                                        flow_instances.append(flow_instance)
+                                except Exception:  # noqa: S112
+                                    continue
+
+                            if flow_instances:
+                                break
+
+                        except Exception:  # noqa: S112
+                            continue
+
+                    except (ImportError, AttributeError):
+                        continue
+
+            if flow_instances:
+                break
+
+    except Exception:  # noqa: S110
+        pass
+
+    return flow_instances
+
+
 def is_valid_tool(obj: Any) -> bool:
     from crewai.tools.base_tool import Tool
 

lib/crewai/src/crewai/cli/version.py

@@ -6,12 +6,12 @@ from functools import lru_cache
 import importlib.metadata
 import json
 from pathlib import Path
-from typing import Any, cast
+from typing import Any
 from urllib import request
 from urllib.error import URLError
 
 import appdirs
-from packaging.version import InvalidVersion, parse
+from packaging.version import InvalidVersion, Version, parse
 
 
 @lru_cache(maxsize=1)
@@ -42,21 +42,88 @@ def _is_cache_valid(cache_data: Mapping[str, Any]) -> bool:
         return False
 
 
+def _find_latest_non_yanked_version(
+    releases: Mapping[str, list[dict[str, Any]]],
+) -> str | None:
+    """Find the latest non-yanked version from PyPI releases data.
+
+    Args:
+        releases: PyPI releases dict mapping version strings to file info lists.
+
+    Returns:
+        The latest non-yanked version string, or None if all versions are yanked.
+    """
+    best_version: Version | None = None
+    best_version_str: str | None = None
+
+    for version_str, files in releases.items():
+        try:
+            v = parse(version_str)
+        except InvalidVersion:
+            continue
+
+        if v.is_prerelease or v.is_devrelease:
+            continue
+
+        if not files:
+            continue
+
+        all_yanked = all(f.get("yanked", False) for f in files)
+        if all_yanked:
+            continue
+
+        if best_version is None or v > best_version:
+            best_version = v
+            best_version_str = version_str
+
+    return best_version_str
+
+
+def _is_version_yanked(
+    version_str: str,
+    releases: Mapping[str, list[dict[str, Any]]],
+) -> tuple[bool, str]:
+    """Check if a specific version is yanked.
+
+    Args:
+        version_str: The version string to check.
+        releases: PyPI releases dict mapping version strings to file info lists.
+
+    Returns:
+        Tuple of (is_yanked, yanked_reason).
+    """
+    files = releases.get(version_str, [])
+    if not files:
+        return False, ""
+
+    all_yanked = all(f.get("yanked", False) for f in files)
+    if not all_yanked:
+        return False, ""
+
+    for f in files:
+        reason = f.get("yanked_reason", "")
+        if reason:
+            return True, str(reason)
+
+    return True, ""
+
+
 def get_latest_version_from_pypi(timeout: int = 2) -> str | None:
-    """Get the latest version of CrewAI from PyPI.
+    """Get the latest non-yanked version of CrewAI from PyPI.
 
     Args:
         timeout: Request timeout in seconds.
 
     Returns:
-        Latest version string or None if unable to fetch.
+        Latest non-yanked version string or None if unable to fetch.
     """
     cache_file = _get_cache_file()
     if cache_file.exists():
         try:
             cache_data = json.loads(cache_file.read_text())
-            if _is_cache_valid(cache_data):
-                return cast(str | None, cache_data.get("version"))
+            if _is_cache_valid(cache_data) and "current_version" in cache_data:
+                version: str | None = cache_data.get("version")
+                return version
         except (json.JSONDecodeError, OSError):
             pass
 
@@ -65,11 +132,18 @@ def get_latest_version_from_pypi(timeout: int = 2) -> str | None:
             "https://pypi.org/pypi/crewai/json", timeout=timeout
         ) as response:
             data = json.loads(response.read())
-            latest_version = cast(str, data["info"]["version"])
+            releases: dict[str, list[dict[str, Any]]] = data["releases"]
+            latest_version = _find_latest_non_yanked_version(releases)
+
+            current_version = get_crewai_version()
+            is_yanked, yanked_reason = _is_version_yanked(current_version, releases)
 
             cache_data = {
                 "version": latest_version,
                 "timestamp": datetime.now().isoformat(),
+                "current_version": current_version,
+                "current_version_yanked": is_yanked,
+                "current_version_yanked_reason": yanked_reason,
             }
             cache_file.write_text(json.dumps(cache_data))
 
@@ -78,6 +152,40 @@ def get_latest_version_from_pypi(timeout: int = 2) -> str | None:
         return None
 
 
+def is_current_version_yanked() -> tuple[bool, str]:
+    """Check if the currently installed version has been yanked on PyPI.
+
+    Reads from cache if available, otherwise triggers a fetch.
+
+    Returns:
+        Tuple of (is_yanked, yanked_reason).
+    """
+    cache_file = _get_cache_file()
+    if cache_file.exists():
+        try:
+            cache_data = json.loads(cache_file.read_text())
+            if _is_cache_valid(cache_data) and "current_version" in cache_data:
+                current = get_crewai_version()
+                if cache_data.get("current_version") == current:
+                    return (
+                        bool(cache_data.get("current_version_yanked", False)),
+                        str(cache_data.get("current_version_yanked_reason", "")),
+                    )
+        except (json.JSONDecodeError, OSError):
+            pass
+
+    get_latest_version_from_pypi()
+
+    try:
+        cache_data = json.loads(cache_file.read_text())
+        return (
+            bool(cache_data.get("current_version_yanked", False)),
+            str(cache_data.get("current_version_yanked_reason", "")),
+        )
+    except (json.JSONDecodeError, OSError):
+        return False, ""
+
+
 def check_version() -> tuple[str, str | None]:
     """Check current and latest versions.
 

lib/crewai/src/crewai/crew.py

@@ -83,10 +83,6 @@ from crewai.knowledge.knowledge import Knowledge
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.llm import LLM
 from crewai.llms.base_llm import BaseLLM
-from crewai.memory.entity.entity_memory import EntityMemory
-from crewai.memory.external.external_memory import ExternalMemory
-from crewai.memory.long_term.long_term_memory import LongTermMemory
-from crewai.memory.short_term.short_term_memory import ShortTermMemory
 from crewai.process import Process
 from crewai.rag.embeddings.types import EmbedderConfig
 from crewai.rag.types import SearchResult
@@ -174,10 +170,7 @@ class Crew(FlowTrackable, BaseModel):
     _logger: Logger = PrivateAttr()
     _file_handler: FileHandler = PrivateAttr()
     _cache_handler: InstanceOf[CacheHandler] = PrivateAttr(default_factory=CacheHandler)
-    _short_term_memory: InstanceOf[ShortTermMemory] | None = PrivateAttr()
-    _long_term_memory: InstanceOf[LongTermMemory] | None = PrivateAttr()
-    _entity_memory: InstanceOf[EntityMemory] | None = PrivateAttr()
-    _external_memory: InstanceOf[ExternalMemory] | None = PrivateAttr()
+    _memory: Any = PrivateAttr(default=None)  # Unified Memory | MemoryScope
     _train: bool | None = PrivateAttr(default=False)
     _train_iteration: int | None = PrivateAttr()
     _inputs: dict[str, Any] | None = PrivateAttr(default=None)
@@ -187,6 +180,7 @@ class Crew(FlowTrackable, BaseModel):
     _task_output_handler: TaskOutputStorageHandler = PrivateAttr(
         default_factory=TaskOutputStorageHandler
     )
+    _kickoff_event_id: str | None = PrivateAttr(default=None)
 
     name: str | None = Field(default="crew")
     cache: bool = Field(default=True)
@@ -194,25 +188,12 @@ class Crew(FlowTrackable, BaseModel):
     agents: list[BaseAgent] = Field(default_factory=list)
     process: Process = Field(default=Process.sequential)
     verbose: bool = Field(default=False)
-    memory: bool = Field(
+    memory: bool | Any = Field(
         default=False,
-        description="If crew should use memory to store memories of it's execution",
-    )
-    short_term_memory: InstanceOf[ShortTermMemory] | None = Field(
-        default=None,
-        description="An Instance of the ShortTermMemory to be used by the Crew",
-    )
-    long_term_memory: InstanceOf[LongTermMemory] | None = Field(
-        default=None,
-        description="An Instance of the LongTermMemory to be used by the Crew",
-    )
-    entity_memory: InstanceOf[EntityMemory] | None = Field(
-        default=None,
-        description="An Instance of the EntityMemory to be used by the Crew",
-    )
-    external_memory: InstanceOf[ExternalMemory] | None = Field(
-        default=None,
-        description="An Instance of the ExternalMemory to be used by the Crew",
+        description=(
+            "Enable crew memory. Pass True for default Memory(), "
+            "or a Memory/MemoryScope/MemorySlice instance for custom configuration."
+        ),
     )
     embedder: EmbedderConfig | None = Field(
         default=None,
@@ -371,31 +352,23 @@ class Crew(FlowTrackable, BaseModel):
 
         return self
 
-    def _initialize_default_memories(self) -> None:
-        self._long_term_memory = self._long_term_memory or LongTermMemory()
-        self._short_term_memory = self._short_term_memory or ShortTermMemory(
-            crew=self,
-            embedder_config=self.embedder,
-        )
-        self._entity_memory = self.entity_memory or EntityMemory(
-            crew=self, embedder_config=self.embedder
-        )
-
     @model_validator(mode="after")
     def create_crew_memory(self) -> Crew:
-        """Initialize private memory attributes."""
-        self._external_memory = (
-            # External memory does not support a default value since it was
-            # designed to be managed entirely externally
-            self.external_memory.set_crew(self) if self.external_memory else None
-        )
+        """Initialize unified memory, respecting crew embedder config."""
+        if self.memory is True:
+            from crewai.memory.unified_memory import Memory
 
-        self._long_term_memory = self.long_term_memory
-        self._short_term_memory = self.short_term_memory
-        self._entity_memory = self.entity_memory
+            embedder = None
+            if self.embedder is not None:
+                from crewai.rag.embeddings.factory import build_embedder
 
-        if self.memory:
-            self._initialize_default_memories()
+                embedder = build_embedder(self.embedder)
+            self._memory = Memory(embedder=embedder)
+        elif self.memory:
+            # User passed a Memory / MemoryScope / MemorySlice instance
+            self._memory = self.memory
+        else:
+            self._memory = None
 
         return self
 
@@ -759,10 +732,17 @@ class Crew(FlowTrackable, BaseModel):
         except Exception as e:
             crewai_event_bus.emit(
                 self,
-                CrewKickoffFailedEvent(error=str(e), crew_name=self.name),
+                CrewKickoffFailedEvent(
+                    error=str(e),
+                    crew_name=self.name,
+                    started_event_id=self._kickoff_event_id,
+                ),
             )
             raise
         finally:
+            # Ensure all background memory saves complete before returning
+            if self._memory is not None and hasattr(self._memory, "drain_writes"):
+                self._memory.drain_writes()
             clear_files(self.id)
             detach(token)
 
@@ -949,7 +929,11 @@ class Crew(FlowTrackable, BaseModel):
         except Exception as e:
             crewai_event_bus.emit(
                 self,
-                CrewKickoffFailedEvent(error=str(e), crew_name=self.name),
+                CrewKickoffFailedEvent(
+                    error=str(e),
+                    crew_name=self.name,
+                    started_event_id=self._kickoff_event_id,
+                ),
             )
             raise
         finally:
@@ -1314,6 +1298,11 @@ class Crew(FlowTrackable, BaseModel):
         if agent and (hasattr(agent, "mcps") and getattr(agent, "mcps", None)):
             tools = self._add_mcp_tools(task, tools)
 
