docs: remove --public flag references (public tools no longer supported)

Remove all references to --public visibility flag since public tools
have been removed from the platform (crewai-plus#2380, ENG-1453).
Tools are now organization-scoped (private) by default.

Co-authored-by: Diego Nogues <diego@crewai.com>

docs/en/guides/tools/platform-tools-cli.mdx

@@ -0,0 +1,131 @@
+---
+title: Platform Tools CLI
+description: Create, publish, and install custom tools on the CrewAI platform using the CLI.
+icon: terminal
+mode: "wide"
+---
+
+## Overview
+
+The CrewAI CLI provides commands to manage custom tools on the **CrewAI platform** — a hosted tool registry that lets you share tools within your organization without publishing to PyPI.
+
+| Command | Purpose |
+|---------|---------|
+| `crewai tool create <handle>` | Scaffold a new tool project |
+| `crewai tool publish` | Publish the tool to the CrewAI platform |
+| `crewai tool install <handle>` | Install a platform tool into your crew project |
+
+<Note type="info" title="Platform vs PyPI">
+  These commands manage tools on the **CrewAI platform registry**. If you want to publish a standalone Python package to PyPI instead, see the [Publish Custom Tools to PyPI](/en/guides/tools/publish-custom-tools) guide.
+</Note>
+
+## Prerequisites
+
+- **CrewAI CLI** installed (`pip install crewai`)
+- **Authenticated** with the platform — run `crewai login` first
+
+---
+
+## Step 1: Create a Tool Project
+
+Scaffold a new tool project:
+
+```bash
+crewai tool create my_custom_tool
+```
+
+This generates a project structure with the boilerplate you need to start building your tool.
+
+<Tip>
+  The `handle` is the unique identifier for your tool on the platform. Choose something descriptive and specific to what the tool does.
+</Tip>
+
+### Implement Your Tool
+
+Edit the generated tool file to add your logic. The tool follows the standard CrewAI tools contract — you can subclass `BaseTool` or use the `@tool` decorator:
+
+```python
+from crewai.tools import BaseTool
+
+class MyCustomTool(BaseTool):
+    name: str = "My Custom Tool"
+    description: str = "Description of what this tool does — be specific so agents know when to use it."
+
+    def _run(self, argument: str) -> str:
+        # Your tool logic here
+        return "result"
+```
+
+For the full tools API reference (input schemas, caching, async support, error handling), see the [Create Custom Tools](/en/learn/create-custom-tools) guide.
+
+---
+
+## Step 2: Publish to the Platform
+
+From your tool project directory, publish it to the CrewAI platform:
+
+```bash
+crewai tool publish
+```
+
+### Options
+
+| Flag | Description |
+|------|-------------|
+| `--force` | Bypass Git remote validations |
+
+Tools are published privately to your organization by default.
+
+---
+
+## Step 3: Install a Platform Tool
+
+To install a tool that's been published to the platform:
+
+```bash
+crewai tool install my_custom_tool
+```
+
+Once installed, you can use the tool in your crew like any other tool — assign it to an agent via the `tools` parameter.
+
+---
+
+## Full Lifecycle Example
+
+```bash
+# 1. Authenticate with the platform
+crewai login
+
+# 2. Scaffold a new tool
+crewai tool create weather_lookup
+
+# 3. Implement your logic in the generated project
+cd weather_lookup
+# ... edit the tool file ...
+
+# 4. Publish to the platform
+crewai tool publish
+
+# 5. In another project, install and use it
+crewai tool install weather_lookup
+```
+
+---
+
+## Platform Tools vs PyPI Packages
+
+| | Platform Tools | PyPI Packages |
+|---|---|---|
+| **Publish** | `crewai tool publish` | `uv build` + `uv publish` |
+| **Registry** | CrewAI platform | PyPI |
+| **Install** | `crewai tool install <handle>` | `pip install <package>` |
+| **Auth** | `crewai login` | PyPI account + token |
+| **Visibility** | Organization-scoped (private) | Always public |
+| **Guide** | This page | [Publish Custom Tools](/en/guides/tools/publish-custom-tools) |
+
+---
+
+## Related
+
+- [Create Custom Tools](/en/learn/create-custom-tools) — Python API reference for building tools (BaseTool, @tool decorator)
+- [Publish Custom Tools to PyPI](/en/guides/tools/publish-custom-tools) — package and distribute tools as standalone Python libraries

