Agent skill
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Analyze main branch implementation and configuration to find missing, incorrect, or outdated documentation in docs/.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.
Install this agent skill to your Project
npx add-skill https://github.com/openai/openai-agents-js/tree/main/.agents/skills/docs-sync
SKILL.md
Docs Sync
Overview
Identify doc coverage gaps and inaccuracies by comparing main branch features and configuration options against the current docs structure, then propose targeted improvements.
Workflow
-
Confirm scope and base branch
- Identify the current branch and default branch (usually
main). - Prefer analyzing the current branch to keep work aligned with in-flight changes.
- If the current branch is not
main, analyze only the diff vsmainto scope doc updates. - Avoid switching branches if it would disrupt local changes; use
git show main:<path>orgit worktree addwhen needed.
- Identify the current branch and default branch (usually
-
Build a feature inventory from the selected scope
- If on
main: inventory the full surface area and review docs comprehensively. - If not on
main: inventory only changes vsmain(feature additions/changes/removals). - Focus on user-facing behavior: public exports, configuration options, environment variables, CLI commands, default values, and documented runtime behaviors.
- Capture evidence for each item (file path + symbol/setting).
- Use targeted search to find option types and feature flags (for example:
rg "Options",rg "process.env",rg "export"). - When the topic involves OpenAI platform features, invoke
$openai-knowledgeto pull current details from the OpenAI Developer Docs MCP server instead of guessing, while treating the SDK source code as the source of truth when discrepancies appear. - For MCP SDK (
modelcontextprotocol/typescript-sdk) or Vercel AI SDK (@ai-sdk/*) topics, optionally use Deepwiki MCP for quick lookups, and still treat the SDK source code as the source of truth.
- If on
-
Doc-first pass: review existing pages
- Walk each relevant page under
docs/src/content/docs(excludingdocs/src/content/docs/openai). - Identify missing mentions of important, supported options (opt-in flags, env vars), customization points, or new features from
packages/. - Propose additions where users would reasonably expect to find them on that page.
- Walk each relevant page under
-
Code-first pass: map features to docs
- Review the current docs information architecture under
docs/src/content/docs. - Determine the best page/section for each feature based on existing patterns and package boundaries.
- Identify features that lack any doc page or have a page but no corresponding content.
- Note when a structural adjustment would improve discoverability.
- Review the current docs information architecture under
-
Detect gaps and inaccuracies
- Missing: features/configs present in main but absent in docs.
- Incorrect/outdated: names, defaults, or behaviors that diverge from main.
- Structural issues (optional): pages overloaded, missing overviews, or mis-grouped topics.
-
Produce a Docs Sync Report and ask for approval
- Provide a clear report with evidence, suggested doc locations, and proposed edits.
- Ask the user whether to proceed with doc updates.
-
If approved, apply changes (English only)
- Edit only English docs in
docs/src/content/docs/**. - Exclude
docs/src/content/docs/openaifrom review and updates. - Do not edit
docs/src/content/docs/ja,docs/src/content/docs/ko, ordocs/src/content/docs/zh. - Keep changes aligned with the existing docs style and navigation.
- Place any code snippets under
examples/docs/<doc-filename>/so the directory name matches the target doc file, mirroring existing patterns. - Verify doc code snippets build successfully with
pnpm -F docs-code build-checkand fix issues before handoff.
- Edit only English docs in
Output format
Use this template when reporting findings:
Docs Sync Report
- Doc-first findings
- Page + missing content → evidence + suggested insertion point
- Code-first gaps
- Feature + evidence → suggested doc page/section (or missing page)
- Incorrect or outdated docs
- Doc file + issue + correct info + evidence
- Structural suggestions (optional)
- Proposed change + rationale
- Proposed edits
- Doc file → concise change summary
- Questions for the user
References
references/doc-coverage-checklist.md
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
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`.
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.
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.
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