+        # Add memory tools if memory is available (agent or crew level)
+        resolved_memory = getattr(agent, "memory", None) or self._memory
+        if resolved_memory is not None:
+            tools = self._add_memory_tools(tools, resolved_memory)
+
         files = get_all_files(self.id, task.id)
         if files:
             supported_types: list[str] = []
@@ -1421,6 +1410,22 @@ class Crew(FlowTrackable, BaseModel):
             return self._merge_tools(tools, cast(list[BaseTool], code_tools))
         return tools
 
+    def _add_memory_tools(
+        self, tools: list[BaseTool], memory: Any
+    ) -> list[BaseTool]:
+        """Add recall and remember tools when memory is available.
+
+        Args:
+            tools: Current list of tools.
+            memory: The resolved Memory, MemoryScope, or MemorySlice instance.
+
+        Returns:
+            Updated list with memory tools added.
+        """
+        from crewai.tools.memory_tools import create_memory_tools
+
+        return self._merge_tools(tools, create_memory_tools(memory))
+
     def _add_file_tools(
         self, tools: list[BaseTool], files: dict[str, Any]
     ) -> list[BaseTool]:
@@ -1524,6 +1529,7 @@ class Crew(FlowTrackable, BaseModel):
                 crew_name=self.name,
                 output=final_task_output,
                 total_tokens=self.token_usage.total_tokens,
+                started_event_id=self._kickoff_event_id,
             ),
         )
 
@@ -1664,10 +1670,7 @@ class Crew(FlowTrackable, BaseModel):
             "_execution_span",
             "_file_handler",
             "_cache_handler",
-            "_short_term_memory",
-            "_long_term_memory",
-            "_entity_memory",
-            "_external_memory",
+            "_memory",
             "agents",
             "tasks",
             "knowledge_sources",
@@ -1701,18 +1704,8 @@ class Crew(FlowTrackable, BaseModel):
 
         copied_data = self.model_dump(exclude=exclude)
         copied_data = {k: v for k, v in copied_data.items() if v is not None}
-        if self.short_term_memory:
-            copied_data["short_term_memory"] = self.short_term_memory.model_copy(
-                deep=True
-            )
-        if self.long_term_memory:
-            copied_data["long_term_memory"] = self.long_term_memory.model_copy(
-                deep=True
-            )
-        if self.entity_memory:
-            copied_data["entity_memory"] = self.entity_memory.model_copy(deep=True)
-        if self.external_memory:
-            copied_data["external_memory"] = self.external_memory.model_copy(deep=True)
+        if getattr(self, "_memory", None):
+            copied_data["memory"] = self._memory
 
         copied_data.pop("agents", None)
         copied_data.pop("tasks", None)
@@ -1843,23 +1836,24 @@ class Crew(FlowTrackable, BaseModel):
 
         Args:
             command_type: Type of memory to reset.
-                Valid options: 'long', 'short', 'entity', 'knowledge', 'agent_knowledge'
-                'kickoff_outputs', or 'all'
+                Valid options: 'memory', 'knowledge', 'agent_knowledge',
+                'kickoff_outputs', or 'all'. Legacy names 'long', 'short',
+                'entity', 'external' are treated as 'memory'.
 
         Raises:
             ValueError: If an invalid command type is provided.
             RuntimeError: If memory reset operation fails.
         """
+        legacy_memory = frozenset(["long", "short", "entity", "external"])
+        if command_type in legacy_memory:
+            command_type = "memory"
         valid_types = frozenset(
             [
-                "long",
-                "short",
-                "entity",
+                "memory",
                 "knowledge",
                 "agent_knowledge",
                 "kickoff_outputs",
                 "all",
-                "external",
             ]
         )
 
@@ -1965,25 +1959,10 @@ class Crew(FlowTrackable, BaseModel):
         ) + agent_knowledges
 
         return {
-            "short": {
-                "system": getattr(self, "_short_term_memory", None),
+            "memory": {
+                "system": getattr(self, "_memory", None),
                 "reset": default_reset,
-                "name": "Short Term",
-            },
-            "entity": {
-                "system": getattr(self, "_entity_memory", None),
-                "reset": default_reset,
-                "name": "Entity",
-            },
-            "external": {
-                "system": getattr(self, "_external_memory", None),
-                "reset": default_reset,
-                "name": "External",
-            },
-            "long": {
-                "system": getattr(self, "_long_term_memory", None),
-                "reset": default_reset,
-                "name": "Long Term",
+                "name": "Memory",
             },
             "kickoff_outputs": {
                 "system": getattr(self, "_task_output_handler", None),

lib/crewai/src/crewai/crews/utils.py

@@ -265,10 +265,9 @@ def prepare_kickoff(
             normalized = {}
         normalized = before_callback(normalized)
 
-    future = crewai_event_bus.emit(
-        crew,
-        CrewKickoffStartedEvent(crew_name=crew.name, inputs=normalized),
-    )
+    started_event = CrewKickoffStartedEvent(crew_name=crew.name, inputs=normalized)
+    crew._kickoff_event_id = started_event.event_id
+    future = crewai_event_bus.emit(crew, started_event)
     if future is not None:
         try:
             future.result()

lib/crewai/src/crewai/events/types/flow_events.py

@@ -120,6 +120,52 @@ class FlowPlotEvent(FlowEvent):
     type: str = "flow_plot"
 
 
+class FlowInputRequestedEvent(FlowEvent):
+    """Event emitted when a flow requests user input via ``Flow.ask()``.
+
+    This event is emitted before the flow suspends waiting for user input,
+    allowing UI frameworks and observability tools to know when a flow
+    needs user interaction.
+
+    Attributes:
+        flow_name: Name of the flow requesting input.
+        method_name: Name of the flow method that called ``ask()``.
+        message: The question or prompt being shown to the user.
+        metadata: Optional metadata sent with the question (e.g., user ID,
+            channel, session context).
+    """
+
+    method_name: str
+    message: str
+    metadata: dict[str, Any] | None = None
+    type: str = "flow_input_requested"
+
+
+class FlowInputReceivedEvent(FlowEvent):
+    """Event emitted when user input is received after ``Flow.ask()``.
+
+    This event is emitted after the user provides input (or the request
+    times out), allowing UI frameworks and observability tools to track
+    input collection.
+
+    Attributes:
+        flow_name: Name of the flow that received input.
+        method_name: Name of the flow method that called ``ask()``.
+        message: The original question or prompt.
+        response: The user's response, or None if timed out / unavailable.
+        metadata: Optional metadata sent with the question.
+        response_metadata: Optional metadata from the provider about the
+            response (e.g., who responded, thread ID, timestamps).
+    """
+
+    method_name: str
+    message: str
+    response: str | None = None
+    metadata: dict[str, Any] | None = None
+    response_metadata: dict[str, Any] | None = None
+    type: str = "flow_input_received"
+
+
 class HumanFeedbackRequestedEvent(FlowEvent):
     """Event emitted when human feedback is requested.
 

lib/crewai/src/crewai/events/utils/console_formatter.py

@@ -8,7 +8,7 @@ from rich.live import Live
 from rich.panel import Panel
 from rich.text import Text
 
-from crewai.cli.version import is_newer_version_available
+from crewai.cli.version import is_current_version_yanked, is_newer_version_available
 
 
 _disable_version_check: ContextVar[bool] = ContextVar(
@@ -104,6 +104,22 @@ To update, run: uv sync --upgrade-package crewai"""
                 )
                 self.console.print(panel)
                 self.console.print()
+
+            is_yanked, yanked_reason = is_current_version_yanked()
+            if is_yanked:
+                yanked_message = f"Version {current} has been yanked from PyPI."
+                if yanked_reason:
+                    yanked_message += f"\nReason: {yanked_reason}"
+                yanked_message += "\n\nTo update, run: uv sync --upgrade-package crewai"
+
+                yanked_panel = Panel(
+                    yanked_message,
+                    title="Yanked Version",
+                    border_style="red",
+                    padding=(1, 2),
+                )
+                self.console.print(yanked_panel)
+                self.console.print()
         except Exception:  # noqa: S110
             # Silently ignore errors in version check - it's non-critical
             pass
@@ -154,16 +170,16 @@ To enable tracing, do any one of these:
         """Create standardized status content with consistent formatting."""
         content = Text()
         content.append(f"{title}\n", style=f"{status_style} bold")
-        content.append("Name: \n", style="white")
+        content.append("Name: ", style="white")
         content.append(f"{name}\n", style=status_style)
 
         for label, value in fields.items():
-            content.append(f"{label}: \n", style="white")
+            content.append(f"{label}: ", style="white")
             content.append(
                 f"{value}\n", style=fields.get(f"{label}_style", status_style)
             )
         if tool_args:
-            content.append("Tool Args: \n", style="white")
+            content.append("Tool Args: ", style="white")
             content.append(f"{tool_args}\n", style=status_style)
 
         return content
@@ -721,6 +737,27 @@ To enable tracing, do any one of these:
 
         self.print_panel(content, title, style)
 
+    @staticmethod
+    def _simplify_tools_field(fields: dict[str, Any]) -> dict[str, Any]:
+        """Simplify the tools field to show only tool names instead of full definitions.
+
+        Args:
+            fields: Dictionary of fields that may contain a 'tools' key with
+                    full tool objects.
+
+        Returns:
+            The fields dictionary with 'tools' replaced by a comma-separated
+            string of tool names.
+        """
+        if "tools" in fields:
+            tools = fields["tools"]
+            if tools:
+                tool_names = [getattr(t, "name", str(t)) for t in tools]
+                fields["tools"] = ", ".join(tool_names) if tool_names else "None"
+            else:
+                fields["tools"] = "None"
+        return fields
+
     def handle_lite_agent_execution(
         self,
         lite_agent_role: str,
@@ -732,6 +769,8 @@ To enable tracing, do any one of these:
         if not self.verbose:
             return
 
+        fields = self._simplify_tools_field(fields)
+
         if status == "started":
             self.create_lite_agent_branch(lite_agent_role)
             if fields:

lib/crewai/src/crewai/experimental/agent_executor.py

@@ -1,7 +1,10 @@
 from __future__ import annotations
 
+import asyncio
 from collections.abc import Callable, Coroutine
+from concurrent.futures import ThreadPoolExecutor, as_completed
 from datetime import datetime
+import inspect
 import json
 import threading
 from typing import TYPE_CHECKING, Any, Literal, cast
@@ -63,6 +66,7 @@ from crewai.utilities.agent_utils import (
     has_reached_max_iterations,
     is_context_length_exceeded,
     is_inside_event_loop,
+    parse_tool_call_args,
     process_llm_response,
     track_delegation_if_needed,
 )
@@ -668,9 +672,12 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
         if not self.state.pending_tool_calls:
             return "native_tool_completed"
 
+        pending_tool_calls = list(self.state.pending_tool_calls)
+        self.state.pending_tool_calls.clear()
+
         # Group all tool calls into a single assistant message
         tool_calls_to_report = []
-        for tool_call in self.state.pending_tool_calls:
+        for tool_call in pending_tool_calls:
             info = extract_tool_call_info(tool_call)
             if not info:
                 continue
@@ -695,202 +702,86 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
                 "content": None,
                 "tool_calls": tool_calls_to_report,
             }
-            if all(
-                type(tc).__qualname__ == "Part" for tc in self.state.pending_tool_calls
-            ):
-                assistant_message["raw_tool_call_parts"] = list(
-                    self.state.pending_tool_calls
-                )
+            if all(type(tc).__qualname__ == "Part" for tc in pending_tool_calls):
+                assistant_message["raw_tool_call_parts"] = list(pending_tool_calls)
             self.state.messages.append(assistant_message)
 
