codex-bug
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npx mdskill add openai/codex/codex-bugVerify GitHub bug reports and determine next diagnostic steps.
- Analyzes openai/codex issue URLs to confirm bug validity.
- Uses GitHub API endpoints for issue and comment data.
- Decides actions by comparing reports against repository sources.
- Outputs verified findings or requests additional information.
SKILL.md
.github/skills/codex-bugView on GitHub ↗
--- name: codex-bug description: 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 Bug ## Overview Diagnose a Codex GitHub bug report and decide the next action: verify against sources, request more info, or explain why it is not a bug. ## Workflow 1. Confirm the input - Require a GitHub issue URL that points to `github.com/openai/codex/issues/…`. - If the URL is missing or not in the right repo, ask the user for the correct link. 2. Network access - Always access the issue over the network immediately, even if you think access is blocked or unavailable. - Prefer the GitHub API over HTML pages because the HTML is noisy: - Issue: `https://api.github.com/repos/openai/codex/issues/<number>` - Comments: `https://api.github.com/repos/openai/codex/issues/<number>/comments` - If the environment requires explicit approval, request it on demand via the tool and continue without additional user prompting. - Only if the network attempt fails after requesting approval, explain what you can do offline (e.g., draft a response template) and ask how to proceed. 3. Read the issue - Use the GitHub API responses (issue + comments) as the source of truth rather than scraping the HTML issue page. - Extract: title, body, repro steps, expected vs actual, environment, logs, and any attachments. - Note whether the report already includes logs or session details. - If the report includes a thread ID, mention it in the summary and use it to look up the logs and session details if you have access to them. 4. Summarize the bug before investigating - Before inspecting code, docs, or logs in depth, write a short summary of the report in your own words. - Include the reported behavior, expected behavior, repro steps, environment, and what evidence is already attached or missing. 5. Decide the course of action - **Verify with sources** when the report is specific and likely reproducible. Inspect relevant Codex files (or mention the files to inspect if access is unavailable). - **Request more information** when the report is vague, missing repro steps, or lacks logs/environment. - **Explain not a bug** when the report contradicts current behavior or documented constraints (cite the evidence from the issue and any local sources you checked). 6. Respond - Provide a concise report of your findings and next steps.
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-reviewRun a final code review on a pull request
- code-review-change-sizeChange size guidance (800 lines)
- code-review-contextModel visible context
- code-review-testingTest authoring guidance
- 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.