pr-review

Files (4)

• SKILL.md
• quality-guidelines.md · references/
• structure-rules.md · references/
• validate_skills.py · scripts/

SKILL.md (first lines)

# PR Review Skill

Review pull requests against repository standards. Two-phase process: automated validation, then manual content review.

## Phase 1: Automated Validation (Hard Rules)

Run the validation script to check structural requirements:

```bash
python .claude/skills/pr-review/scripts/validate_skills.py
```

The script checks:
- `SKILL.md` exists in every skill directory
- YAML frontmatter is parseable
- Required fields present: `name`, `description`
- `name` matches directory name
- No hardcoded secrets detected

All ERROR-level checks must pass. WARNING-level items (missing `license`, `metadata`) should be flagged but are not blockers.

See [references/structure-rules.md](references/structure-rules.md) for the complete hard rules specification.

## Phase 2: Content Review (Soft Guidelines)

After automated checks pass, review the PR against quality guidelines:

1. **Skill scope** — Does it overlap with existing skills? Is the boundary clear?
2. **Description quality** — Does the `description` include clear trigger conditions?
3. **File size** — Are reference docs reasonably sized for context window consumption?
4. **API key handling** — If external APIs are used, are credentials read from environment variables?
5. **Script quality** — Do scripts have shebang, requirements.txt, and error handling?
6. **Language** — Are SKILL.md and code written in English?
7. **README sync** — Are `README.md` and `README_zh.md` updated for new skills?

See [references/quality-guidelines.md](references/quality-guidelines.md) for soft guidelines details.

## Review Checklist Summary

### Must Pass (Blockers)
- [ ] `validate_skills.py` exits with code 0
- [ ] PR title follows conventional commit format
- [ ] One PR, one purpose

### Should Pass (Flagged in Review)
- [ ] No functional overlap with existing skills
- [ ] Description includes trigger conditions
- [ ] Files are reasonably sized
- [ ] API keys via environment variables
- [ ] README tables updated for new skills (Source column set to `Community`)

From MiniMax-AI/skills, MIT.

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