docs/en/learn/create-custom-tools.mdx

@@ -12,7 +12,9 @@ incorporating the latest functionalities such as tool delegation, error handling
 enabling agents to perform a wide range of actions.
 
 <Tip>
-  **Want to publish your tool for the community?** If you're building a tool that others could benefit from, check out the [Publish Custom Tools](/en/guides/tools/publish-custom-tools) guide to learn how to package and distribute your tool on PyPI.
+  **Want to publish your tool to the CrewAI platform?** Use the CLI to scaffold, publish, and share tools directly on the platform — see the [Platform Tools CLI](/en/guides/tools/platform-tools-cli) guide.
+
+  **Prefer publishing to PyPI?** Check out the [Publish Custom Tools](/en/guides/tools/publish-custom-tools) guide to package and distribute your tool as a standalone Python library.
 </Tip>
 
 ### Subclassing `BaseTool`

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

@@ -220,11 +220,7 @@ class Agent(BaseAgent):
         str | BaseLLM | None,
         BeforeValidator(_validate_llm_ref),
         PlainSerializer(_serialize_llm_ref, return_type=dict | None, when_used="json"),
-    ] = Field(
-        description="Language model that will run the agent.",
-        default=None,
-        deprecated="function_calling_llm is deprecated and will be removed in a future release.",
-    )
+    ] = Field(description="Language model that will run the agent.", default=None)
     system_template: str | None = Field(
         default=None, description="System format for the agent."
     )

lib/crewai/src/crewai/agents/agent_adapters/langgraph/langgraph_adapter.py

@@ -51,10 +51,7 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
     _graph: Any = PrivateAttr(default=None)
     _memory: Any = PrivateAttr(default=None)
     _max_iterations: int = PrivateAttr(default=10)
-    function_calling_llm: Any = Field(
-        default=None,
-        deprecated="function_calling_llm is deprecated and will be removed in a future release.",
-    )
+    function_calling_llm: Any = Field(default=None)
     step_callback: SerializableCallable | None = Field(default=None)
 
     model: str = Field(default="gpt-4o")

lib/crewai/src/crewai/agents/agent_adapters/openai_agents/openai_adapter.py

@@ -60,10 +60,7 @@ class OpenAIAgentAdapter(BaseAgentAdapter):
     _openai_agent: OpenAIAgentProtocol = PrivateAttr()
     _logger: Logger = PrivateAttr(default_factory=Logger)
     _active_thread: str | None = PrivateAttr(default=None)
-    function_calling_llm: Any = Field(
-        default=None,
-        deprecated="function_calling_llm is deprecated and will be removed in a future release.",
-    )
+    function_calling_llm: Any = Field(default=None)
     step_callback: Any = Field(default=None)
     _tool_adapter: OpenAIAgentToolAdapter = PrivateAttr()
     _converter_adapter: OpenAIConverterAdapter = PrivateAttr()

lib/crewai/src/crewai/crew.py

@@ -251,11 +251,7 @@ class Crew(FlowTrackable, BaseModel):
         str | LLM | None,
         BeforeValidator(_validate_llm_ref),
         PlainSerializer(_serialize_llm_ref, return_type=dict | None, when_used="json"),
-    ] = Field(
-        description="Language model that will run the agent.",
-        default=None,
-        deprecated="function_calling_llm is deprecated and will be removed in a future release.",
-    )
+    ] = Field(description="Language model that will run the agent.", default=None)
     config: Json[dict[str, Any]] | dict[str, Any] | None = Field(default=None)
     id: UUID4 = Field(default_factory=uuid.uuid4, frozen=True)
     share_crew: bool | None = Field(default=False)

lib/crewai/src/crewai/llm.py

@@ -940,21 +940,6 @@ class LLM(BaseLLM):
                 self._track_token_usage_internal(usage_info)
             self._handle_streaming_callbacks(callbacks, usage_info, last_chunk)
 
