Code Quality Review
SkillAI & modelsComprehensive code quality review through expert perspectives (Sandi Metz, Jeremy Evans, Kent Beck, Avdi Grimm, Gary Bernhardt). Updates docs/quality_review.md with findings.
Available today. Use it from your connected AI after setup.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Code Quality Review skill
What this skill tells your AI
The instructions your AI receives, as published by codenamev/claude_memory in .claude/skills/review-for-quality/SKILL.md and read by ahel’s review.
Critically review this Ruby codebase for best-practices, idiom use, and overall quality through the eyes of Ruby experts.
Expert Perspectives
Analyze the codebase through these 5 perspectives:
-
Sandi Metz (POODR principles)
- Single Responsibility Principle
- Small, focused methods (< 5 lines ideal)
- Classes with single purpose
- DRY principle
- Clear dependencies
- High test coverage
-
Jeremy Evans (Sequel maintainer)
- Proper Sequel usage patterns (datasets over raw SQL)
- Database performance optimization
- Schema design best practices
- Connection management
- Transaction safety
- Sequel plugins and extensions
-
Kent Beck (TDD, Simple Design)
- Test-first design
- Simple solutions over complex ones
- Revealing intent through naming
- Clear boundaries between components
- Testability without mocks
- Command-Query Separation
-
Avdi Grimm (Confident Ruby)
- Confident code (no defensive nil checks everywhere)
- Tell, don't ask principle
- Null object pattern
- Meaningful return values (not nil)
- Duck typing
- Result objects over exceptions
-
Gary Bernhardt (Boundaries, Fast Tests)
- Functional core, imperative shell
- Fast unit tests (no I/O in logic)
- Clear boundaries between layers
- Separation of I/O and pure logic
- Value objects
- Immutable data structures
Review Process
-
Explore the codebase systematically:
lib/claude_memory/(all subdirectories)- Identify the largest files (> 500 lines)
- Find code duplication patterns
- Check architecture and design patterns
-
Document EVERY issue found with:
- Priority: 🔴 Critical / High / 🟡 Medium / Low
- Specific file:line references
- Which expert's principle is violated
- Concrete improvement suggestions with code examples
- Estimated effort to fix
-
Track progress:
- Compare with previous review date
- Show metrics (lines of code, god objects, etc.)
- Identify what's been fixed since last review
- Highlight new issues that have emerged
-
Provide actionable recommendations:
- High priority items (this week)
- Medium priority items (next week)
- Low priority items (later)
- Quick wins (can do today)
Output Format
Update docs/quality_review.md with:
Structure:
# Code Quality Review - Ruby Best Practices
**Review Date:** [YYYY-MM-DD]
**Previous Review:** [YYYY-MM-DD]
## Executive Summary
[Progress since last review + new critical issues]
## 1. Sandi Metz Perspective
### What's Been Fixed ✅
### Critical Issues 🔴
### Medium Issues 🟡
## 2. Jeremy Evans Perspective
[Same structure]
## 3. Kent Beck Perspective
[Same structure]
## 4. Avdi Grimm Perspective
[Same structure]
## 5. Gary Bernhardt Perspective
[Same structure]
## 6. General Ruby Idioms
[Style and convention issues]
## 7. Positive Observations
[What's working well]
## 8. Priority Refactoring Recommendations
### High Priority (This Week)
### Medium Priority (Next Week)
### Low Priority (Later)
## 9. Conclusion
[Summary + risk assessment + next steps]
## Appendix A: Metrics Comparison
[Table showing progress]
## Appendix B: Quick Wins
[Things that can be done immediately]
## Appendix C: File Size Report
[Largest files identified]
Important Notes
- Be thorough and critical - find real issues to improve
- Every issue needs a specific file:line reference
- Provide code examples for suggested fixes
- Don't just praise - identify concrete problems
- Compare metrics with previous review date
- Estimate effort for each recommendation (days)
Success Criteria
The review is complete when:
docs/quality_review.mdis updated with dated findings- Every issue has file:line references
- Concrete code examples are provided
- Metrics comparison table is included
- Actionable priorities are listed with time estimates
Signals
- GitHub stars
- 24
- Forks
- 2
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
review-for-quality- Source
- github.com/codenamev/claude_memory