-        # Now execute each tool
-        while self.state.pending_tool_calls:
-            tool_call = self.state.pending_tool_calls.pop(0)
-            info = extract_tool_call_info(tool_call)
-            if not info:
-                continue
+        runnable_tool_calls = [
+            tool_call
+            for tool_call in pending_tool_calls
+            if extract_tool_call_info(tool_call) is not None
+        ]
+        should_parallelize = self._should_parallelize_native_tool_calls(
+            runnable_tool_calls
+        )
 
-            call_id, func_name, func_args = info
-
-            # Parse arguments
-            if isinstance(func_args, str):
-                try:
-                    args_dict = json.loads(func_args)
-                except json.JSONDecodeError:
-                    args_dict = {}
-            else:
-                args_dict = func_args
-
-            # Get agent_key for event tracking
-            agent_key = (
-                getattr(self.agent, "key", "unknown") if self.agent else "unknown"
-            )
-
-            # Find original tool by matching sanitized name (needed for cache_function and result_as_answer)
-            original_tool = None
-            for tool in self.original_tools or []:
-                if sanitize_tool_name(tool.name) == func_name:
-                    original_tool = tool
-                    break
-
-            # Check if tool has reached max usage count
-            max_usage_reached = False
-            if (
-                original_tool
-                and original_tool.max_usage_count is not None
-                and original_tool.current_usage_count >= original_tool.max_usage_count
-            ):
-                max_usage_reached = True
-
-            # Check cache before executing
-            from_cache = False
-            input_str = json.dumps(args_dict) if args_dict else ""
-            if self.tools_handler and self.tools_handler.cache:
-                cached_result = self.tools_handler.cache.read(
-                    tool=func_name, input=input_str
+        execution_results: list[dict[str, Any]] = []
+        if should_parallelize:
+            max_workers = min(8, len(runnable_tool_calls))
+            with ThreadPoolExecutor(max_workers=max_workers) as pool:
+                future_to_idx = {
+                    pool.submit(self._execute_single_native_tool_call, tool_call): idx
+                    for idx, tool_call in enumerate(runnable_tool_calls)
+                }
+                ordered_results: list[dict[str, Any] | None] = [None] * len(
+                    runnable_tool_calls
                 )
-                if cached_result is not None:
-                    result = (
-                        str(cached_result)
-                        if not isinstance(cached_result, str)
-                        else cached_result
-                    )
-                    from_cache = True
+                for future in as_completed(future_to_idx):
+                    idx = future_to_idx[future]
+                    ordered_results[idx] = future.result()
+                execution_results = [
+                    result for result in ordered_results if result is not None
+                ]
+        else:
+            # Execute sequentially so result_as_answer tools can short-circuit
+            # immediately without running remaining calls.
+            for tool_call in runnable_tool_calls:
+                execution_result = self._execute_single_native_tool_call(tool_call)
+                call_id = cast(str, execution_result["call_id"])
+                func_name = cast(str, execution_result["func_name"])
+                result = cast(str, execution_result["result"])
+                from_cache = cast(bool, execution_result["from_cache"])
+                original_tool = execution_result["original_tool"]
 
-            # Emit tool usage started event
-            started_at = datetime.now()
-            crewai_event_bus.emit(
-                self,
-                event=ToolUsageStartedEvent(
-                    tool_name=func_name,
-                    tool_args=args_dict,
-                    from_agent=self.agent,
-                    from_task=self.task,
-                    agent_key=agent_key,
-                ),
-            )
-            error_event_emitted = False
+                tool_message: LLMMessage = {
+                    "role": "tool",
+                    "tool_call_id": call_id,
+                    "name": func_name,
+                    "content": result,
+                }
+                self.state.messages.append(tool_message)
 
-            track_delegation_if_needed(func_name, args_dict, self.task)
-
-            structured_tool: CrewStructuredTool | None = None
-            for structured in self.tools or []:
-                if sanitize_tool_name(structured.name) == func_name:
-                    structured_tool = structured
-                    break
-
-            hook_blocked = False
-            before_hook_context = ToolCallHookContext(
-                tool_name=func_name,
-                tool_input=args_dict,
-                tool=structured_tool,  # type: ignore[arg-type]
-                agent=self.agent,
-                task=self.task,
-                crew=self.crew,
-            )
-            before_hooks = get_before_tool_call_hooks()
-            try:
-                for hook in before_hooks:
-                    hook_result = hook(before_hook_context)
-                    if hook_result is False:
-                        hook_blocked = True
-                        break
-            except Exception as hook_error:
-                if self.agent.verbose:
+                # Log the tool execution
+                if self.agent and self.agent.verbose:
+                    cache_info = " (from cache)" if from_cache else ""
                     self._printer.print(
-                        content=f"Error in before_tool_call hook: {hook_error}",
-                        color="red",
+                        content=f"Tool {func_name} executed with result{cache_info}: {result[:200]}...",
+                        color="green",
                     )
 
-            if hook_blocked:
-                result = f"Tool execution blocked by hook. Tool: {func_name}"
-            elif not from_cache and not max_usage_reached:
-                result = "Tool not found"
-                if func_name in self._available_functions:
-                    try:
-                        tool_func = self._available_functions[func_name]
-                        raw_result = tool_func(**args_dict)
-
-                        # Add to cache after successful execution (before string conversion)
-                        if self.tools_handler and self.tools_handler.cache:
-                            should_cache = True
-                            if original_tool:
-                                should_cache = original_tool.cache_function(
-                                    args_dict, raw_result
-                                )
-                            if should_cache:
-                                self.tools_handler.cache.add(
-                                    tool=func_name, input=input_str, output=raw_result
-                                )
-
-                        # Convert to string for message
-                        result = (
-                            str(raw_result)
-                            if not isinstance(raw_result, str)
-                            else raw_result
-                        )
-                    except Exception as e:
-                        result = f"Error executing tool: {e}"
-                        if self.task:
-                            self.task.increment_tools_errors()
-                        # Emit tool usage error event
-                        crewai_event_bus.emit(
-                            self,
-                            event=ToolUsageErrorEvent(
-                                tool_name=func_name,
-                                tool_args=args_dict,
-                                from_agent=self.agent,
-                                from_task=self.task,
-                                agent_key=agent_key,
-                                error=e,
-                            ),
-                        )
-                        error_event_emitted = True
-            elif max_usage_reached and original_tool:
-                # Return error message when max usage limit is reached
-                result = f"Tool '{func_name}' has reached its usage limit of {original_tool.max_usage_count} times and cannot be used anymore."
-
-            # Execute after_tool_call hooks (even if blocked, to allow logging/monitoring)
-            after_hook_context = ToolCallHookContext(
-                tool_name=func_name,
-                tool_input=args_dict,
-                tool=structured_tool,  # type: ignore[arg-type]
-                agent=self.agent,
-                task=self.task,
-                crew=self.crew,
-                tool_result=result,
-            )
-            after_hooks = get_after_tool_call_hooks()
-            try:
-                for after_hook in after_hooks:
-                    after_hook_result = after_hook(after_hook_context)
-                    if after_hook_result is not None:
-                        result = after_hook_result
-                        after_hook_context.tool_result = result
-            except Exception as hook_error:
-                if self.agent.verbose:
-                    self._printer.print(
-                        content=f"Error in after_tool_call hook: {hook_error}",
-                        color="red",
-                    )
-
-            if not error_event_emitted:
-                crewai_event_bus.emit(
-                    self,
-                    event=ToolUsageFinishedEvent(
+                if (
+                    original_tool
+                    and hasattr(original_tool, "result_as_answer")
+                    and original_tool.result_as_answer
+                ):
+                    self.state.current_answer = AgentFinish(
+                        thought="Tool result is the final answer",
                         output=result,
-                        tool_name=func_name,
-                        tool_args=args_dict,
-                        from_agent=self.agent,
-                        from_task=self.task,
-                        agent_key=agent_key,
-                        started_at=started_at,
-                        finished_at=datetime.now(),
-                    ),
-                )
+                        text=result,
+                    )
+                    self.state.is_finished = True
+                    return "tool_result_is_final"
 
-            # Append tool result message
-            tool_message: LLMMessage = {
+            return "native_tool_completed"
+
+        for execution_result in execution_results:
+            call_id = cast(str, execution_result["call_id"])
+            func_name = cast(str, execution_result["func_name"])
+            result = cast(str, execution_result["result"])
+            from_cache = cast(bool, execution_result["from_cache"])
+            original_tool = execution_result["original_tool"]
+
+            tool_message = {
                 "role": "tool",
                 "tool_call_id": call_id,
                 "name": func_name,
@@ -922,6 +813,220 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
 
         return "native_tool_completed"
 
