PR Review Skill

Generate and post AI-powered PR review comments to GitHub following engineering best practices.

Usage

/review-pr <pr-number>         # Generate review (step 1)
/review-pr <pr-number> --post  # Post review to GitHub (step 2)

Examples:

• /review-pr 180 - Generate review and save to YAML file
• /review-pr 180 --post - Post the reviewed YAML to GitHub

What this skill does

Step 1: Generate (/review-pr <number>)

1. Fetches PR details from GitHub using the gh CLI
2. Performs architectural review (NEW!): Questions design decisions, checks for scope creep, validates use cases
3. Analyzes changes for security, testing, design patterns, and code quality issues
4. Differentiates contexts: CLI code vs GitHub Actions code (different standards)
5. Creates actionable feedback: Specific refactoring suggestions based on file names and patterns
6. Generates structured review comments in an editable YAML file
7. Shows preview of all generated comments

Step 2: Post (/review-pr <number> --post)

1. Reads the YAML file you reviewed/edited
2. Posts to GitHub: Submits all enabled comments to the PR
3. Automatic fallback: If GitHub API posting fails (e.g., Enterprise Managed User restrictions), automatically generates a markdown file with formatted comments for manual copy/paste

Engineering Review Principles

This skill enforces the following principles:

Architectural Review (NEW!)

• Design Decision Validation: Questions "why" before reviewing "how"
• Scope Creep Detection: Flags expansions beyond Agent365 deployment/management
• Use Case Validation: Requires concrete scenarios for new features
• Overlap Detection: Identifies duplication with existing tools (Azure CLI, Portal)
• YAGNI Enforcement: Questions features without documented need

Architecture & Patterns

• .NET architect patterns: Reviews follow .NET best practices
• Azure CLI alignment: Ensures consistency with az cli patterns and conventions
• Cross-platform compatibility: Validates Windows, Linux, and macOS compatibility (for CLI code)

Design Patterns

• KISS (Keep It Simple, Stupid): Prefers simple, straightforward solutions
• DRY (Don't Repeat Yourself): Identifies code duplication
• SOLID principles: Especially Single Responsibility Principle
• YAGNI (You Aren't Gonna Need It): Avoids over-engineering
• One class per file: Enforces clean code organization

Code Quality

• No large files: Flags files over 500 additions
• Function reuse: Encourages reusing functions across commands
• No special characters: Avoids emojis in logs/output (Windows compatibility)
• Self-documenting code: Prefers clear code over excessive comments
• Minimal changes: Makes only necessary changes to solve the problem

Testing Standards

• Framework: xUnit, FluentAssertions, NSubstitute for .NET; pytest/unittest for Python
• Quality over quantity: Focus on critical paths and edge cases
• CLI reliability: CLI code without tests is BLOCKING
• GitHub Actions tests: Strongly recommended (HIGH severity) but not blocking
• Mock external dependencies: Proper mocking patterns

Security

• No hardcoded secrets: Use environment variables or Azure Key Vault
• Credential management: Follow az cli patterns for CLI code; use GitHub Secrets for Actions

Context Awareness

The skill differentiates between:

• CLI code (strict requirements): Cross-platform, reliable, must have tests
• GitHub Actions code (GitHub-specific): Linux-only is acceptable, tests strongly recommended

Review Comments Output

Generated comments are saved to:

C:\Users\<username>\AppData\Local\Temp\pr-reviews\pr-<number>-review.yaml

You can edit this file to:

• Disable comments by setting enabled: false
• Modify comment text
• Adjust severity levels (blocking, high, medium, low, info)
• Add or remove comments

Implementation

The skill uses Claude Code directly for semantic code analysis (inspired by Agent365-dotnet). No separate API key required!

Generate mode (default):

1. Claude Code reads .claude/agents/pr-code-reviewer.md for review process guidelines
2. Claude Code reads .github/copilot-instructions.md for coding standards
3. Claude Code fetches PR details: gh pr view <number> --json ...
4. Claude Code analyzes actual code changes: gh pr diff <number>
5. Claude Code performs semantic analysis using its own capabilities
6. Claude Code identifies specific issues with line numbers and code references
7. Claude Code writes YAML file to C:\Users\<username>\AppData\Local\Temp\pr-reviews\pr-<number>-review.yaml

Post mode (with --post flag):

1. Python script reads the YAML file
2. Python script posts comments to GitHub using gh pr comment
3. If posting fails (API permissions), automatically generates markdown file for manual copy/paste

Key Advantages:

• ✅ No ANTHROPIC_API_KEY required - uses Claude Code's existing authentication
• ✅ Better semantic analysis - Claude Code has full context and conversation history
• ✅ Simpler Python script - only handles posting logic (~240 lines vs ~1500 lines)
• ✅ Easier to maintain and debug

Workflow

1. Generate review: /review-pr 180

   • Fetches PR details from GitHub
   • Analyzes code and generates review comments
   • Saves to YAML file (shows path in output)

2. Review and edit: Open the YAML file

   • Review all generated comments
   • Edit comment text if needed
   • Disable comments by setting enabled: false
   • Add your own comments if desired

3. Post to GitHub: /review-pr 180 --post

   • Reads the YAML file
   • Posts all enabled comments to the PR
   • If API posting fails, automatically generates a markdown file for manual copy/paste

Requirements

• GitHub CLI (gh) installed and authenticated
• Python 3.x (only for --post mode)
• PyYAML library: pip install pyyaml (only for --post mode)
• Repository must be a GitHub repository
• GitHub API permissions to post reviews (Enterprise Managed Users may have restrictions)

See Also

• README.md - Detailed documentation
• review-pr.py - Implementation script