code-review
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npx mdskill add openai/codex/code-reviewExecute comprehensive code review across all repository skills.
- Identifies critical issues in pull request submissions.
- Integrates with GitHub for labeling and reporting.
- Aggregates findings from specialized subagent reviews.
- Delivers numbered Markdown reports with file paths.
SKILL.md
.github/skills/code-reviewView on GitHub ↗
--- name: code-review description: Run a final code review on a pull request --- Use subagents to review code using all code-review-* skills in this repository other than this orchestrator. One subagent per skill. Pass full skill path to subagents. Use xhigh reasoning. You must return every single issue from every subagent. You can return an unlimited number of findings. Use raw Markdown to report findings. Number findings for ease of reference. Each finding must include a specific file path and line number. If the GitHub user running the review is the owner of the pull request add a `code-reviewed` label. Do not leave GitHub comments unless explicitly asked.
More from openai/codex
- babysit-prBabysit 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-changesBreaking changes
- code-review-change-sizeChange size guidance (800 lines)
- code-review-contextModel visible context
- code-review-testingTest authoring guidance
- codex-bugDiagnose 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-digestRun 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-bodyUpdate the title and body of one or more pull requests.
- imagegenGenerate 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-docsUse 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.