spillwavesolutions/agent_rulez/pr-reviewer
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Comprehensive GitHub Pull Request code review skill. Use when asked to "review this PR", "code review", "review pull request", "check this PR", or when a GitHub PR URL is provided. Fetches PR metadata, diff, comments, commits, and related issues using gh CLI. Creates organized review workspace, analyzes code against industry-standard criteria, and optionally adds inline comments to the PR.
Install
npx vskill@latest install spillwavesolutions/agent_rulez/pr-reviewerSKILL.md
PR Reviewer Skill
Conduct comprehensive, professional code reviews for GitHub Pull Requests using industry-standard criteria and automated tooling.
Table of Contents
- Purpose
- When to Use
- Review Process Workflow
- Reference Documentation
- Scripts Reference
- Best Practices
- Quick Reference Commands
- Tips for Effective Reviews
- Resources
Purpose
This skill performs code reviews by:
- Automating data collection - Fetching all PR-related information (metadata, diff, comments, commits, issues)
- Organizing review workspace - Creating structured directory with all artifacts
- Applying systematic criteria - Reviewing against comprehensive quality checklist
- Facilitating inline feedback - Optionally adding comments directly to PR code
- Ensuring completeness - Checking functionality, security, testing, maintainability
When to Use
Activate this skill when:
- A GitHub PR URL is provided with a review request
- Receiving "review this PR" or "code review" requests
- Checking PR quality before merging
- Providing systematic feedback on proposed changes
- GitHub PR review is mentioned in any context
Review Process Workflow
IMPORTANT: This skill uses a two-stage approval process. Nothing is posted to GitHub until explicit approval with /send or /send-decline.
Overview
- Fetch PR data - Collect all information
- Generate review files - Create detailed, human, and inline comment files
- Review and edit - Examine files, make changes as needed (use
/show) - Approve and post - Use
/send(approve) or/send-decline(request changes)
Step 1: Fetch PR Data
Use fetch_pr_data.py to automatically collect all PR information:
Actions performed:
- Parse PR URL to extract owner, repo, and PR number
- Create directory structure:
<output-dir>/PRs/<repo-name>/<PR-NUMBER>/ - Fetch PR metadata (title, author, state, branches, labels)
- Download PR diff and commit history
- Retrieve all PR comments and reviews
- Extract ticket references (JIRA, GitHub issues)
- Optionally clone source branch and generate git diff
Example:
Output structure:
Step 2: Analyze PR Data
After fetching, analyze collected data against review criteria:
- Read
SUMMARY.txt- High-level overview - Review
metadata.json- PR context, labels, assignees - Examine
diff.patch- Code changes - Check
comments.json- Existing feedback - Review
commits.json- Commit quality and messages - Check
related_issues.json- Linked tickets/issues - Apply review criteria - Evaluate against comprehensive checklist
Use the Read tool to examine files:
Step 3: Generate Review Files
CRITICAL: After analysis, use generate_review_files.py to create structured review documents:
Creates three files in pr_review_dir/pr/:
- `pr/review.md` - Detailed internal review with emojis and line numbers
- `pr/human.md` - Clean review for posting (no emojis, em-dashes, line numbers)
- `pr/inline.md` - Proposed inline comments with code snippets
Also creates slash commands in .claude/commands/:
/send- Post human.md and approve PR/send-decline- Post human.md and request changes/show- Open review directory in VS Code
Findings JSON structure:
Step 4: Review and Edit Files
Use `/show` to open the review directory in VS Code.
Actions available:
- Read
pr/review.md- Detailed analysis - Edit
pr/human.md- Modify before posting - Review
pr/inline.md- Check proposed comments - Adjust any content as needed
NOTHING is posted until explicit approval in Step 5.
Step 5: Approve and Post
Post the review when ready:
Option A: Approve the PR
- Posts
pr/human.mdas comment - Approves the PR
- Confirms action
Option B: Request Changes
- Posts
pr/human.mdas comment - Requests changes on the PR
- Confirms action
Posting inline comments (optional, after /send or /send-decline): Review pr/inline.md and run the provided commands for specific code comments.
