> Review pull requests for the MiniMax Skills repository. Use when reviewing PRs, validating new skill submissions, or checking existing skills for compliance. Run the validation script first for hard checks, then apply quality guidelines for content review. Triggers: PR review, pull request, validate skill, check skill.
Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add MiniMax-AI/skills --skill "pr-review" -g -a claude-code -yOr manually — clone and copy the skill directory (SKILL.md + companion files):
git clone --depth 1 https://github.com/MiniMax-AI/skills /tmp/skills && cp -r /tmp/skills/.claude/skills/pr-review ~/.claude/skills/pr-review-minimax-aiThis skill is a directory: SKILL.md is the entry point; the files below ship with it.
---
name: pr-review
description: >
Review pull requests for the MiniMax Skills repository. Use when reviewing PRs,
validating new skill submissions, or checking existing skills for compliance.
Run the validation script first for hard checks, then apply quality guidelines
for content review. Triggers: PR review, pull request, validate skill, check skill.
license: MIT
metadata:
version: "1.0"
category: tooling
---
# 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`)
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes