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OpenAISkillopenai/openai-agents-python/.agents/skills/examples-run-analysis/SKILL.md
Analyze logs and source from a completed manual examples run. Never execute or control examples.
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OpenAIReads credentialsSkillopenai/openai-agents-python/.agents/skills/final-release-review/SKILL.md
Assess a Python SDK release candidate or release plan against the previous release and recommend ship or block.
OpenAISkillopenai/openai-agents-python/.agents/skills/implementation-final-review/SKILL.md
Review completed implementation changes before final verification. Use when repository policy requires independent review or the user explicitly requests it.
OpenAISkillopenai/openai-agents-python/.agents/skills/implementation-kickoff/SKILL.md
Carry implementation through an isolated worktree and local handoff. Use only when this skill is explicitly invoked.
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OpenAISkillopenai/openai-agents-python/.agents/skills/implementation-strategy/SKILL.md
Choose supported scope and compatibility boundaries for SDK behavior changes; revisit when feedback changes the design.
OpenAISkillopenai/openai-agents-python/.agents/skills/maintainer-review/SKILL.md
Assess a GitHub issue or PR for demonstrated need, supported alternatives, correctness, and maintainer action. Desk review only.
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5 projects use a version of this
OpenAISkillopenai/openai-agents-python/.agents/skills/openai-knowledge/SKILL.md
Retrieve authoritative OpenAI API and platform documentation when an integration or claim needs current external evidence.
OpenAISkillopenai/openai-agents-python/.agents/skills/pr-draft-summary/SKILL.md
Prepare the required local PR title, description, and branch suggestion after eligible implementation work is complete.
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9 projects use a version of this
OpenAIReads credentialsSkillopenai/openai-agents-python/.agents/skills/release-candidate-prep/SKILL.md
Prepare a local Python SDK release candidate in a dedicated worktree. Use only when explicitly invoked with a version.
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OpenAIReads credentialsSkillopenai/openai-agents-python/.agents/skills/runtime-behavior-probe/SKILL.md
Plan controlled runtime probes when explicitly invoked; execute only after the required probe approval.
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OpenAISkillopenai/openai-agents-python/.agents/skills/sensitive-logging-audit/SKILL.md
Audit or fix sensitive-data exposure in Python SDK diagnostics, exceptions, logging, and telemetry.
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1 project uses a version of this
OpenAISkillopenai/openai-agents-python/.agents/skills/test-coverage-improver/SKILL.md
Measure Python SDK coverage or address measured coverage gaps. Use for coverage audits and metric regressions, not routine test additions.
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4 projects use a version of this
OpenAIAGENTS.mdopenai/openai-agents-python/docs/agents.md
Agents are the core building block in your apps. An agent is a large language model (LLM) configured with instructions, tools, and optional runtime behavior such as handoffs, guardrails, and structured outputs. Use this page when you want to define or customize a single base Agent rather than a SandboxAgent. If you are deciding how multiple agents should collaborate, read Agent orchestration. If the agent should run inside an isolated workspace with manifest-defined files and sandbox-native capabilities, read Sandbox agent…
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OpenAIAGENTS.mdopenai/openai-agents-python/docs/ja/agents.md
エージェントは、アプリの中核となる構成要素です。エージェントは、指示、ツール、およびハンドオフ、ガードレール、structured outputs などのオプションのランタイム動作を設定した大規模言語モデル (LLM) です。 SandboxAgent ではなく、単一の基本 Agent を定義またはカスタマイズする場合は、このページを使用してください。複数のエージェントをどのように連携させるかを決める場合は、エージェントオーケストレーションを参照してください。マニフェストで定義されたファイルとサンドボックスネイティブの機能を備えた分離ワークスペース内でエージェントを実行する場合は、サンドボックスエージェントの概念を参照してください。 SDK は、OpenAI モデルに対してデフォルトで Responses API を使用しますが、ここでの違いはオーケストレーションにあります。Agent と Runner を組み合わせることで、SDK がターン、ツール、ガードレール、ハンドオフ、セッションを管理します。このループを自分で管理したい場合は、代わりに Responses API を直接使用してください。 このページを、エージェント定義のハブとして使用してください。次に行う必要がある判断に合った関連ガイドに進んでください。 エージェントで最も一般的なプロパティは次のとおりです。 このセクションの内容はすべて Agent に適用されます。SandboxAgent は同じ考え方を基盤とし、さらにワークスペース単位の実行用に default_manifest、base_instructions、capabilities、run_as を追加します。サンドボックスエージェントの概念を参照してください。 prompt を設定すると、OpenAI プラットフォームで作成したプロンプトテンプレートを参照できます。これは、Responses API を介して OpenAI モデルにアクセスする場合に機能します。 使用するには、次の手順を行ってください。 実行時にプロンプトを動的に生成することもできます。
