openai-knowledge

Use when working with the OpenAI API (Responses API) or OpenAI platform features (tools, streaming, Realtime API, auth, models, rate limits, MCP) and you need authoritative, up-to-date documentation (schemas, examples, limits, edge cases). Prefer the OpenAI Developer Documentation MCP server tools when available; otherwise guide the user to enable `openaiDeveloperDocs`.

Ir a la instalación

Repositorio: openai/openai-agents-python
Última actividad en el origen: 20 de marzo de 2026 a las 03:56
Idioma detectado de SKILL.md: inglés
Estrellas: 28.574
Forks: 4481

Opciones de instalación

De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.

Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.

Un comando directo omite el prompt de revisión. Revisa el origen antes de ejecutarlo.

npx skills add https://github.com/openai/openai-agents-python --skill openai-knowledge

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SKILL.md

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docs-sync

Analyze main branch implementation and configuration to find missing, incorrect, or outdated documentation in docs/. Use when asked to audit doc coverage, sync docs with code, or propose doc updates/structure changes. Only update English docs under docs/** and never touch translated docs under docs/ja, docs/ko, or docs/zh. Provide a report and ask for approval before editing docs.

2026-08-13

implementation-final-review

Perform a risk-tiered zero-base final review loop before an implementation is declared complete. Use only when the user explicitly invokes $implementation-final-review or repository instructions authorize automatic invocation after implementation. Audit the complete merge-base diff for requirement fit, contract-surface coverage, await-boundary and lifecycle gaps, released compatibility, security, protocol, and persistence boundaries, unnecessary complexity, package and generated public surfaces, and adversarial test coverage; use compact self-contained reviewer packets and two concurrent no-history independent reviewers per round, defer broad final repository verification until review is clean and observable host capacity is available, preserve clean evidence for unchanged semantic components, close repeated root-cause groups instead of accumulating local patches, and enforce bounded review cycles in one task-global ledger.

2026-08-11

implementation-kickoff

Start and carry an explicitly invoked openai-agents-python implementation through a fresh isolated worktree and a local PR-ready handoff. Fetch the latest origin/main, keep task changes uncommitted, replay them onto the latest main before final review, run applicable verification and $implementation-final-review, use $pr-draft-summary to generate the complete PR draft and branch name, then create one clean local commit with takeover provenance when applicable. Use only when the user explicitly invokes this skill; never push, open a PR, or mutate GitHub.

2026-08-11

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name	openai-knowledge
description	Use when working with the OpenAI API (Responses API) or OpenAI platform features (tools, streaming, Realtime API, auth, models, rate limits, MCP) and you need authoritative, up-to-date documentation (schemas, examples, limits, edge cases). Prefer the OpenAI Developer Documentation MCP server tools when available; otherwise guide the user to enable `openaiDeveloperDocs`.