+    def _should_parallelize_native_tool_calls(self, tool_calls: list[Any]) -> bool:
+        """Determine if native tool calls are safe to run in parallel."""
+        if len(tool_calls) <= 1:
+            return False
+
+        for tool_call in tool_calls:
+            info = extract_tool_call_info(tool_call)
+            if not info:
+                continue
+            _, func_name, _ = info
+
+            original_tool = None
+            for tool in self.original_tools or []:
+                if sanitize_tool_name(tool.name) == func_name:
+                    original_tool = tool
+                    break
+
+            if not original_tool:
+                continue
+
+            if getattr(original_tool, "result_as_answer", False):
+                return False
+            if getattr(original_tool, "max_usage_count", None) is not None:
+                return False
+
+        return True
+
+    def _execute_single_native_tool_call(self, tool_call: Any) -> dict[str, Any]:
+        """Execute a single native tool call and return metadata/result."""
+        info = extract_tool_call_info(tool_call)
+        if not info:
+            raise ValueError("Invalid native tool call format")
+
+        call_id, func_name, func_args = info
+
+        # Parse arguments
+        args_dict, parse_error = parse_tool_call_args(func_args, func_name, call_id)
+        if parse_error is not None:
+            return parse_error
+
+        # Get agent_key for event tracking
+        agent_key = getattr(self.agent, "key", "unknown") if self.agent else "unknown"
+
+        # Find original tool by matching sanitized name (needed for cache_function and result_as_answer)
+        original_tool = None
+        for tool in self.original_tools or []:
+            if sanitize_tool_name(tool.name) == func_name:
+                original_tool = tool
+                break
+
+        # Check if tool has reached max usage count
+        max_usage_reached = False
+        if (
+            original_tool
+            and original_tool.max_usage_count is not None
+            and original_tool.current_usage_count >= original_tool.max_usage_count
+        ):
+            max_usage_reached = True
+
+        # Check cache before executing
+        from_cache = False
+        input_str = json.dumps(args_dict) if args_dict else ""
+        if self.tools_handler and self.tools_handler.cache:
+            cached_result = self.tools_handler.cache.read(
+                tool=func_name, input=input_str
+            )
+            if cached_result is not None:
+                result = (
+                    str(cached_result)
+                    if not isinstance(cached_result, str)
+                    else cached_result
+                )
+                from_cache = True
+
+        # Emit tool usage started event
+        started_at = datetime.now()
+        crewai_event_bus.emit(
+            self,
+            event=ToolUsageStartedEvent(
+                tool_name=func_name,
+                tool_args=args_dict,
+                from_agent=self.agent,
+                from_task=self.task,
+                agent_key=agent_key,
+            ),
+        )
+        error_event_emitted = False
+
+        track_delegation_if_needed(func_name, args_dict, self.task)
+
+        structured_tool: CrewStructuredTool | None = None
+        for structured in self.tools or []:
+            if sanitize_tool_name(structured.name) == func_name:
+                structured_tool = structured
+                break
+
+        hook_blocked = False
+        before_hook_context = ToolCallHookContext(
+            tool_name=func_name,
+            tool_input=args_dict,
+            tool=structured_tool,  # type: ignore[arg-type]
+            agent=self.agent,
+            task=self.task,
+            crew=self.crew,
+        )
+        before_hooks = get_before_tool_call_hooks()
+        try:
+            for hook in before_hooks:
+                hook_result = hook(before_hook_context)
+                if hook_result is False:
+                    hook_blocked = True
+                    break
+        except Exception as hook_error:
+            if self.agent.verbose:
+                self._printer.print(
+                    content=f"Error in before_tool_call hook: {hook_error}",
+                    color="red",
+                )
+
+        if hook_blocked:
+            result = f"Tool execution blocked by hook. Tool: {func_name}"
+        elif not from_cache and not max_usage_reached:
+            result = "Tool not found"
+            if func_name in self._available_functions:
+                try:
+                    tool_func = self._available_functions[func_name]
+                    raw_result = tool_func(**args_dict)
+
+                    # Add to cache after successful execution (before string conversion)
+                    if self.tools_handler and self.tools_handler.cache:
+                        should_cache = True
+                        if original_tool:
+                            should_cache = original_tool.cache_function(
+                                args_dict, raw_result
+                            )
+                        if should_cache:
+                            self.tools_handler.cache.add(
+                                tool=func_name, input=input_str, output=raw_result
+                            )
+
+                    # Convert to string for message
+                    result = (
+                        str(raw_result)
+                        if not isinstance(raw_result, str)
+                        else raw_result
+                    )
+                except Exception as e:
+                    result = f"Error executing tool: {e}"
+                    if self.task:
+                        self.task.increment_tools_errors()
+                    # Emit tool usage error event
+                    crewai_event_bus.emit(
+                        self,
+                        event=ToolUsageErrorEvent(
+                            tool_name=func_name,
+                            tool_args=args_dict,
+                            from_agent=self.agent,
+                            from_task=self.task,
+                            agent_key=agent_key,
+                            error=e,
+                        ),
+                    )
+                    error_event_emitted = True
+        elif max_usage_reached and original_tool:
+            # Return error message when max usage limit is reached
+            result = f"Tool '{func_name}' has reached its usage limit of {original_tool.max_usage_count} times and cannot be used anymore."
+
+        # Execute after_tool_call hooks (even if blocked, to allow logging/monitoring)
+        after_hook_context = ToolCallHookContext(
+            tool_name=func_name,
+            tool_input=args_dict,
+            tool=structured_tool,  # type: ignore[arg-type]
+            agent=self.agent,
+            task=self.task,
+            crew=self.crew,
+            tool_result=result,
+        )
+        after_hooks = get_after_tool_call_hooks()
+        try:
+            for after_hook in after_hooks:
+                after_hook_result = after_hook(after_hook_context)
+                if after_hook_result is not None:
+                    result = after_hook_result
+                    after_hook_context.tool_result = result
+        except Exception as hook_error:
+            if self.agent.verbose:
+                self._printer.print(
+                    content=f"Error in after_tool_call hook: {hook_error}",
+                    color="red",
+                )
+
+        if not error_event_emitted:
+            crewai_event_bus.emit(
+                self,
+                event=ToolUsageFinishedEvent(
+                    output=result,
+                    tool_name=func_name,
+                    tool_args=args_dict,
+                    from_agent=self.agent,
+                    from_task=self.task,
+                    agent_key=agent_key,
+                    started_at=started_at,
+                    finished_at=datetime.now(),
+                ),
+            )
+
+        return {
+            "call_id": call_id,
+            "func_name": func_name,
+            "result": result,
+            "from_cache": from_cache,
+            "original_tool": original_tool,
+        }
+
     def _extract_tool_name(self, tool_call: Any) -> str:
         """Extract tool name from various tool call formats."""
         if hasattr(tool_call, "function"):
@@ -1106,9 +1211,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
             if self.state.ask_for_human_input:
                 formatted_answer = self._handle_human_feedback(formatted_answer)
 
-            self._create_short_term_memory(formatted_answer)
-            self._create_long_term_memory(formatted_answer)
-            self._create_external_memory(formatted_answer)
+            self._save_to_memory(formatted_answer)
 
             return {"output": formatted_answer.output}
 
@@ -1191,9 +1294,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
             if self.state.ask_for_human_input:
                 formatted_answer = await self._ahandle_human_feedback(formatted_answer)
 
-            self._create_short_term_memory(formatted_answer)
-            self._create_long_term_memory(formatted_answer)
-            self._create_external_memory(formatted_answer)
+            self._save_to_memory(formatted_answer)
 
             return {"output": formatted_answer.output}
 
@@ -1256,7 +1357,9 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
             formatted_answer: Current agent response.
         """
         if self.step_callback:
-            self.step_callback(formatted_answer)
+            cb_result = self.step_callback(formatted_answer)
+            if inspect.iscoroutine(cb_result):
+                asyncio.run(cb_result)
 
     def _append_message_to_state(
         self, text: str, role: Literal["user", "assistant", "system"] = "assistant"

lib/crewai/src/crewai/flow/__init__.py

@@ -7,6 +7,7 @@ from crewai.flow.async_feedback import (
 from crewai.flow.flow import Flow, and_, listen, or_, router, start
 from crewai.flow.flow_config import flow_config
 from crewai.flow.human_feedback import HumanFeedbackResult, human_feedback
+from crewai.flow.input_provider import InputProvider, InputResponse
 from crewai.flow.persistence import persist
 from crewai.flow.visualization import (
     FlowStructure,
@@ -22,6 +23,8 @@ __all__ = [
     "HumanFeedbackPending",
     "HumanFeedbackProvider",
     "HumanFeedbackResult",
+    "InputProvider",
+    "InputResponse",
     "PendingFeedbackContext",
     "and_",
     "build_flow_structure",

lib/crewai/src/crewai/flow/async_feedback/providers.py

@@ -1,7 +1,8 @@
-"""Default provider implementations for human feedback.
+"""Default provider implementations for human feedback and user input.
 
 This module provides the ConsoleProvider, which is the default synchronous
-provider that collects feedback via console input.
+provider that collects both feedback (for ``@human_feedback``) and user input
+(for ``Flow.ask()``) via console.
 """
 
 from __future__ import annotations
@@ -16,20 +17,23 @@ if TYPE_CHECKING:
 
 
 class ConsoleProvider:
-    """Default synchronous console-based feedback provider.
+    """Default synchronous console-based provider for feedback and input.
 
     This provider blocks execution and waits for console input from the user.
-    It displays the method output with formatting and prompts for feedback.
+    It serves two purposes:
+
+    - **Feedback** (``request_feedback``): Used by ``@human_feedback`` to
+      display method output and collect review feedback.
+    - **Input** (``request_input``): Used by ``Flow.ask()`` to prompt the
+      user with a question and collect a response.
 
     This is the default provider used when no custom provider is specified
-    in the @human_feedback decorator.
+    in the ``@human_feedback`` decorator or on the Flow's ``input_provider``.
 
-    Example:
+    Example (feedback):
         ```python
         from crewai.flow.async_feedback import ConsoleProvider
 
-
-        # Explicitly use console provider
         @human_feedback(
             message="Review this:",
             provider=ConsoleProvider(),
@@ -37,9 +41,20 @@ class ConsoleProvider:
         def my_method(self):
             return "Content to review"
         ```
+
+    Example (input):
+        ```python
+        from crewai.flow import Flow, start
+
+        class MyFlow(Flow):
+            @start()
+            def gather_info(self):
+                topic = self.ask("What topic should we research?")
+                return topic
+        ```
     """
 
-    def __init__(self, verbose: bool = True):
+    def __init__(self, verbose: bool = True) -> None:
         """Initialize the console provider.
 
         Args:
@@ -124,3 +139,55 @@ class ConsoleProvider:
         finally:
             # Resume live updates
             formatter.resume_live_updates()
+
+    def request_input(
+        self,
+        message: str,
+        flow: Flow[Any],
+        metadata: dict[str, Any] | None = None,
+    ) -> str | None:
+        """Request user input via console (blocking).
+
+        Displays the prompt message with formatting and waits for the user
+        to type their response. Used by ``Flow.ask()``.
+
+        Unlike ``request_feedback``, this method does not display an
+        "OUTPUT FOR REVIEW" panel or emit feedback-specific events (those
+        are handled by ``ask()`` itself).
+
+        Args:
+            message: The question or prompt to display to the user.
+            flow: The Flow instance requesting input.
+            metadata: Optional metadata from the caller. Ignored by the
+                console provider (console has no concept of user routing).
+
+        Returns:
+            The user's input as a stripped string. Returns empty string
+            if user presses Enter without input. Never returns None
+            (console input is always available).
+        """
+        from crewai.events.event_listener import event_listener
+
+        # Pause live updates during human input
+        formatter = event_listener.formatter
+        formatter.pause_live_updates()
+
+        try:
+            console = formatter.console
+
+            if self.verbose:
+                console.print()
+                console.print(message, style="yellow")
+                console.print()
+
+                response = input(">>> \n").strip()
+            else:
+                response = input(f"{message} ").strip()
+
+            # Add line break after input so formatter output starts clean
+            console.print()
+
+            return response
+        finally:
+            # Resume live updates
+            formatter.resume_live_updates()

lib/crewai/src/crewai/flow/flow.py

@@ -10,6 +10,7 @@ import asyncio
 from collections.abc import (
     Callable,
     ItemsView,
+    Iterable,
     Iterator,
     KeysView,
     Sequence,
@@ -17,6 +18,7 @@ from collections.abc import (
 )
 from concurrent.futures import Future
 import copy
+import enum
 import inspect
 import logging
 import threading
@@ -27,8 +29,10 @@ from typing import (
     Generic,
     Literal,
     ParamSpec,
+    SupportsIndex,
     TypeVar,
     cast,
+    overload,
 )
 from uuid import uuid4
 
@@ -77,7 +81,12 @@ from crewai.flow.flow_wrappers import (
     StartMethod,
 )
 from crewai.flow.persistence.base import FlowPersistence
-from crewai.flow.types import FlowExecutionData, FlowMethodName, PendingListenerKey
+from crewai.flow.types import (
+    FlowExecutionData,
+    FlowMethodName,
+    InputHistoryEntry,
+    PendingListenerKey,
+)
 from crewai.flow.utils import (
     _extract_all_methods,
     _extract_all_methods_recursive,
@@ -416,13 +425,17 @@ def and_(*conditions: str | FlowCondition | Callable[..., Any]) -> FlowCondition
     return {"type": AND_CONDITION, "conditions": processed_conditions}
 
 
-class LockedListProxy(Generic[T]):
+class LockedListProxy(list, Generic[T]):  # type: ignore[type-arg]
     """Thread-safe proxy for list operations.
 