-            if accumulated_tool_args and not available_functions:
-                tool_calls_list: list[ChatCompletionDeltaToolCall] = [
-                    ChatCompletionDeltaToolCall(
-                        index=idx,
-                        function=Function(
-                            name=tool_arg.function.name,
-                            arguments=tool_arg.function.arguments,
-                        ),
-                    )
-                    for idx, tool_arg in sorted(accumulated_tool_args.items())
-                    if tool_arg.function.name
-                ]
-                if tool_calls_list:
-                    return tool_calls_list
-
             if not tool_calls or not available_functions:
                 if response_model and self.is_litellm:
                     instructor_instance = InternalInstructor(
@@ -1550,7 +1535,8 @@ class LLM(BaseLLM):
             if usage_info:
                 self._track_token_usage_internal(usage_info)
 
-            if accumulated_tool_args:
+            if accumulated_tool_args and available_functions:
+                # Convert accumulated tool args to ChatCompletionDeltaToolCall objects
                 tool_calls_list: list[ChatCompletionDeltaToolCall] = [
                     ChatCompletionDeltaToolCall(
                         index=idx,
@@ -1559,24 +1545,21 @@ class LLM(BaseLLM):
                             arguments=tool_arg.function.arguments,
                         ),
                     )
-                    for idx, tool_arg in sorted(accumulated_tool_args.items())
+                    for idx, tool_arg in accumulated_tool_args.items()
                     if tool_arg.function.name
                 ]
 
                 if tool_calls_list:
-                    if available_functions:
-                        result = self._handle_streaming_tool_calls(
-                            tool_calls=tool_calls_list,
-                            accumulated_tool_args=accumulated_tool_args,
-                            available_functions=available_functions,
-                            from_task=from_task,
-                            from_agent=from_agent,
-                            response_id=response_id,
-                        )
-                        if result is not None:
-                            return result
-                    else:
-                        return tool_calls_list
+                    result = self._handle_streaming_tool_calls(
+                        tool_calls=tool_calls_list,
+                        accumulated_tool_args=accumulated_tool_args,
+                        available_functions=available_functions,
+                        from_task=from_task,
+                        from_agent=from_agent,
+                        response_id=response_id,
+                    )
+                    if result is not None:
+                        return result
 
             usage_dict = self._usage_to_dict(usage_info)
             self._handle_emit_call_events(

lib/crewai/tests/test_llm.py

@@ -624,15 +624,12 @@ def test_handle_streaming_tool_calls_no_available_functions(
         ],
         tools=[get_weather_tool_schema],
     )
-    assert isinstance(response, list)
-    assert len(response) == 1
-    assert response[0].function.name == "get_weather"
-    assert response[0].function.arguments == '{"location":"New York, NY"}'
+    assert response == ""
 
     assert_event_count(
         mock_emit=mock_emit,
         expected_stream_chunk=9,
-        expected_completed_llm_call=0,
+        expected_completed_llm_call=1,
         expected_final_chunk_result='{"location":"New York, NY"}',
     )
 

