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openai-agents-sdk

laguagu/claude-code-nextjs-skills

How to install openai-agents-sdk

npx skills add https://github.com/laguagu/claude-code-nextjs-skills --skill openai-agents-sdk
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Full instructions (SKILL.md)

Source of truth, from laguagu/claude-code-nextjs-skills.


name: openai-agents-sdk argument-hint: "[question or feature]" description: OpenAI Agents SDK (Python) development. Use when building AI agents, multi-agent handoffs, function tools, guardrails, sessions, streaming, or tracing with the openai-agents / agents Python package — including Azure OpenAI via LiteLLM. Triggers on imports from agents, uses of Runner.run_sync/Runner.run_streamed, @function_tool, AgentOutputSchema, SQLiteSession, or questions about the openai-agents-python SDK.

OpenAI Agents SDK (Python)

Use this skill when developing AI agents using OpenAI Agents SDK (openai-agents package).

Quick Reference

Installation

pip install openai-agents

Environment Variables

# OpenAI (direct)
OPENAI_API_KEY=sk-...
LLM_PROVIDER=openai

# Azure OpenAI (via LiteLLM)
LLM_PROVIDER=azure
AZURE_API_KEY=...
AZURE_API_BASE=https://your-resource.openai.azure.com
AZURE_API_VERSION=2024-12-01-preview

Basic Agent

from agents import Agent, Runner

agent = Agent(
    name="Assistant",
    instructions="You are a helpful assistant.",
    model="gpt-5.4",  # or "gpt-5.4-mini", "gpt-5.4-nano"
)

# Synchronous
result = Runner.run_sync(agent, "Tell me a joke")
print(result.final_output)

# Asynchronous
result = await Runner.run(agent, "Tell me a joke")

Key Patterns

PatternPurpose
Basic AgentSimple Q&A with instructions
Azure/LiteLLMAzure OpenAI integration
AgentOutputSchemaStrict JSON validation with Pydantic
Function ToolsExternal actions (@function_tool)
StreamingReal-time UI (Runner.run_streamed)
HandoffsSpecialized agents, delegation
Agents as ToolsOrchestration (agent.as_tool)
LLM as JudgeIterative improvement loop
GuardrailsInput/output validation
SessionsAutomatic conversation history
Multi-Agent PipelineMulti-step workflows
SandboxingIsolated execution environment for agents
SubagentsSpawn specialized subordinate agents (Python; TS in beta/development)
ObservabilityBuilt-in execution graph recording

Preferred: Live Docs via MCP

Model names and API details change frequently. When available, consult the OpenAI Developer Docs MCP server (openaiDeveloperDocs) before relying on the static references below.

Setup (Codex CLI):

codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp

Or config (~/.codex/config.toml, VS Code .vscode/mcp.json, Cursor ~/.cursor/mcp.json):

[mcp_servers.openaiDeveloperDocs]
url = "https://developers.openai.com/mcp"

Key tools: mcp__openaiDeveloperDocs__search_openai_docs, fetch_openai_doc, list_api_endpoints, get_openapi_spec.

Rules: Cite fetched docs. Never speculate on field names, defaults, or current model IDs — fetch first. Keep quotes under 125 chars.

Fallback when MCP is unavailable: https://developers.openai.com/api/docs/llms.txt (plain-text index of all API docs; each entry has a .md twin at /api/docs/<slug>.md).

Reference Documentation

Offline/quick-lookup snippets. Verify model names and API signatures against the MCP or docs when accuracy matters.

Official Documentation