-    Wraps a list and uses a lock for all mutating operations.
+    Subclasses ``list`` so that ``isinstance(proxy, list)`` returns True,
+    which is required by libraries like LanceDB and Pydantic that do strict
+    type checks. All mutations go through the lock; reads delegate to the
+    underlying list.
     """
 
     def __init__(self, lst: list[T], lock: threading.Lock) -> None:
+        super().__init__()  # empty builtin list; all access goes through self._list
         self._list = lst
         self._lock = lock
 
@@ -430,11 +443,11 @@ class LockedListProxy(Generic[T]):
         with self._lock:
             self._list.append(item)
 
-    def extend(self, items: list[T]) -> None:
+    def extend(self, items: Iterable[T]) -> None:
         with self._lock:
             self._list.extend(items)
 
-    def insert(self, index: int, item: T) -> None:
+    def insert(self, index: SupportsIndex, item: T) -> None:
         with self._lock:
             self._list.insert(index, item)
 
@@ -442,7 +455,7 @@ class LockedListProxy(Generic[T]):
         with self._lock:
             self._list.remove(item)
 
-    def pop(self, index: int = -1) -> T:
+    def pop(self, index: SupportsIndex = -1) -> T:
         with self._lock:
             return self._list.pop(index)
 
@@ -450,15 +463,23 @@ class LockedListProxy(Generic[T]):
         with self._lock:
             self._list.clear()
 
-    def __setitem__(self, index: int, value: T) -> None:
+    @overload
+    def __setitem__(self, index: SupportsIndex, value: T) -> None: ...
+    @overload
+    def __setitem__(self, index: slice, value: Iterable[T]) -> None: ...
+    def __setitem__(self, index: Any, value: Any) -> None:
         with self._lock:
             self._list[index] = value
 
-    def __delitem__(self, index: int) -> None:
+    def __delitem__(self, index: SupportsIndex | slice) -> None:
         with self._lock:
             del self._list[index]
 
-    def __getitem__(self, index: int) -> T:
+    @overload
+    def __getitem__(self, index: SupportsIndex) -> T: ...
+    @overload
+    def __getitem__(self, index: slice) -> list[T]: ...
+    def __getitem__(self, index: Any) -> Any:
         return self._list[index]
 
     def __len__(self) -> int:
@@ -476,14 +497,31 @@ class LockedListProxy(Generic[T]):
     def __bool__(self) -> bool:
         return bool(self._list)
 
+    def __eq__(self, other: object) -> bool:
+        """Compare based on the underlying list contents."""
+        if isinstance(other, LockedListProxy):
+            # Avoid deadlocks by acquiring locks in a consistent order.
+            first, second = (self, other) if id(self) <= id(other) else (other, self)
+            with first._lock:
+                with second._lock:
+                    return first._list == second._list
+        with self._lock:
+            return self._list == other
 
-class LockedDictProxy(Generic[T]):
+    def __ne__(self, other: object) -> bool:
+        return not self.__eq__(other)
+
+
+class LockedDictProxy(dict, Generic[T]):  # type: ignore[type-arg]
     """Thread-safe proxy for dict operations.
 
-    Wraps a dict and uses a lock for all mutating operations.
+    Subclasses ``dict`` so that ``isinstance(proxy, dict)`` returns True,
+    which is required by libraries like Pydantic that do strict type checks.
+    All mutations go through the lock; reads delegate to the underlying dict.
     """
 
     def __init__(self, d: dict[str, T], lock: threading.Lock) -> None:
+        super().__init__()  # empty builtin dict; all access goes through self._dict
         self._dict = d
         self._lock = lock
 
@@ -495,11 +533,11 @@ class LockedDictProxy(Generic[T]):
         with self._lock:
             del self._dict[key]
 
-    def pop(self, key: str, *default: T) -> T:
+    def pop(self, key: str, *default: T) -> T:  # type: ignore[override]
         with self._lock:
             return self._dict.pop(key, *default)
 
-    def update(self, other: dict[str, T]) -> None:
+    def update(self, other: dict[str, T]) -> None:  # type: ignore[override]
         with self._lock:
             self._dict.update(other)
 
@@ -507,7 +545,7 @@ class LockedDictProxy(Generic[T]):
         with self._lock:
             self._dict.clear()
 
-    def setdefault(self, key: str, default: T) -> T:
+    def setdefault(self, key: str, default: T) -> T:  # type: ignore[override]
         with self._lock:
             return self._dict.setdefault(key, default)
 
@@ -523,16 +561,16 @@ class LockedDictProxy(Generic[T]):
     def __contains__(self, key: object) -> bool:
         return key in self._dict
 
-    def keys(self) -> KeysView[str]:
+    def keys(self) -> KeysView[str]:  # type: ignore[override]
         return self._dict.keys()
 
-    def values(self) -> ValuesView[T]:
+    def values(self) -> ValuesView[T]:  # type: ignore[override]
         return self._dict.values()
 
-    def items(self) -> ItemsView[str, T]:
+    def items(self) -> ItemsView[str, T]:  # type: ignore[override]
         return self._dict.items()
 
-    def get(self, key: str, default: T | None = None) -> T | None:
+    def get(self, key: str, default: T | None = None) -> T | None:  # type: ignore[override]
         return self._dict.get(key, default)
 
     def __repr__(self) -> str:
@@ -541,6 +579,20 @@ class LockedDictProxy(Generic[T]):
     def __bool__(self) -> bool:
         return bool(self._dict)
 
+    def __eq__(self, other: object) -> bool:
+        """Compare based on the underlying dict contents."""
+        if isinstance(other, LockedDictProxy):
+            # Avoid deadlocks by acquiring locks in a consistent order.
+            first, second = (self, other) if id(self) <= id(other) else (other, self)
+            with first._lock:
+                with second._lock:
+                    return first._dict == second._dict
+        with self._lock:
+            return self._dict == other
+
+    def __ne__(self, other: object) -> bool:
+        return not self.__eq__(other)
+
 
 class StateProxy(Generic[T]):
     """Proxy that provides thread-safe access to flow state.
@@ -700,6 +752,10 @@ class Flow(Generic[T], metaclass=FlowMeta):
     name: str | None = None
     tracing: bool | None = None
     stream: bool = False
+    memory: Any = (
+        None  # Memory | MemoryScope | MemorySlice | None; auto-created if not set
+    )
+    input_provider: Any = None  # InputProvider | None; per-flow override for self.ask()
 
     def __class_getitem__(cls: type[Flow[T]], item: type[T]) -> type[Flow[T]]:
         class _FlowGeneric(cls):  # type: ignore
@@ -746,6 +802,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
         self._pending_feedback_context: PendingFeedbackContext | None = None
         self.suppress_flow_events: bool = suppress_flow_events
 
+        # User input history (for self.ask())
+        self._input_history: list[InputHistoryEntry] = []
+
         # Initialize state with initial values
         self._state = self._create_initial_state()
         self.tracing = tracing
@@ -767,6 +826,14 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 ),
             )
 
+        # Auto-create memory if not provided at class or instance level.
+        # Internal flows (RecallFlow, EncodingFlow) set _skip_auto_memory
+        # to avoid creating a wasteful standalone Memory instance.
+        if self.memory is None and not getattr(self, "_skip_auto_memory", False):
+            from crewai.memory.unified_memory import Memory
+
+            self.memory = Memory()
+
         # Register all flow-related methods
         for method_name in dir(self):
             if not method_name.startswith("_"):
@@ -777,6 +844,63 @@ class Flow(Generic[T], metaclass=FlowMeta):
                         method = method.__get__(self, self.__class__)
                     self._methods[method.__name__] = method
 
+    def recall(self, query: str, **kwargs: Any) -> Any:
+        """Recall relevant memories. Delegates to this flow's memory.
+
+        Args:
+            query: Natural language query.
+            **kwargs: Passed to memory.recall (e.g. scope, categories, limit, depth).
+
+        Returns:
+            Result of memory.recall(query, **kwargs).
+
+        Raises:
+            ValueError: If no memory is configured for this flow.
+        """
+        if self.memory is None:
+            raise ValueError("No memory configured for this flow")
+        return self.memory.recall(query, **kwargs)
+
+    def remember(self, content: str | list[str], **kwargs: Any) -> Any:
+        """Store one or more items in memory.
+
+        Pass a single string for synchronous save (returns the MemoryRecord).
+        Pass a list of strings for non-blocking batch save (returns immediately).
+
+        Args:
+            content: Text or list of texts to remember.
+            **kwargs: Passed to memory.remember / remember_many
+                      (e.g. scope, categories, metadata, importance).
+
+        Returns:
+            MemoryRecord for single item, empty list for batch (background save).
+
+        Raises:
+            ValueError: If no memory is configured for this flow.
+        """
+        if self.memory is None:
+            raise ValueError("No memory configured for this flow")
+        if isinstance(content, list):
+            return self.memory.remember_many(content, **kwargs)
+        return self.memory.remember(content, **kwargs)
+
+    def extract_memories(self, content: str) -> list[str]:
+        """Extract discrete memories from content. Delegates to this flow's memory.
+
+        Args:
+            content: Raw text (e.g. task + result dump).
+
+        Returns:
+            List of short, self-contained memory statements.
+
+        Raises:
+            ValueError: If no memory is configured for this flow.
+        """
+        if self.memory is None:
+            raise ValueError("No memory configured for this flow")
+        result: list[str] = self.memory.extract_memories(content)
+        return result
+
     def _mark_or_listener_fired(self, listener_name: FlowMethodName) -> bool:
         """Mark an OR listener as fired atomically.
 
@@ -1246,8 +1370,10 @@ class Flow(Generic[T], metaclass=FlowMeta):
             ValueError: If structured state model lacks 'id' field
             TypeError: If state is neither BaseModel nor dictionary
         """
+        init_state = self.initial_state
+
         # Handle case where initial_state is None but we have a type parameter
-        if self.initial_state is None and hasattr(self, "_initial_state_t"):
+        if init_state is None and hasattr(self, "_initial_state_t"):
             state_type = self._initial_state_t
             if isinstance(state_type, type):
                 if issubclass(state_type, FlowState):
@@ -1271,12 +1397,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
                     return cast(T, {"id": str(uuid4())})
 
         # Handle case where no initial state is provided
-        if self.initial_state is None:
+        if init_state is None:
             return cast(T, {"id": str(uuid4())})
 
         # Handle case where initial_state is a type (class)
-        if isinstance(self.initial_state, type):
-            state_class: type[T] = self.initial_state
+        if isinstance(init_state, type):
+            state_class = init_state
             if issubclass(state_class, FlowState):
                 return state_class()
             if issubclass(state_class, BaseModel):
@@ -1287,19 +1413,19 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 if not getattr(model_instance, "id", None):
                     object.__setattr__(model_instance, "id", str(uuid4()))
                 return model_instance
-            if self.initial_state is dict:
+            if init_state is dict:
                 return cast(T, {"id": str(uuid4())})
 
         # Handle dictionary instance case
-        if isinstance(self.initial_state, dict):
-            new_state = dict(self.initial_state)  # Copy to avoid mutations
+        if isinstance(init_state, dict):
+            new_state = dict(init_state)  # Copy to avoid mutations
             if "id" not in new_state:
                 new_state["id"] = str(uuid4())
             return cast(T, new_state)
 
         # Handle BaseModel instance case
-        if isinstance(self.initial_state, BaseModel):
-            model = cast(BaseModel, self.initial_state)
+        if isinstance(init_state, BaseModel):
+            model = cast(BaseModel, init_state)
             if not hasattr(model, "id"):
                 raise ValueError("Flow state model must have an 'id' field")
 
@@ -1698,8 +1824,13 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 self._pending_and_listeners.clear()
                 self._clear_or_listeners()
             else:
-                # We're restoring from persistence, set the flag
-                self._is_execution_resuming = True
+                # Only enter resumption mode if there are completed methods to
+                # replay.  When _completed_methods is empty (e.g. a pure
+                # state-reload via kickoff(inputs={"id": ...})), the flow
+                # executes from scratch and the flag would incorrectly
+                # suppress cyclic re-execution on the second iteration.
+                if self._completed_methods:
+                    self._is_execution_resuming = True
 
             if inputs:
                 # Override the id in the state if it exists in inputs
@@ -1872,6 +2003,9 @@ class Flow(Generic[T], metaclass=FlowMeta):
 
             return final_output
         finally:
+            # Ensure all background memory saves complete before returning
+            if self.memory is not None and hasattr(self.memory, "drain_writes"):
+                self.memory.drain_writes()
             if request_id_token is not None:
                 current_flow_request_id.reset(request_id_token)
             if flow_id_token is not None:
@@ -2014,15 +2148,24 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 if future:
                     self._event_futures.append(future)
 