pyproject.toml

@@ -185,7 +185,7 @@ exclude-newer = "3 days"
 # python-multipart <0.0.27 has GHSA-pp6c-gr5w-3c5g (DoS via unbounded multipart headers).
 # gitpython <3.1.50 has GHSA-mv93-w799-cj2w (config_writer newline injection bypassing the 3.1.49 patch -> RCE via core.hooksPath).
 # urllib3 <2.7.0 has GHSA-qccp-gfcp-xxvc (ProxyManager cross-origin redirect leaks Authorization/Cookie) and GHSA-mf9v-mfxr-j63j (streaming decompression-bomb bypass); force 2.7.0+.
-# langsmith <0.8.0 has GHSA-3644-q5cj-c5c7 (public prompt manifest deserialization, SSRF/secret disclosure); force 0.8.0+.
+# langsmith <0.7.31 has GHSA-rr7j-v2q5-chgv (streaming token redaction bypass); force 0.7.31+.
 # authlib <1.6.11 has GHSA-jj8c-mmj3-mmgv (CSRF bypass in cache-based state storage).
 # litellm 1.83.8+ hard-pins openai==2.24.0, missing openai.types.responses used by crewai;
 # override to >=2.30.0 (the version litellm 1.83.7 used) until upstream relaxes the pin.
@@ -203,7 +203,7 @@ override-dependencies = [
     "uv>=0.11.6,<1",
     "python-multipart>=0.0.27,<1",
     "gitpython>=3.1.50,<4",
-    "langsmith>=0.8.0,<1",
+    "langsmith>=0.7.31,<0.8",
     "authlib>=1.6.11",
 ]
 

uv.lock

@@ -13,7 +13,7 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-05-12T13:27:48.906744Z"
+exclude-newer = "2026-05-08T16:33:02.834109Z"
 exclude-newer-span = "P3D"
 
 [manifest]
@@ -31,7 +31,7 @@ overrides = [
     { name = "gitpython", specifier = ">=3.1.50,<4" },
     { name = "langchain-core", specifier = ">=1.3.3,<2" },
     { name = "langchain-text-splitters", specifier = ">=1.1.2,<2" },
-    { name = "langsmith", specifier = ">=0.8.0,<1" },
+    { name = "langsmith", specifier = ">=0.7.31,<0.8" },
     { name = "onnxruntime", marker = "python_full_version < '3.11'", specifier = "<1.24" },
     { name = "openai", specifier = ">=2.30.0,<3" },
     { name = "pillow", specifier = ">=12.1.1" },
@@ -3888,7 +3888,7 @@ sdist = { url = "https://files.pythonhosted.org/packages/0e/72/a3add0e4eec4eb9e2
 
 [[package]]
 name = "langsmith"
-version = "0.8.3"
+version = "0.7.32"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -3901,9 +3901,9 @@ dependencies = [
     { name = "xxhash" },
     { name = "zstandard" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/de/8a/1e8ea5e8bab2a65fa95bd36229ef38e8723ec46e430e20ca2d953487a7f1/langsmith-0.8.3.tar.gz", hash = "sha256:767ff7a8d136ed42926bf99059ac631dc6883542d6e3104b32e71c7625e1fa05", size = 4460330, upload-time = "2026-05-07T19:56:56.18Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/2f/b4/a0b4a501bee6b8a741ce29f8c48155b132118483cddc6f9247735ddb38fa/langsmith-0.7.32.tar.gz", hash = "sha256:b59b8e106d0e4c4842e158229296086e2aa7c561e3f602acda73d3ad0062e915", size = 1184518, upload-time = "2026-04-15T23:42:41.885Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/98/a9/51e644c1f1dbc3dd7d22dfd6412eab206d538c81e024e4f287373544bdcb/langsmith-0.8.3-py3-none-any.whl", hash = "sha256:b2e40e308222fa0beb2dccee3b4b30bfee9062d7a4f20a3e3e93df3c51a08ab4", size = 399048, upload-time = "2026-05-07T19:56:53.994Z" },
+    { url = "https://files.pythonhosted.org/packages/62/bc/148f98ac7dad73ac5e1b1c985290079cfeeb9ba13d760a24f25002beb2c9/langsmith-0.7.32-py3-none-any.whl", hash = "sha256:e1fde928990c4c52f47dc5132708cec674355d9101723d564183e965f383bf5f", size = 378272, upload-time = "2026-04-15T23:42:39.905Z" },
 ]
 
 [[package]]