agentleFS
MicrosoftKnown publishermicrosoft/Agent365-devTools/.claude/skills/review-pr/SKILL.md

review-pr

Skill61 starsChanged 5 months agoMITView on GitHub

Generate structured PR review comments using Claude Code agents and post them to GitHub. No API key required - uses Claude Code's existing authentication.

  • Reads credentials
  • Installs packages

185 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use diagnose-ci-failures, docs-loop and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • zerx-labSkill

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    Also in 3 projects that use this

  • GeiserXSkill

    docs-loop

    Use when the user asks to audit docs, check documentation for stale claims, or verify docs against the code.

    Also in 3 projects that use this

  • GeiserXSkill

    full-loop

    Drive a repository to done with sergio-loop, then keep improving it with refine-loop at a descending theta. Use only when the user explicitly invokes full-loop.

    Also in 3 projects that use this

  • n24q02mSkill

    review-delta

    Review only changes since last commit using impact analysis. Token-efficient delta review with automatic blast-radius detection.

    Also in 3 projects that use this

  • n24q02mSkill

    build-graph

    Build or update the code review knowledge graph. Run this first to initialize, or let hooks keep it updated automatically.

    Also in 3 projects that use this

  • +7 more from GeiserX
  • Other versions185 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 185

    1. denoland/deno★ 109ksame name
    2. ToolJet/ToolJet★ 41ksame name
    3. remix-run/remix★ 33ksame name
    4. tirth8205/code-review-graph★ 33ksame name
    5. alpinejs/alpine★ 32ksame name
    6. nrwl/nx★ 29ksame name
    7. PrefectHQ/fastmcp★ 28ksame name
    8. jlowin/fastmcp★ 28ksame name
    9. livewire/livewire★ 24ksame name
    10. microsoft/fluentui★ 20ksame name

    175 more not listed

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository3 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 7 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 178 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Automatic fallback: If GitHub API posting fails (e.g., Enterprise Managed User restrictions), automatically generates a markdown file with …

    line 36
  2. Distinctive:

    No hardcoded secrets: Use environment variables or Azure Key Vault

    line 78
  3. Distinctive:

    Credential management: Follow az cli patterns for CLI code.

    line 79
  4. Distinctive:

    Add or remove comments

    line 97
  5. Distinctive:

    If posting fails (API permissions), automatically generates markdown file for manual copy/paste

    line 115
  6. Distinctive:

    Add your own comments if desired

    line 134
  7. Distinctive:

    If API posting fails, automatically generates a markdown file for manual copy/paste

    line 139

“Common” is measured: kept by at least 6 in 10 of the 178 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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
  • Crisp comments (pr-code-reviewer #30): Flags added comments that run past 1-2 lines, restate the code, or narrate design history — a comment says why in one line; long-form reasoning belongs in the commit/PR.
  • Release-note-ready CHANGELOG (pr-code-reviewer #31): Flags CHANGELOG.md entries that name internals, explain mechanism, or run multiple sentences — each entry is one crisp consumer-facing sentence (it ships verbatim to nuget.org release notes).
  • 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. Read the working-tree (PR) version of this file and of .github/copilot-instructions.md and CLAUDE.md — not the base-branch copy. When the PR under review adds or changes a review rule (as PR #461 did with rules #30/#31), the new rule must be applied to that same PR in the same run; reading the base copy would skip it.
  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

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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