-            if asyncio.iscoroutinefunction(method):
-                result = await method(*args, **kwargs)
-            else:
-                # Run sync methods in thread pool for isolation
-                # This allows Agent.kickoff() to work synchronously inside Flow methods
-                import contextvars
+            # Set method name in context so ask() can read it without
+            # stack inspection.  Must happen before copy_context() so the
+            # value propagates into the thread pool for sync methods.
+            from crewai.flow.flow_context import current_flow_method_name
 
-                ctx = contextvars.copy_context()
-                result = await asyncio.to_thread(ctx.run, method, *args, **kwargs)
+            method_name_token = current_flow_method_name.set(method_name)
+            try:
+                if asyncio.iscoroutinefunction(method):
+                    result = await method(*args, **kwargs)
+                else:
+                    # Run sync methods in thread pool for isolation
+                    # This allows Agent.kickoff() to work synchronously inside Flow methods
+                    import contextvars
+
+                    ctx = contextvars.copy_context()
+                    result = await asyncio.to_thread(ctx.run, method, *args, **kwargs)
+            finally:
+                current_flow_method_name.reset(method_name_token)
 
             # Auto-await coroutines returned from sync methods (enables AgentExecutor pattern)
             if asyncio.iscoroutine(result):
@@ -2055,6 +2198,8 @@ class Flow(Generic[T], metaclass=FlowMeta):
             from crewai.flow.async_feedback.types import HumanFeedbackPending
 
             if isinstance(e, HumanFeedbackPending):
+                e.context.method_name = method_name
+
                 # Auto-save pending feedback (create default persistence if needed)
                 if self._persistence is None:
                     from crewai.flow.persistence import SQLiteFlowPersistence
@@ -2154,14 +2299,23 @@ class Flow(Generic[T], metaclass=FlowMeta):
                     router_name, router_input, current_triggering_event_id
                 )
                 if router_result:  # Only add non-None results
-                    router_results.append(FlowMethodName(str(router_result)))
+                    router_result_str = (
+                        router_result.value
+                        if isinstance(router_result, enum.Enum)
+                        else str(router_result)
+                    )
+                    router_results.append(FlowMethodName(router_result_str))
                     # If this was a human_feedback router, map the outcome to the feedback
                     if self.last_human_feedback is not None:
-                        router_result_to_feedback[str(router_result)] = (
+                        router_result_to_feedback[router_result_str] = (
                             self.last_human_feedback
                         )
                 current_trigger = (
-                    FlowMethodName(str(router_result))
+                    FlowMethodName(
+                        router_result.value
+                        if isinstance(router_result, enum.Enum)
+                        else str(router_result)
+                    )
                     if router_result is not None
                     else FlowMethodName("")  # Update for next iteration of router chain
                 )
@@ -2428,8 +2582,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 return (None, None)
             # For cyclic flows, clear from completed to allow re-execution
             self._completed_methods.discard(listener_name)
-            # Also clear from fired OR listeners for cyclic flows
-            self._discard_or_listener(listener_name)
+            # Clear ALL fired OR listeners so they can fire again in the new cycle.
+            # This mirrors what _execute_start_method does for start-method cycles.
+            # Only discarding the individual listener is insufficient because
+            # downstream or_() listeners (e.g., method_a listening to
+            # or_(handler_a, handler_b)) would remain suppressed across iterations.
+            self._clear_or_listeners()
 
         try:
             method = self._methods[listener_name]
@@ -2473,6 +2631,206 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 logger.error(f"Error executing listener {listener_name}: {e}")
             raise
 
+    # ── User Input (self.ask) ────────────────────────────────────────
+
+    def _resolve_input_provider(self) -> Any:
+        """Resolve the input provider using the priority chain.
+
+        Resolution order:
+        1. ``self.input_provider`` (per-flow override)
+        2. ``flow_config.input_provider`` (global default)
+        3. ``ConsoleInputProvider()`` (built-in fallback)
+
+        Returns:
+            An object implementing the ``InputProvider`` protocol.
+        """
+        from crewai.flow.async_feedback.providers import ConsoleProvider
+        from crewai.flow.flow_config import flow_config
+
+        if self.input_provider is not None:
+            return self.input_provider
+        if flow_config.input_provider is not None:
+            return flow_config.input_provider
+        return ConsoleProvider()
+
+    def _checkpoint_state_for_ask(self) -> None:
+        """Auto-checkpoint flow state before waiting for user input.
+
+        If persistence is configured, saves the current state so that
+        ``self.state`` is recoverable even if the process crashes while
+        waiting for input.
+
+        This is best-effort: if persistence is not configured, this is a no-op.
+        """
+        if self._persistence is None:
+            return
+        try:
+            state_data = (
+                self._state
+                if isinstance(self._state, dict)
+                else self._state.model_dump()
+            )
+            self._persistence.save_state(
+                flow_uuid=self.flow_id,
+                method_name="_ask_checkpoint",
+                state_data=state_data,
+            )
+        except Exception:
+            logger.debug("Failed to checkpoint state before ask()", exc_info=True)
+
+    def ask(
+        self,
+        message: str,
+        timeout: float | None = None,
+        metadata: dict[str, Any] | None = None,
+    ) -> str | None:
+        """Request input from the user during flow execution.
+
+        Blocks the current thread until the user provides input or the
+        timeout expires. Works in both sync and async flow methods (the
+        flow framework runs sync methods in a thread pool via
+        ``asyncio.to_thread``, so the event loop stays free).
+
+        Timeout ensures flows always terminate. When timeout expires,
+        ``None`` is returned, enabling the pattern::
+
+            while (msg := self.ask("You: ", timeout=300)) is not None:
+                process(msg)
+
+        Before waiting for input, the current ``self.state`` is automatically
+        checkpointed to persistence (if configured) for durability.
+
+        Args:
+            message: The question or prompt to display to the user.
+            timeout: Maximum seconds to wait for input. ``None`` means
+                wait indefinitely. When timeout expires, returns ``None``.
+                Note: timeout is best-effort for the provider call --
+                ``ask()`` returns ``None`` promptly, but the underlying
+                ``request_input()`` may continue running in a background
+                thread until it completes naturally. Network providers
+                should implement their own internal timeouts.
+            metadata: Optional metadata to send to the input provider,
+                such as user ID, channel, session context. The provider
+                can use this to route the question to the right recipient.
+
+        Returns:
+            The user's input as a string, or ``None`` on timeout, disconnect,
+            or provider error. Empty string ``""`` means the user pressed
+            Enter without typing (intentional empty input).
+
+        Example:
+            ```python
+            class MyFlow(Flow):
+                @start()
+                def gather_info(self):
+                    topic = self.ask(
+                        "What topic should we research?",
+                        metadata={"user_id": "u123", "channel": "#research"},
+                    )
+                    if topic is None:
+                        return "No input received"
+                    return topic
+            ```
+        """
+        from concurrent.futures import (
+            ThreadPoolExecutor,
+            TimeoutError as FuturesTimeoutError,
+        )
+        from datetime import datetime
+
+        from crewai.events.types.flow_events import (
+            FlowInputReceivedEvent,
+            FlowInputRequestedEvent,
+        )
+        from crewai.flow.flow_context import current_flow_method_name
+        from crewai.flow.input_provider import InputResponse
+
+        method_name = current_flow_method_name.get("unknown")
+
+        # Emit input requested event
+        crewai_event_bus.emit(
+            self,
+            FlowInputRequestedEvent(
+                type="flow_input_requested",
+                flow_name=self.name or self.__class__.__name__,
+                method_name=method_name,
+                message=message,
+                metadata=metadata,
+            ),
+        )
+
+        # Auto-checkpoint state before waiting
+        self._checkpoint_state_for_ask()
+
+        provider = self._resolve_input_provider()
+        raw: str | InputResponse | None = None
+
+        try:
+            if timeout is not None:
+                # Manual executor management to avoid shutdown(wait=True)
+                # deadlock when the provider call outlives the timeout.
+                executor = ThreadPoolExecutor(max_workers=1)
+                future = executor.submit(
+                    provider.request_input, message, self, metadata
+                )
+                try:
+                    raw = future.result(timeout=timeout)
+                except FuturesTimeoutError:
+                    future.cancel()
+                    raw = None
+                finally:
+                    # wait=False so we don't block if the provider is still
+                    # running (e.g. input() stuck waiting for user).
+                    # cancel_futures=True cleans up any queued-but-not-started tasks.
+                    executor.shutdown(wait=False, cancel_futures=True)
+            else:
+                raw = provider.request_input(message, self, metadata=metadata)
+        except KeyboardInterrupt:
+            raise
+        except Exception:
+            logger.debug("Input provider error in ask()", exc_info=True)
+            raw = None
+
+        # Normalize provider response: str, InputResponse, or None
+        response: str | None = None
+        response_metadata: dict[str, Any] | None = None
+
+        if isinstance(raw, InputResponse):
+            response = raw.text
+            response_metadata = raw.metadata
+        elif isinstance(raw, str):
+            response = raw
+        else:
+            response = None
+
+        # Record in history
+        self._input_history.append(
+            {
+                "message": message,
+                "response": response,
+                "method_name": method_name,
+                "timestamp": datetime.now(),
+                "metadata": metadata,
+                "response_metadata": response_metadata,
+            }
+        )
+
+        # Emit input received event
+        crewai_event_bus.emit(
+            self,
+            FlowInputReceivedEvent(
+                type="flow_input_received",
+                flow_name=self.name or self.__class__.__name__,
+                method_name=method_name,
+                message=message,
+                response=response,
+                metadata=metadata,
+                response_metadata=response_metadata,
+            ),
+        )
+
+        return response
+
     def _request_human_feedback(
         self,
         message: str,

lib/crewai/src/crewai/flow/flow_config.py

@@ -11,6 +11,7 @@ from typing import TYPE_CHECKING, Any
 
 if TYPE_CHECKING:
     from crewai.flow.async_feedback.types import HumanFeedbackProvider
+    from crewai.flow.input_provider import InputProvider
 
 
 class FlowConfig:
@@ -20,10 +21,15 @@ class FlowConfig:
         hitl_provider: The human-in-the-loop feedback provider.
                        Defaults to None (uses console input).
                        Can be overridden by deployments at startup.
+        input_provider: The input provider used by ``Flow.ask()``.
+                        Defaults to None (uses ``ConsoleProvider``).
+                        Can be overridden by
+                        deployments at startup.
     """
 
     def __init__(self) -> None:
         self._hitl_provider: HumanFeedbackProvider | None = None
+        self._input_provider: InputProvider | None = None
 
     @property
     def hitl_provider(self) -> Any:
@@ -35,6 +41,32 @@ class FlowConfig:
         """Set the HITL provider."""
         self._hitl_provider = provider
 
+    @property
+    def input_provider(self) -> Any:
+        """Get the configured input provider for ``Flow.ask()``.
+
+        Returns:
+            The configured InputProvider instance, or None if not set
+            (in which case ``ConsoleInputProvider`` is used as default).
+        """
+        return self._input_provider
+
+    @input_provider.setter
+    def input_provider(self, provider: Any) -> None:
+        """Set the input provider for ``Flow.ask()``.
+
+        Args:
+            provider: An object implementing the ``InputProvider`` protocol.
+
+        Example:
+            ```python
+            from crewai.flow import flow_config
+
+            flow_config.input_provider = WebSocketInputProvider(...)
+            ```
+        """
+        self._input_provider = provider
+
 
