Agent skill
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`.
Install this agent skill to your Project
npx add-skill https://github.com/openai/openai-agents-js/tree/main/.agents/skills/openai-knowledge
SKILL.md
OpenAI Knowledge
Overview
Use the OpenAI Developer Documentation MCP server to search and fetch exact docs (markdown), then base your answer on that text instead of guessing.
Workflow
1) Check whether the Docs MCP server is available
If the mcp__openaiDeveloperDocs__* tools are available, use them.
If you are unsure, run codex mcp list and check for openaiDeveloperDocs.
2) Use MCP tools to pull exact docs
- Search first, then fetch the specific page(s).
mcp__openaiDeveloperDocs__search_openai_docs→ pick the best URL.mcp__openaiDeveloperDocs__fetch_openai_doc→ retrieve the exact markdown (optionally with ananchor).
- When you need endpoint schemas or parameters, use:
mcp__openaiDeveloperDocs__get_openapi_specmcp__openaiDeveloperDocs__list_api_endpoints
Base your answer on the fetched text and quote or paraphrase it precisely. Do not invent flags, field names, defaults, or limits.
3) If MCP is not configured, guide setup (do not change config unless asked)
Provide one of these setup options, then ask the user to restart the Codex session so the tools load:
- CLI:
codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp
- Config file (
~/.codex/config.toml):- Add:
toml
[mcp_servers.openaiDeveloperDocs] url = "https://developers.openai.com/mcp"
- Add:
Also point to: https://developers.openai.com/resources/docs-mcp#quickstart
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
final-release-review
Perform a release-readiness review by locating the previous release tag from remote tags and auditing the diff (e.g., v1.2.3...<commit>) for breaking changes, regressions, improvement opportunities, and risks before releasing openai-agents-js.
examples-auto-run
Run examples:start-all in auto mode with parallel execution, per-script logs, and start/stop helpers.
implementation-strategy
Decide how to implement runtime and API changes in openai-agents-js before editing code. Use when a task changes exported APIs, runtime behavior, schemas, tests, or docs and you need to choose the compatibility boundary, whether shims or migrations are warranted, and when unreleased interfaces can be rewritten directly.
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 (docs/src/content/docs/**) and never touch translated docs under docs/src/content/docs/ja, ko, or zh. Provide a report and ask for approval before editing docs.
pnpm-upgrade
Keep pnpm current: run pnpm self-update/corepack prepare, align packageManager in package.json, and bump pnpm/action-setup + pinned pnpm versions in .github/workflows to the latest release. Use this when refreshing the pnpm toolchain manually or in automation.
runtime-behavior-probe
Plan and execute runtime-behavior investigations with temporary TypeScript probe scripts, validation matrices, state controls, and findings-first reports. Use only when the user explicitly invokes this skill to verify actual runtime behavior beyond normal code-level checks, especially to uncover edge cases, undocumented behavior, or common failure modes in local or live integrations. A baseline smoke check is fine as an entry point, but do not stop at happy-path confirmation.
Didn't find tool you were looking for?