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Run npx skillmds@latest add tao12345666333/gh-pr-review in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Gh Pr Review safe to use?

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Which AI agents work with Gh Pr Review?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Gh Pr Review free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Gh Pr Review?

tao12345666333 (@tao12345666333) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Gh Pr Review by tao12345666333 — Agent Skill

Name: Gh Pr Review
Author: tao12345666333

Gh Pr Review

Review GitHub Pull Requests using the gh CLI. Use when a user asks to review a PR, perform code review, check a pull request, or provide feedback on proposed changes. Triggers on phrases like "review PR", "review pull request", "check PR", "code review".

File contents

GitHub PR Review Skill

Review Pull Requests by fetching the diff, analyzing changes, and posting structured review comments.

Prerequisites

gh CLI authenticated (gh auth status)
Repository must be a git clone with a GitHub remote

Review Workflow

Fetch PR metadata: Run gh pr view <number> --json title,body,files,additions,deletions,author,baseRefName,headRefName
Fetch the diff: Run gh pr diff <number> to get the full diff
Analyze the changes by category:
- Architecture: New files/modules, structural decisions
- Correctness: Logic bugs, edge cases, error handling
- Security: Input validation, secrets, auth
- Performance: Unnecessary allocations, N+1 queries, blocking I/O
- Style: Naming, consistency with codebase conventions
- Tests: Coverage, edge cases, test quality
Produce a structured review (see format below)

Review Output Format

## PR Review: <title>

**PR**: #<number> | **Author**: <author> | **Branch**: <head> → <base>
**Files changed**: <count> | **+<additions>** / **-<deletions>**

### Summary
<1-2 sentence overview of what this PR does>

### 👍 Strengths
- <what's done well>

### 🔍 Issues Found

#### Critical
- [ ] <file>:<line> — <description>

#### Suggestions
- [ ] <file>:<line> — <description>

#### Nits
- <minor style/naming suggestions>

### 📋 Checklist
- [ ] Tests added/updated
- [ ] No secrets or credentials
- [ ] Error handling adequate
- [ ] Documentation updated if needed

### Verdict
<APPROVE | REQUEST_CHANGES | COMMENT> — <reasoning>

Posting the Review

After generating the review, offer to post it as a PR comment:

gh pr review <number> --comment --body "<review content>"

Or for approve/request-changes:

gh pr review <number> --approve --body "<review content>"
gh pr review <number> --request-changes --body "<review content>"

Tips

For large PRs (>500 lines), focus on architectural decisions and critical issues first
Check for consistency with the existing codebase patterns
Look at test coverage relative to the complexity of changes
Use gh pr checks <number> to see CI status
When reviewing Python, pay attention to type hints, docstrings, and error handling

---name: gh-pr-reviewdescription: Review GitHub Pull Requests using the gh CLI. Use when a user asks to review a PR, perform code review, check a pull request, or provide feedback on proposed changes. Triggers on phrases like "review PR", "review pull request", "check PR", "code review".---# GitHub PR Review SkillReview Pull Requests by fetching the diff, analyzing changes, and posting structured review comments.## Prerequisites- `gh` CLI authenticated (`gh auth status`)- Repository must be a git clone with a GitHub remote## Review Workflow1. **Fetch PR metadata**: Run `gh pr view <number> --json title,body,files,additions,deletions,author,baseRefName,headRefName`2. **Fetch the diff**: Run `gh pr diff <number>` to get the full diff3. **Analyze the changes** by category: - **Architecture**: New files/modules, structural decisions - **Correctness**: Logic bugs, edge cases, error handling - **Security**: Input validation, secrets, auth - **Performance**: Unnecessary allocations, N+1 queries, blocking I/O - **Style**: Naming, consistency with codebase conventions - **Tests**: Coverage, edge cases, test quality4. **Produce a structured review** (see format below)## Review Output Format```markdown## PR Review: <title>**PR**: #<number> | **Author**: <author> | **Branch**: <head> → <base>**Files changed**: <count> | **+<additions>** / **-<deletions>**### Summary<1-2 sentence overview of what this PR does>### 👍 Strengths- <what's done well>### 🔍 Issues Found#### Critical- [ ] <file>:<line> — <description>#### Suggestions- [ ] <file>:<line> — <description>#### Nits- <minor style/naming suggestions>### 📋 Checklist- [ ] Tests added/updated- [ ] No secrets or credentials- [ ] Error handling adequate- [ ] Documentation updated if needed### Verdict<APPROVE | REQUEST_CHANGES | COMMENT> — <reasoning>```## Posting the ReviewAfter generating the review, offer to post it as a PR comment:```bashgh pr review <number> --comment --body "<review content>"```Or for approve/request-changes:```bashgh pr review <number> --approve --body "<review content>"gh pr review <number> --request-changes --body "<review content>"```## Tips- For large PRs (>500 lines), focus on architectural decisions and critical issues first- Check for consistency with the existing codebase patterns- Look at test coverage relative to the complexity of changes- Use `gh pr checks <number>` to see CI status- When reviewing Python, pay attention to type hints, docstrings, and error handling

Frequently asked questions