 # Singleton instance
 flow_config = FlowConfig()

lib/crewai/src/crewai/flow/flow_context.py

@@ -14,3 +14,7 @@ current_flow_request_id: contextvars.ContextVar[str | None] = contextvars.Contex
 current_flow_id: contextvars.ContextVar[str | None] = contextvars.ContextVar(
     "flow_id", default=None
 )
+
+current_flow_method_name: contextvars.ContextVar[str] = contextvars.ContextVar(
+    "flow_method_name", default="unknown"
+)

lib/crewai/src/crewai/flow/human_feedback.py

@@ -62,6 +62,8 @@ from datetime import datetime
 from functools import wraps
 from typing import TYPE_CHECKING, Any, TypeVar
 
+from pydantic import BaseModel, Field
+
 from crewai.flow.flow_wrappers import FlowMethod
 
 
@@ -132,10 +134,12 @@ class HumanFeedbackConfig:
 
     message: str
     emit: Sequence[str] | None = None
-    llm: str | BaseLLM | None = None
+    llm: str | BaseLLM | None = "gpt-4o-mini"
     default_outcome: str | None = None
     metadata: dict[str, Any] | None = None
     provider: HumanFeedbackProvider | None = None
+    learn: bool = False
+    learn_source: str = "hitl"
 
 
 class HumanFeedbackMethod(FlowMethod[Any, Any]):
@@ -155,13 +159,36 @@ class HumanFeedbackMethod(FlowMethod[Any, Any]):
     __human_feedback_config__: HumanFeedbackConfig | None = None
 
 
+class PreReviewResult(BaseModel):
+    """Structured output from the HITL pre-review LLM call."""
+
+    improved_output: str = Field(
+        description="The improved version of the output with past human feedback lessons applied.",
+    )
+
+
+class DistilledLessons(BaseModel):
+    """Structured output from the HITL lesson distillation LLM call."""
+
+    lessons: list[str] = Field(
+        default_factory=list,
+        description=(
+            "Generalizable lessons extracted from the human feedback. "
+            "Each lesson should be a reusable rule or preference. "
+            "Return an empty list if the feedback contains no generalizable guidance."
+        ),
+    )
+
+
 def human_feedback(
     message: str,
     emit: Sequence[str] | None = None,
-    llm: str | BaseLLM | None = None,
+    llm: str | BaseLLM | None = "gpt-4o-mini",
     default_outcome: str | None = None,
     metadata: dict[str, Any] | None = None,
     provider: HumanFeedbackProvider | None = None,
+    learn: bool = False,
+    learn_source: str = "hitl"
 ) -> Callable[[F], F]:
     """Decorator for Flow methods that require human feedback.
 
@@ -256,7 +283,9 @@ def human_feedback(
         if not llm:
             raise ValueError(
                 "llm is required when emit is specified. "
-                "Provide an LLM model string (e.g., 'gpt-4o-mini') or a BaseLLM instance."
+                "Provide an LLM model string (e.g., 'gpt-4o-mini') or a BaseLLM instance. "
+                "See the CrewAI Human-in-the-Loop (HITL) documentation for more information: "
+                "https://docs.crewai.com/en/learn/human-feedback-in-flows"
             )
         if default_outcome is not None and default_outcome not in emit:
             raise ValueError(
@@ -269,6 +298,101 @@ def human_feedback(
     def decorator(func: F) -> F:
         """Inner decorator that wraps the function."""
 
+        # -- HITL learning helpers (only used when learn=True) --------
+
+        def _get_hitl_prompt(key: str) -> str:
+            """Read a HITL prompt from the i18n translations."""
+            from crewai.utilities.i18n import get_i18n
+
+            return get_i18n().slice(key)
+
+        def _resolve_llm_instance() -> Any:
+            """Resolve the ``llm`` parameter to a BaseLLM instance.
+
+            Uses the SAME model specified in the decorator so pre-review,
+            distillation, and outcome collapsing all share one model.
+            """
+            if llm is None:
+                from crewai.llm import LLM
+
+                return LLM(model="gpt-4o-mini")
+            if isinstance(llm, str):
+                from crewai.llm import LLM
+
+                return LLM(model=llm)
+            return llm  # already a BaseLLM instance
+
+        def _pre_review_with_lessons(
+            flow_instance: Flow[Any], method_output: Any
+        ) -> Any:
+            """Recall past HITL lessons and use LLM to pre-review the output."""
+            try:
+                query = f"human feedback lessons for {func.__name__}: {method_output!s}"
+                matches = flow_instance.memory.recall(
+                    query, source=learn_source
+                )
+                if not matches:
+                    return method_output
+
+                lessons = "\n".join(f"- {m.record.content}" for m in matches)
+                llm_inst = _resolve_llm_instance()
+                prompt = _get_hitl_prompt("hitl_pre_review_user").format(
+                    output=str(method_output),
+                    lessons=lessons,
+                )
+                messages = [
+                    {"role": "system", "content": _get_hitl_prompt("hitl_pre_review_system")},
+                    {"role": "user", "content": prompt},
+                ]
+                if getattr(llm_inst, "supports_function_calling", lambda: False)():
+                    response = llm_inst.call(messages, response_model=PreReviewResult)
+                    if isinstance(response, PreReviewResult):
+                        return response.improved_output
+                    return PreReviewResult.model_validate(response).improved_output
+                reviewed = llm_inst.call(messages)
+                return reviewed if isinstance(reviewed, str) else str(reviewed)
+            except Exception:
+                return method_output  # fallback to raw output on any failure
+
+        def _distill_and_store_lessons(
+            flow_instance: Flow[Any], method_output: Any, raw_feedback: str
+        ) -> None:
+            """Extract generalizable lessons from output + feedback, store in memory."""
+            try:
+                llm_inst = _resolve_llm_instance()
+                prompt = _get_hitl_prompt("hitl_distill_user").format(
+                    method_name=func.__name__,
+                    output=str(method_output),
+                    feedback=raw_feedback,
+                )
+                messages = [
+                    {"role": "system", "content": _get_hitl_prompt("hitl_distill_system")},
+                    {"role": "user", "content": prompt},
+                ]
+
+                lessons: list[str] = []
+                if getattr(llm_inst, "supports_function_calling", lambda: False)():
+                    response = llm_inst.call(messages, response_model=DistilledLessons)
+                    if isinstance(response, DistilledLessons):
+                        lessons = response.lessons
+                    else:
+                        lessons = DistilledLessons.model_validate(response).lessons
+                else:
+                    response = llm_inst.call(messages)
+                    if isinstance(response, str):
+                        lessons = [
+                            line.strip("- ").strip()
+                            for line in response.strip().split("\n")
+                            if line.strip() and line.strip() != "NONE"
+                        ]
+
+                if lessons:
+                    flow_instance.memory.remember_many(lessons, source=learn_source)
+            except Exception:  # noqa: S110
+                pass  # non-critical: don't fail the flow because lesson storage failed
+
+        # -- Core feedback helpers ------------------------------------
+
         def _request_feedback(flow_instance: Flow[Any], method_output: Any) -> str:
             """Request feedback using provider or default console."""
             from crewai.flow.async_feedback.types import PendingFeedbackContext
@@ -353,28 +477,40 @@ def human_feedback(
             # Async wrapper
             @wraps(func)
             async def async_wrapper(self: Flow[Any], *args: Any, **kwargs: Any) -> Any:
-                # Execute the original method
                 method_output = await func(self, *args, **kwargs)
 
-                # Request human feedback (may raise HumanFeedbackPending)
-                raw_feedback = _request_feedback(self, method_output)
+                # Pre-review: apply past HITL lessons before human sees it
+                if learn and getattr(self, "memory", None) is not None:
+                    method_output = _pre_review_with_lessons(self, method_output)
 
-                # Process and return
-                return _process_feedback(self, method_output, raw_feedback)
+                raw_feedback = _request_feedback(self, method_output)
+                result = _process_feedback(self, method_output, raw_feedback)
+
+                # Distill: extract lessons from output + feedback, store in memory
+                if learn and getattr(self, "memory", None) is not None and raw_feedback.strip():
+                    _distill_and_store_lessons(self, method_output, raw_feedback)
+
+                return result
 
             wrapper: Any = async_wrapper
         else:
             # Sync wrapper
             @wraps(func)
             def sync_wrapper(self: Flow[Any], *args: Any, **kwargs: Any) -> Any:
-                # Execute the original method
                 method_output = func(self, *args, **kwargs)
 
-                # Request human feedback (may raise HumanFeedbackPending)
-                raw_feedback = _request_feedback(self, method_output)
+                # Pre-review: apply past HITL lessons before human sees it
+                if learn and getattr(self, "memory", None) is not None:
+                    method_output = _pre_review_with_lessons(self, method_output)
 
-                # Process and return
-                return _process_feedback(self, method_output, raw_feedback)
+                raw_feedback = _request_feedback(self, method_output)
+                result = _process_feedback(self, method_output, raw_feedback)
+
+                # Distill: extract lessons from output + feedback, store in memory
+                if learn and getattr(self, "memory", None) is not None and raw_feedback.strip():
+                    _distill_and_store_lessons(self, method_output, raw_feedback)
+
+                return result
 
             wrapper = sync_wrapper
 
@@ -397,6 +533,8 @@ def human_feedback(
             default_outcome=default_outcome,
             metadata=metadata,
             provider=provider,
+            learn=learn,
+            learn_source=learn_source
         )
         wrapper.__is_flow_method__ = True
 

lib/crewai/src/crewai/flow/input_provider.py

@@ -0,0 +1,151 @@
+"""Input provider protocol for Flow.ask().
+
+This module provides the InputProvider protocol and InputResponse dataclass
+used by Flow.ask() to request input from users during flow execution.
+
+The default implementation is ``ConsoleProvider`` (from
+``crewai.flow.async_feedback.providers``), which serves both feedback
+and input collection via console.
+
+Example (default console input):
+    ```python
+    from crewai.flow import Flow, start
+
+
+    class MyFlow(Flow):
+        @start()
+        def gather_info(self):
+            topic = self.ask("What topic should we research?")
+            return topic
+    ```
+
+Example (custom provider with metadata):
+    ```python
+    from crewai.flow import Flow, start
+    from crewai.flow.input_provider import InputProvider, InputResponse
+
+
+    class SlackProvider:
+        def request_input(self, message, flow, metadata=None):
+            channel = metadata.get("channel", "#general") if metadata else "#general"
+            thread = self.post_question(channel, message)
+            reply = self.wait_for_reply(thread)
+            return InputResponse(
+                text=reply.text,
+                metadata={"responded_by": reply.user_id, "thread_id": thread.id},
+            )
+
+
+    class MyFlow(Flow):
+        input_provider = SlackProvider()
+
+        @start()
+        def gather_info(self):
+            topic = self.ask("What topic?", metadata={"channel": "#research"})
+            return topic
+    ```
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import TYPE_CHECKING, Any, Protocol, runtime_checkable
+
+
+if TYPE_CHECKING:
+    from crewai.flow.flow import Flow
+
+
+@dataclass
+class InputResponse:
+    """Response from an InputProvider, optionally carrying metadata.
+
+    Simple providers can just return a string from ``request_input()``.
+    Providers that need to send metadata back (e.g., who responded,
+    thread ID, external timestamps) return an ``InputResponse`` instead.
+
+    ``ask()`` normalizes both cases -- callers always get ``str | None``.
+    The response metadata is stored in ``_input_history`` and emitted
+    in ``FlowInputReceivedEvent``.
+
+    Attributes:
+        text: The user's input text, or None if unavailable.
+        metadata: Optional metadata from the provider about the response
+            (e.g., who responded, thread ID, timestamps).
+
+    Example:
+        ```python
+        class MyProvider:
+            def request_input(self, message, flow, metadata=None):
+                response = get_response_from_external_system(message)
+                return InputResponse(
+                    text=response.text,
+                    metadata={"responded_by": response.user_id},
+                )
+        ```
+    """
+
+    text: str | None
+    metadata: dict[str, Any] | None = field(default=None)
+
+
+@runtime_checkable
+class InputProvider(Protocol):
+    """Protocol for user input collection strategies.
+
+    Implement this protocol to create custom input providers that integrate
+    with external systems like websockets, web UIs, Slack, or custom APIs.
+
+    The default provider is ``ConsoleProvider``, which blocks waiting for
+    console input via Python's built-in ``input()`` function.
+
+    Providers are always synchronous. The flow framework runs sync methods
+    in a thread pool (via ``asyncio.to_thread``), so ``ask()`` never blocks
+    the event loop even inside async flow methods.
+
+    Providers can return either:
+    - ``str | None`` for simple cases (no response metadata)
+    - ``InputResponse`` when they need to send metadata back with the answer
+
+    Example (simple):
+        ```python
+        class SimpleProvider:
+            def request_input(self, message: str, flow: Flow) -> str | None:
+                return input(message)
+        ```
+
+    Example (with metadata):
+        ```python
+        class SlackProvider:
+            def request_input(self, message, flow, metadata=None):
+                channel = metadata.get("channel") if metadata else "#general"
+                reply = self.post_and_wait(channel, message)
+                return InputResponse(
+                    text=reply.text,
+                    metadata={"responded_by": reply.user_id},
+                )
+        ```
+    """
+
+    def request_input(
+        self,
+        message: str,
+        flow: Flow[Any],
+        metadata: dict[str, Any] | None = None,
+    ) -> str | InputResponse | None:
+        """Request input from the user.
+
+        Args:
+            message: The question or prompt to display to the user.
+            flow: The Flow instance requesting input. Can be used to
+                access flow state, name, or other context.
+            metadata: Optional metadata from the caller, such as user ID,
+                channel, session context, etc. Providers can use this to
+                route the question to the right recipient.
+
+        Returns:
+            The user's input as a string, an ``InputResponse`` with text
+            and optional response metadata, or None if input is unavailable
+            (e.g., user cancelled, connection dropped).
+        """
+        ...

