openai-agents-sdk
Expert guidance for building multi-agent AI applications using the OpenAI Agents SDK for Python. Use when (1) creating agents with handoffs, tools, guardrails, or sessions, (2) implementing structured outputs with Pydantic models, (3) building agentic workflows, (4) debugging and tracing agent execution, (5) working with provider-agnostic LLM applications (OpenAI, Anthropic, LiteLLM), or (6) implementing customer support, legal research, financial analysis, or autonomous task completion systems.
npx skills add majiayu000/claude-skill-registry --skill openai-agents-sdk --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# OpenAI Agents SDK A lightweight, powerful framework for building multi-agent AI workflows in Python. ## Installation ```bash pip install openai-agents # With LiteLLM for multi-provider support pip install openai-agents[litellm] ``` Set your API key: ```bash export OPENAI_API_KEY=your-key ``` ## Quick Start ```python from agents import Agent, Runner agent = Agent( name="Assistant", instructions="You are a helpful assistant", ) result = Runner.run_sync(agent, "Hello!") print(result.final_output) ``` ## Core Primitives | Primitive | Purpose | |-----------|---------| | **Agent** | LLM with instructions and tools | | **Tools** | Python functions agents can call | | **Handoffs** | Delegate to specialized agents | | **Guardrails** | Validate inputs/outputs | | **Sessions** | Maintain conversation history | | **Runner** | Execute agent workflows | ## Agent with Tools ```python from agents import Agent, Runner, function_tool @function_tool def get_weather(city: str) -> str: """Get weather for a city.""" return f"Weather in {city}: Sunny, 72F" agent = Agent( name="Weather Bot", instructions="Help with weather questions", tools=[get_weather], ) result = Runner.run_sync(agent, "What's the we
- Installation
- Quick Start
- Core Primitives
- Agent with Tools
- Structured Output
- Multi-Agent Handoffs
- Sessions (Conversation Memory)
- Custom OpenAI-Compatible Providers
- Multi-Provider (LiteLLM)
- Fallback Model Pattern
- DeepSeek Integration
- Reference Documentation
- Common Patterns
- Customer Support
pip install openai-agents With LiteLLM for multi-provider support pip install openai-agents[litellm] export OPENAI_API_KEY=your-key
What does the openai-agents-sdk skill do?
Expert guidance for building multi-agent AI applications using the OpenAI Agents SDK for Python. Use when (1) creating agents with handoffs, tools, guardrails, or sessions, (2) implementing structured outputs with Pydantic models, (3) building agentic workflows, (4) debugging and tracing agent execution, (5) working with provider-agnostic LLM applications (OpenAI, Anthropic, LiteLLM), or (6) implementing customer support, legal research, financial analysis, or autonomous task completion systems.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill openai-agents-sdk --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.