Step 6: Apply Review Criteria
Reference references/review_criteria.md for comprehensive checklist. Review against these categories:
| Category | Key Questions | |
|---|---|---|
| Functionality | Does code solve the problem? Bugs? Edge cases? | |
| Readability | Clear code? Meaningful names? DRY? | |
| Style | Follows linter rules? Consistent with codebase? | |
| Performance | Efficient algorithms? Scalable? | |
| Security | Vulnerabilities addressed? Secrets protected? | |
| Testing | Tests exist? Cover happy paths and edge cases? | |
| PR Quality | Focused scope? Clean commits? Clear description? |
Priority markers for findings:
- Blocker: Must be fixed before merge
- Important: Should be addressed
- Nit: Nice to have, optional
- Suggestion: Consider for future
- Question: Clarification needed
- Praise: Good work
For detailed criteria: Read references/review_criteria.md
Reference Documentation
This skill includes comprehensive reference guides:
| Reference | Purpose | |
|---|---|---|
references/review_criteria.md | Complete checklist covering functionality, security, testing, and more | |
references/gh_cli_guide.md | Quick reference for GitHub CLI commands | |
references/scenarios.md | Detailed workflows for common review scenarios | |
references/troubleshooting.md | Common issues and solutions |
Scripts Reference
scripts/fetch_pr_data.py
Automated PR data fetching and organization.
scripts/generate_review_files.py
Generate structured review files from analysis findings.
Creates:
pr/review.md- Detailed internal reviewpr/human.md- Clean review for postingpr/inline.md- Proposed inline comments with commands.claude/commands/send.md- Slash command to approve and post.claude/commands/send-decline.md- Slash command to request changes.claude/commands/show.md- Slash command to open in VS CodeREVIEW_READY.txt- Summary of next steps
scripts/add_inline_comment.py
Add inline code review comments to specific lines in PR.
Best Practices
Communication
- Frame feedback as suggestions, not criticism
- Explain why an issue matters, not just what is wrong
- Acknowledge excellent practices
- Prioritize blockers first, style issues last
Review Efficiency
- Use scripts to automate data fetching and comment posting
- Reference
review_criteria.mdas checklist - Focus: Critical issues > Important > Nice-to-have
- Review promptly (within 24 hours if possible)
Inline Comments
- Reference exact lines and files
- Provide better alternatives
- Test inline comments on test PRs first
- Use sparingly to avoid overwhelming
PR Size Handling
- Large PRs (>400 lines): Suggest splitting
- Review in logical chunks
- Focus on architecture for large changes
For detailed scenarios: Read references/scenarios.md
Quick Reference Commands
Tips for Effective Reviews
- Start with context: Read PR description, linked issues, commit messages
- Understand intent: Identify the problem being solved
- Check tests first: Verify tests demonstrate the fix/feature
- Look for patterns: Repeated issues suggest architecture problems
- Consider alternatives: Evaluate simpler approaches
- Think about maintenance: Assess future modification ease
- Remember humans: Maintain kindness, respect, and constructive tone
For troubleshooting: Read references/troubleshooting.md
Resources
- Review Criteria:
references/review_criteria.md - gh CLI Guide:
references/gh_cli_guide.md - Scenarios:
references/scenarios.md - Troubleshooting:
references/troubleshooting.md - GitHub PR Review Docs: https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/reviewing-changes-in-pull-requests
- Google Engineering Practices: https://google.github.io/eng-practices/review/
- OWASP Top 10: https://owasp.org/www-project-top-ten/
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryChecking.skilz/skills/pr-reviewer/SKILL.md
Popularity
- Repository stars
- 34
- Repository forks
- 8
- 7-day trend score
- 18
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 25 Mar 2026, 7 months ago.
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