lib/crewai/src/crewai/flow/types.py

@@ -4,6 +4,7 @@ This module contains TypedDict definitions and type aliases used throughout
 the Flow system.
 """
 
+from datetime import datetime
 from typing import (
     Annotated,
     Any,
@@ -101,6 +102,30 @@ class FlowData(TypedDict):
     flow_methods_attributes: list[FlowMethodData]
 
 
+class InputHistoryEntry(TypedDict):
+    """A single entry in the flow's input history from ``self.ask()``.
+
+    Each call to ``Flow.ask()`` appends one entry recording the question,
+    the user's response, which method asked, and any metadata exchanged
+    between the caller and the input provider.
+
+    Attributes:
+        message: The question or prompt that was displayed to the user.
+        response: The user's response, or None on timeout/error.
+        method_name: The flow method that called ``ask()``.
+        timestamp: When the input was received.
+        metadata: Metadata sent with the question (caller to provider).
+        response_metadata: Metadata received with the answer (provider to caller).
+    """
+
+    message: str
+    response: str | None
+    method_name: str
+    timestamp: datetime
+    metadata: dict[str, Any] | None
+    response_metadata: dict[str, Any] | None
+
+
 class FlowExecutionData(TypedDict):
     """Flow execution data.
 

lib/crewai/src/crewai/lite_agent.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import asyncio
 from collections.abc import Callable
+import time
 from functools import wraps
 import inspect
 import json
@@ -48,6 +49,11 @@ from crewai.events.types.agent_events import (
     LiteAgentExecutionErrorEvent,
     LiteAgentExecutionStartedEvent,
 )
+from crewai.events.types.memory_events import (
+    MemoryRetrievalCompletedEvent,
+    MemoryRetrievalFailedEvent,
+    MemoryRetrievalStartedEvent,
+)
 from crewai.events.types.logging_events import AgentLogsExecutionEvent
 from crewai.flow.flow_trackable import FlowTrackable
 from crewai.hooks.llm_hooks import get_after_llm_call_hooks, get_before_llm_call_hooks
@@ -244,6 +250,10 @@ class LiteAgent(FlowTrackable, BaseModel):
         description="A2A (Agent-to-Agent) configuration for delegating tasks to remote agents. "
         "Can be a single A2AConfig/A2AClientConfig/A2AServerConfig, or a list of configurations.",
     )
+    memory: bool | Any | None = Field(
+        default=None,
+        description="If True, use default Memory(). If Memory/MemoryScope/MemorySlice, use it for recall and remember.",
+    )
     tools_results: list[dict[str, Any]] = Field(
         default_factory=list, description="Results of the tools used by the agent."
     )
@@ -266,6 +276,7 @@ class LiteAgent(FlowTrackable, BaseModel):
     _after_llm_call_hooks: list[AfterLLMCallHookType] = PrivateAttr(
         default_factory=get_after_llm_call_hooks
     )
+    _memory: Any = PrivateAttr(default=None)
 
     @model_validator(mode="after")
     def emit_deprecation_warning(self) -> Self:
@@ -363,6 +374,19 @@ class LiteAgent(FlowTrackable, BaseModel):
 
         return self
 
+    @model_validator(mode="after")
+    def resolve_memory(self) -> Self:
+        """Resolve memory field to _memory: default Memory() when True, else user instance or None."""
+        if self.memory is True:
+            from crewai.memory.unified_memory import Memory
+
+            object.__setattr__(self, "_memory", Memory())
+        elif self.memory is not None and self.memory is not False:
+            object.__setattr__(self, "_memory", self.memory)
+        else:
+            object.__setattr__(self, "_memory", None)
+        return self
+
     @field_validator("guardrail", mode="before")
     @classmethod
     def validate_guardrail_function(
@@ -455,6 +479,19 @@ class LiteAgent(FlowTrackable, BaseModel):
         Returns:
             LiteAgentOutput: The result of the agent execution.
         """
+        # Inject memory tools once if memory is configured (mirrors Agent._prepare_kickoff)
+        if self._memory is not None:
+            from crewai.tools.memory_tools import create_memory_tools
+            from crewai.utilities.agent_utils import sanitize_tool_name
+
+            existing_names = {sanitize_tool_name(t.name) for t in self._parsed_tools}
+            memory_tools = [
+                mt for mt in create_memory_tools(self._memory)
+                if sanitize_tool_name(mt.name) not in existing_names
+            ]
+            if memory_tools:
+                self._parsed_tools = self._parsed_tools + parse_tools(memory_tools)
+
         # Create agent info for event emission
         agent_info = {
             "id": self.id,
@@ -474,6 +511,7 @@ class LiteAgent(FlowTrackable, BaseModel):
             self._messages = self._format_messages(
                 messages, response_format=response_format, input_files=input_files
             )
+            self._inject_memory_context()
 
             return self._execute_core(
                 agent_info=agent_info, response_format=response_format
@@ -496,6 +534,80 @@ class LiteAgent(FlowTrackable, BaseModel):
             )
             raise e
 
+    def _get_last_user_content(self) -> str:
+        """Get the last user message content from _messages for recall/input."""
+        for msg in reversed(self._messages):
+            if msg.get("role") == "user":
+                content = msg.get("content")
+                return content if isinstance(content, str) else ""
+        return ""
+
+    def _inject_memory_context(self) -> None:
+        """Recall relevant memories and append to the system message. No-op if _memory is None."""
+        if self._memory is None:
+            return
+        query = self._get_last_user_content()
+        crewai_event_bus.emit(
+            self,
+            event=MemoryRetrievalStartedEvent(
+                task_id=None,
+                source_type="lite_agent",
+            ),
+        )
+        start_time = time.time()
+        memory_block = ""
+        try:
+            matches = self._memory.recall(query, limit=10)
+            if matches:
+                memory_block = "Relevant memories:\n" + "\n".join(
+                    f"- {m.record.content}" for m in matches
+                )
+            if memory_block:
+                formatted = self.i18n.slice("memory").format(memory=memory_block)
+                if self._messages and self._messages[0].get("role") == "system":
+                    self._messages[0]["content"] = (
+                        self._messages[0].get("content", "") + "\n\n" + formatted
+                    )
+            crewai_event_bus.emit(
+                self,
+                event=MemoryRetrievalCompletedEvent(
+                    task_id=None,
+                    memory_content=memory_block,
+                    retrieval_time_ms=(time.time() - start_time) * 1000,
+                    source_type="lite_agent",
+                ),
+            )
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                event=MemoryRetrievalFailedEvent(
+                    task_id=None,
+                    source_type="lite_agent",
+                    error=str(e),
+                ),
+            )
+
+    def _save_to_memory(self, output_text: str) -> None:
+        """Extract discrete memories from the run and remember each. No-op if _memory is None."""
+        if self._memory is None:
+            return
+        input_str = self._get_last_user_content() or "User request"
+        try:
+            raw = (
+                f"Input: {input_str}\n"
+                f"Agent: {self.role}\n"
+                f"Result: {output_text}"
+            )
+            extracted = self._memory.extract_memories(raw)
+            if extracted:
+                self._memory.remember_many(extracted, agent_role=self.role)
+        except Exception as e:
+            if self.verbose:
+                self._printer.print(
+                    content=f"Failed to save to memory: {e}",
+                    color="yellow",
+                )
+
     def _execute_core(
         self, agent_info: dict[str, Any], response_format: type[BaseModel] | None = None
     ) -> LiteAgentOutput:
@@ -511,6 +623,8 @@ class LiteAgent(FlowTrackable, BaseModel):
 
         # Execute the agent using invoke loop
         agent_finish = self._invoke_loop()
+        if self._memory is not None:
+            self._save_to_memory(agent_finish.output)
         formatted_result: BaseModel | None = None
 
         active_response_format = response_format or self.response_format

lib/crewai/src/crewai/llm.py

@@ -419,8 +419,22 @@ class LLM(BaseLLM):
 
         # FALLBACK to LiteLLM
         if not LITELLM_AVAILABLE:
-            logger.error("LiteLLM is not available, falling back to LiteLLM")
-            raise ImportError("Fallback to LiteLLM is not available") from None
+            native_list = ", ".join(SUPPORTED_NATIVE_PROVIDERS)
+            error_msg = (
+                f"Unable to initialize LLM with model '{model}'. "
+                f"The model did not match any supported native provider "
+                f"({native_list}), and the LiteLLM fallback package is not "
+                f"installed.\n\n"
+                f"To fix this, either:\n"
+                f"  1. Install LiteLLM for broad model support: "
+                f"uv add litellm\n"
+                f"or\n"
+                f"pip install litellm\n\n"
+                f"For more details, see: "
+                f"https://docs.crewai.com/en/learn/llm-connections"
+            )
+            logger.error(error_msg)
+            raise ImportError(error_msg) from None
 
         instance = object.__new__(cls)
         super(LLM, instance).__init__(model=model, is_litellm=True, **kwargs)

lib/crewai/src/crewai/llms/providers/anthropic/completion.py

@@ -1580,10 +1580,12 @@ class AnthropicCompletion(BaseLLM):
             usage = response.usage
             input_tokens = getattr(usage, "input_tokens", 0)
             output_tokens = getattr(usage, "output_tokens", 0)
+            cache_read_tokens = getattr(usage, "cache_read_input_tokens", 0) or 0
             return {
                 "input_tokens": input_tokens,
                 "output_tokens": output_tokens,
                 "total_tokens": input_tokens + output_tokens,
+                "cached_prompt_tokens": cache_read_tokens,
             }
         return {"total_tokens": 0}