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…'name' as required in Agent init doc (#1033) ## What Updated the docs under `docs/agents.md` to clarify that the `name` argument is required when initializing an `Agent`. ## Why Without this clarification, users get a confusing error: `TypeError: Agent.__init__() missing 1 required positional argument: 'name'` This matches the actual constructor in the source code and helps future devs avoid frustration. ## Reference - Source: [`agent.py`](https://github.com/openai/openai-agents-python/blob/main/src/agents/agent.py)

…order (#1015) **Problem:** The expected output in the agent lifecycle example incorrectly shows agent start hooks (`on_start`) running after tool execution and multiple times for the same agent. This misleads developers about when these lifecycle events actually occur. **Solution:** Updated the expected output to accurately reflect the OpenAI Agents framework behavior: - Agent start hooks run immediately when an agent begins execution - Start hooks only run once per agent activation, controlled by the `should_run_agent_start_hooks` flag - After handoffs, the new agent's start hook runs as the first event

### Summary Add MCP prompt support to enable user-controlled agent instruction generation. This enhancement allows MCP servers to provide prompts that can be used to dynamically generate agent instructions, enabling more flexible and user-controlled agent behavior. **Key changes:** - Added abstract `list_prompts()` and `get_prompt()` methods to base `MCPServer` class - Implemented prompt support in `MCPServerStdio` and `MCPServerStreamableHttp` classes - Added comprehensive test suite for prompt functionality - Created example MCP prompt server with working demonstration - Updated documentation with prompt usage examples **Note:** This PR implements MCP prompt support only. Resource support is not included in this implementation. ### Test plan - **Unit tests**: Added 11 comprehensive tests in `tests/mcp/test_prompt_server.py` covering: - Prompt listing and retrieval - Argument formatting and validation - Agent integration with prompt-generated instructions - Streaming and non-streaming scenarios - Error handling for missing prompts - **Integration tests**: Updated existing MCP test suite to handle new abstract methods - **Example verification**: Created working example with MCP prompt server and client - **All tests pass**: 450/450 tests passing after adding optional dependencies ### Issue number Partially addresses #544 (prompts only, resources not implemented) ### Checks - [x] I've added new tests (if relevant) - [x] I've added/updated the relevant documentation - [x] I've run `make lint` and `make format` - [x] I've made sure tests pass --------- Co-authored-by: thein <thein@MacBook-Pro.local>

I added an optional `on_start()` method to `VoiceWorkflowBase`, allowing voice workflows to emit an initial TTS message before any user input. This aligns with the usage pattern suggested in #488 The `VoicePipeline._run_multi_turn()` method was updated to call this hook and stream any yielded messages via TTS before transcription begins. No changes are required to existing workflows, as the method defaults to returning an empty `AsyncIterator[str]`. Resolves #488 and thus improves UX for voice agents that need to greet or instruct users proactively. All tests pass under Python 3.12. Let me know if you'd like an example workflow or docs added in a follow-up!

It adds a Makefile rule `check` to run all linters and checkers in a single command. With only `make check` instead of 3-4 commands, it can help to forget one of them before pushing a PR.

PDF and file upload are supported by litellm and various models. This PR enables them. fixes #893

…tion (#1000) Describe the bug A clear and concise description of what the bug is. In the function_schema method of the OpenAI Agents SDK, the following line: ```python description=description_override or doc_info.description if doc_info else None ``` does not honor description_override when `use_docstring_info=False`. This happens because of operator precedence in Python. Without parentheses, the expression is interpreted as: ```python description=(description_override or doc_info.description) if doc_info else None ``` So when doc_info is None, even if description_override is set, it falls back to None Debug information Python version (e.g. Python 3.10) Repro steps ```python from agents.function_schema import function_schema def my_func(): pass schema = function_schema( my_func, description_override ="CustomDescription", use_docstring_info=False ) print(schema.description) # Expected: "CustomDescription", Actual: None ``` Expected behavior Even when use_docstring_info=False, if description_override is provided, it should be used for description. Suggested Fix: Update this line: description=description_override or doc_info.description if doc_info else None To this (with parentheses to enforce correct evaluation): description=description_override or (doc_info.description if doc_info else None)

This is a patch to address the most pressing issue of #976 while we discuss whether or not these parameters should exist in `list_tools` or should be migrated elsewhere. Resolves #976

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Commits on Jul 8, 2025

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