القائمة
Review the AGENTS.md file to ensure all rules are up-to-date, removing any redundant or overly vague rules and updating deterministic guardrails as needed.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Fully implement a PRD's issues in dependency order — parallel worktrees, each merged to main as it passes, HITL issues left for a human. Use after write-a-prd + prd-to-issues, when the user wants to "implement the PRD", run the whole issue queue, or run /implementation.
Audit comments across the C# and Python codebase against the comment policy in AGENTS.md, then remove or rewrite the ones that don't earn their place. Use when the user wants to clean up comments, reassess comment value, prune redundant comments, or enforce the comment policy. Optional arg scopes the review — a path (e.g. RaceDataDownloader/), "changed" (git-modified files), or "staged".
Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.
Verify all issues related to the current PRD have been completed and then delete all issues and the PRD itself to maintain a clean project management environment. Use when user explicitly states "clean up PRD" or when a PRD has been marked as completed and needs to be archived.
Pick the next AFK issue from issues/ and implement it end-to-end via TDD, then commit. Use when the user wants to advance the ralph queue, asks to "work on the next issue", or runs this in a /loop.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
| name | review-agents-md |
| description | Review the AGENTS.md file to ensure all rules are up-to-date, removing any redundant or overly vague rules and updating deterministic guardrails as needed. |
Please review the current AGENTS.md file. Remove any redundant or overly vague rules that are no longer necessary or that the latest model versions handle automatically.
Specifically ensure that any deterministic guardrails are updated to ensure they continue to be effective in guiding the model's behavior.
If a conversation has just completed successfully, review our agreed outcomes. If a new constraint, preference, or architectural decision was made, reflect on it and propose an update to the rules in agents.md.
Always wait for my approval before saving.
Put commands early: Put relevant executable commands in an early section: npm test, npm run build, pytest -v. Include flags and options, not just tool names. Your agent will reference these often.
Code examples over explanations: One real code snippet showing your style beats three paragraphs describing it. Show what good output looks like.
Set clear boundaries: Tell AI what it should never touch (e.g., secrets, vendor directories, production configs, or specific folders). “Never commit secrets” was the most common helpful constraint.
Be specific about your stack: Say “React 18 with TypeScript, Vite, and Tailwind CSS” not “React project.” Include versions and key dependencies.
Cover six core areas: Hitting these areas puts you in the top tier: commands, testing, project structure, code style, git workflow, and boundaries.
Aim for a maximum of 150 lines of instructions: Long enough to be specific, but short enough to be read and followed. If you need more, consider using progressive disclosure and link to separate files for detailed guidelines thereby keeping AGENTS.md focused on the most critical rules and examples.
Do not reference in flight work in the current issues/PRD.md or issues/NNN-some-issue.md files. AGENTS.md should contain timeless rules and examples that are not tied to specific in-flight work. Avoid mentioning specific issue numbers, PRDs, or temporary architectural decisions that may change frequently. Focus on general principles and practices that will remain relevant over time.