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OpenAIAGENTS.mdopenai/openai-agents-python/docs/ko/agents.md
에이전트는 앱의 핵심 구성 요소입니다. 에이전트는 지침, 도구 및 핸드오프, 가드레일, structured outputs와 같은 선택적 런타임 동작으로 구성된 대규모 언어 모델(LLM)입니다. SandboxAgent가 아닌 단일 기본 Agent을 정의하거나 사용자 지정하려면 이 페이지를 사용하세요. 여러 에이전트의 협업 방식을 결정하려면 에이전트 오케스트레이션을 읽어보세요. 에이전트가 매니페스트에 정의된 파일과 샌드박스 네이티브 기능을 갖춘 격리된 워크스페이스 내에서 실행되어야 한다면 샌드박스 에이전트 개념을 읽어보세요. SDK는 OpenAI 모델에 기본적으로 Responses API를 사용하지만, 여기서 중요한 차이는 오케스트레이션입니다. Agent와 Runner을 사용하면 SDK가 턴, 도구, 가드레일, 핸드오프 및 세션을 대신 관리할…
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OpenAIllms.txtopenai/openai-agents-python/docs/llms-full.txt
Extended reference map for the OpenAI Agents SDK documentation site. Use these curated links when assembling prompts that need authoritative guidance on building, operating, and extending agentic applications with the SDK. The Agents SDK delivers a focused set of Python primitives—agents, tools, guardrails, handoffs, sessions, and tracing—plus voice and realtime interfaces. The pages below provide detailed walkthroughs, architectural patterns, and API-level documentation for integrating those capabilities into production systems.
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OpenAIllms.txtopenai/openai-agents-python/docs/llms.txt
Official documentation for building production-ready agentic applications with the OpenAI Agents SDK, a Python toolkit that equips LLM-powered assistants with tools, guardrails, handoffs, sessions, tracing, voice, and realtime capabilities. The SDK focuses on a concise set of primitives so you can orchestrate multi-agent workflows without heavy abstractions. These pages explain how to install the library, design agents, coordinate tools, handle results, and extend the platform to new modalities.
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OpenAIAGENTS.mdopenai/openai-agents-python/docs/zh/agents.md
智能体是应用中的核心构建块。智能体是配置了指令、工具和可选运行时行为（如任务转移、安全防护措施和 structured outputs）的大语言模型（LLM）。 如果你要定义或自定义单个基础 Agent，而不是 SandboxAgent，请使用本页面。如果你正在决定多个智能体应如何协作，请阅读智能体编排。如果智能体应在具有清单定义文件和沙箱原生能力的隔离工作区中运行，请阅读沙箱智能体概念。 对于OpenAI模型，SDK 默认使用 Responses API，但这里的区别在于编排：Agent 加上 Runner，可让 SDK 为你管理轮次、工具、安全防护措施、任务转移和会话。如果你希望自行控制该循环，请改为直接使用 Responses API。 可将本页面作为定义智能体的中心入口。根据你接下来需要做出的决策，跳转至相应的相邻指南。 智能体最常用的属性包括： 本节中的所有内容均适用于 Agent。SandboxAgent 基于相同理念构建，并额外添加了 default_manifest、base_instructions、capabilities 和 run_as，用于工作区作用域内的运行。请参阅沙箱智能体概念。 通过设置 prompt，你可以引用在OpenAI平台中创建的提示词模板。当通过 Responses API 访问OpenAI模型时，此功能可用。 要使用此功能，请执行以下操作： 你也可以在运行时动态生成提示词： 智能体以其 context 类型作为泛型参数。上下文是一种依赖注入工具：它是由你创建并传递给 Runner.run() 的对象，随后会传递给每个智能体、工具、任务转移等，并作为智能体运行所需依赖项和状态的集合。你可以提供任何 Python 对象作为上下文。 有关完整的 RunContextWrapper 接口、
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OpenAISkillopenai/openai-agents-python/examples/sandbox/docs/skills/credit-note-fixer/SKILL.md
Fix the tiny credit-note formatting bug and rerun the exact targeted test command.
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OpenAISkillopenai/openai-agents-python/examples/sandbox/healthcare_support/skills/prior-auth-packet-builder/SKILL.md
Build a concise prior authorization packet from local case files and payer policy docs.
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Plain text files in a repository that tell a coding agent how the project works: commands to run, conventions to follow and things to avoid. CLAUDE.md, AGENTS.md, cursor rules and skills are the common kinds.
CLAUDE.md is read by Claude Code. AGENTS.md is an open format that Codex, Cursor and other agents read. Many projects keep one and point the other at it.
A folder with a SKILL.md that describes one capability, such as filling PDFs or reviewing code. The agent loads it only when the task calls for it.
Your agents already can, over MCP, limited to the files you're allowed to read. Searching them from this page is coming.
