Agent Skills › MiniMax-AI/skills › pr-review

pr-review

GitHub

用于审查 MiniMax Skills 仓库的 PR，通过自动化脚本验证结构合规性，并人工检查技能范围、描述质量及 API 安全等规范。

.claude/skills/pr-review/SKILL.md MiniMax-AI/skills

Trigger Scenarios

PR review pull request validate skill check skill

Install

npx skills add MiniMax-AI/skills --skill pr-review -g -y

More Options

Non-standard path

npx skills add https://github.com/MiniMax-AI/skills/tree/main/.claude/skills/pr-review -g -y

Use without installing

npx skills use MiniMax-AI/skills@pr-review

指定 Agent (Claude Code)

npx skills add MiniMax-AI/skills --skill pr-review -a claude-code -g -y

安装 repo 全部 skill

npx skills add MiniMax-AI/skills --all -g -y

预览 repo 内 skill

npx skills add MiniMax-AI/skills --list

SKILL.md

Frontmatter

{
    "name": "pr-review",
    "license": "MIT",
    "metadata": {
        "version": "1.0",
        "category": "tooling"
    },
    "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.\n"
}

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:

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 for the complete hard rules specification.

Phase 2: Content Review (Soft Guidelines)

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

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