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Pr Review

  • 1.6k installs
  • 13.2k repo stars
  • Updated April 18, 2026
  • minimax-ai/skills

A structured PR review workflow that applies both automated hard rules and manual content guidelines to validate skill submissions.

About

This skill provides a two-phase PR review process for the MiniMax Skills repository. Phase 1 runs automated validation via a Python script that checks SKILL.md existence, YAML frontmatter syntax, required fields (name, description), name-to-directory matching, and absence of hardcoded secrets. Phase 2 applies soft content guidelines: skill scope overlap, description clarity, file size, API key handling via environment variables, script quality (shebang, requirements.txt, error handling), English language compliance, and README table sync. Developers use this when reviewing contributions, validating new skill submissions, or ensuring existing skills remain compliant with repository standards.

  • Automated validation script checks SKILL.md structure, YAML parsing, required fields, and secret detection
  • Two-phase review: hard structural rules (blockers) then soft content guidelines (flagged items)
  • Validates name matches directory, API credentials via environment variables, script shebangs and error handling
  • Ensures README.md and README_zh.md updated with new skills and Source column set to Community
  • Checks PR title follows conventional commit format and enforces one-PR-one-purpose constraint

Pr Review by the numbers

  • 1,574 all-time installs (skills.sh)
  • +29 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Ranked #84 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

pr-review capabilities & compatibility

Capabilities
validate skill.md structure and yaml frontmatter · check for required fields (name, description) an · detect hardcoded secrets in skill files · review skill scope for functional overlap with e · verify api key handling via environment variable · validate script quality (shebang, requirements.t · check readme table synchronization and source co
Use cases
code review · testing
Platforms
macOS · Windows · Linux · WSL
Runs
Runs locally
Pricing
Free
npx skills add https://github.com/minimax-ai/skills --skill pr-review

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Listed on Skillselion
Installs1.6k
repo stars13.2k
Security audit3 / 3 scanners passed
Last updatedApril 18, 2026
Repositoryminimax-ai/skills

What it does

Validate pull requests to the MiniMax Skills repository against structural and content standards before merge.

Who is it for?

Maintainers and reviewers validating skill submissions; contributors ensuring their PRs pass validation before submission.

Skip if: General code review outside the MiniMax Skills repository; real-time linting during development (use pre-commit hooks instead).

When should I use this skill?

A pull request is opened or updated in the MiniMax Skills repository; contributor wants to self-check before submission.

What you get

Contributors receive clear feedback on compliance with hard blockers and soft guidelines; maintainers can merge with confidence that skills meet repository standards.

  • Review comments
  • Scope boundary notes
  • Description improvement suggestions

By the numbers

  • Two-phase review process: automated hard rules + manual soft guidelines
  • 6 hard structural checks in validation script (SKILL.md, YAML, required fields, name match, secrets)
  • 6 soft content guidelines (scope, description, file size, API handling, script quality, language)

Files

SKILL.mdMarkdownGitHub ↗

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:

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 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)

Related skills

How it compares

Use pr-review for catalog SKILL.md governance; use code-review skills when the PR changes application source instead of agent skills.

FAQ

What do I do if validate_skills.py exits with a non-zero code?

Fix the ERROR-level issues (SKILL.md missing, unparseable YAML, missing name/description, name mismatch, hardcoded secrets). WARNING-level items (missing license, metadata) should be flagged but are not blockers.

Are soft content guidelines blockers or just recommendations?

Soft guidelines (scope overlap, description quality, file size, API key handling, script quality, English language, README sync) are flagged in review but not automated blockers; hard rules from validate_skills.py must pass.

How should I handle API credentials in a skill?

Read credentials from environment variables, never hardcode secrets. The validation script checks for hardcoded secrets and will flag them as errors.

Is Pr Review safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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