implementation-strategy
Decide how to implement runtime and API changes in openai-agents-python before editing code. Use when a task changes exported APIs, runtime behavior, serialized state, 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.
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`.
pr-draft-summary
Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-agents-python. Use in the final handoff after moderate-or-larger changes to runtime code, tests, examples, build/test configuration, or docs with behavior impact; skip only for trivial or conversation-only tasks, repo-meta/doc-only tasks without behavior impact, or when the user explicitly says not to include the PR draft block.
runtime-behavior-probe
Plan and execute runtime-behavior investigations with temporary 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.
test-coverage-improver
Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests.
csv-workbench
Analyze CSV files in /mnt/data and return concise numeric summaries.
pdf-processing-openai
Toolkit for comprehensive PDF reading, reviwing, and creation with visual quality control. Use to work with PDFs (.pdf files) for: (1) Reading or extracting content from existing PDFs, (2) Creating new PDF documents with professional formatting, (3) Generating reports, documents, or layouts that require precise typography and design, or any other PDF reading or generation tasks.
security-review-openai
Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
skill-creator-openai
Guide for creating effective skills. Use when users want to create a new skill (or update an existing skill) that extends the model's capabilities with specialized knowledge, workflows, or tool integrations.
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep watching open PRs so fresh review feedback is surfaced promptly. Use when the user asks Codex to monitor a PR, watch CI, handle review comments, or keep an eye on failures and feedback on an open PR.
code-breaking-changes
Breaking changes
code-review-change-size
Change size guidance (800 lines)
code-review-context
Model visible context
code-review-testing
Test authoring guidance
code-review
Run a final code review on a pull request
codex-bug
Diagnose GitHub bug reports in openai/codex. Use when given a GitHub issue URL from openai/codex and asked to decide next steps such as verifying against the repo, requesting more info, or explaining why it is not a bug; follow any additional user-provided instructions.
codex-issue-digest
Run a GitHub issue digest for openai/codex by feature-area labels, all areas, and configurable time windows. Use when asked to summarize recent Codex bug reports or enhancement requests, especially for owner-specific labels such as tui, exec, app, or similar areas.
codex-pr-body
Update the title and body of one or more pull requests.
path-types
Choose Rust types for operating system paths across the Codex repository. Use when defining new path-bearing types or explicitly migrating existing ones.
pushing-ci-changes
Pushing GitHub Actions changes, resolving push rejection, requesting upload exceptions.
remote-tests
Testing against remote executors in integration tests.
test-tui
Guide for testing Codex TUI interactively
update-v8-version
Update Codex's pinned `v8` / `rusty_v8` versions, validate the release-candidate path, and investigate failed V8 canary or artifact builds. Use when asked to bump V8, update `rusty_v8` artifacts, prepare or validate a V8 release candidate, check `v8-canary`, or diagnose why a V8 version update no longer builds.
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.
openai-docs
Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.
plugin-creator
Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow.
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
skill-installer
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
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.
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.
changeset-validation
Validate changesets in openai-agents-js using LLM judgment against git diffs (including uncommitted local changes). Use when packages/ or .changeset/ are modified, or when verifying PR changeset compliance and bump level.
code-change-verification
Run the mandatory verification stack when changes affect runtime code, tests, or build/test behavior in the OpenAI Agents JS monorepo.
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.
integration-tests
Run the integration-tests pipeline that depends on a local npm registry (Verdaccio). Use when asked to execute integration tests or local publish workflows in this repo.
maintainer-review
Review a GitHub issue or pull request URL as an openai-agents-js maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality, correctly scoped, better served by another design, and worth maintainer and contributor effort. Use when assessing issue validity or severity, deciding whether an issue should be prioritized or closed, determining whether a requested feature represents an unmet need rather than a discoverability or usage gap, judging whether a PR is worth bringing to mergeable quality, comparing open PRs or alternative designs, separating code quality from repository readiness, or drafting a concise maintainer assessment. When closure, additional evidence, or code changes should be requested, also produce a polite, concise, complete, copy-paste-ready maintainer comment.
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`.
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.
pr-draft-summary
Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-agents-js. Must be used before the final response whenever the actual task diff includes runtime code, tests, examples, build/test configuration, or docs with behavior impact, regardless of perceived change size. Skip only when no eligible files changed, every change is repo-meta or docs-only without behavior impact, the task is conversation-only, or the user explicitly opts out.
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.
test-coverage-improver
Improve test coverage in the OpenAI Agents JS monorepo: run `pnpm test:coverage`, inspect coverage artifacts, identify low-coverage files and branches, propose high-impact tests, and confirm with the user before writing tests.
invoice-total-fixer
Use when fixing invoice total calculations in the sandbox quickstart repository.
credit-note-fixer
Fix the tiny credit-note formatting bug and rerun the exact targeted test command.
csv-workbench
Analyze CSV files in /mnt/data and return concise numeric summaries.
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