| name | code-review |
| description | Provide structured code review guidance for catching defects and improving quality. This skill should be used when the user asks to 'review this code', 'check for issues', 'PR review', 'code quality check', or wants systematic code evaluation. Keywords: code review, PR, pull request, quality, defects, security, maintainability, performance. |
| license | MIT |
| compatibility | Works with any programming language. Integrates with github-agile for PR workflow. |
| metadata | {"author":"jwynia","version":"1.0","type":"diagnostic","mode":"evaluative","domain":"development"} |
Code Review Diagnostic
Systematic code review catches 60-90% of defects before production, reduces maintenance costs by 40%, and serves as effective knowledge transfer. This skill provides structured review guidance for both human reviewers and AI agents.
When to Use This Skill
Use this skill when:
- Reviewing code before merge
- Assessing code quality
- Preparing code for PR submission
- Self-reviewing before requesting review
Do NOT use this skill when:
- Writing new code (use implementation skills)
- Designing architecture (use system-design)
- Working on requirements (use requirements-analysis)
Core Principle
Review effectiveness degrades sharply with PR size. Under 400 lines: highest defect detection. 400-800 lines: 50% less effective. 800+ lines: 90% less effective.
Quick Reference: Review Effectiveness
| Factor | Optimal | Degraded |
|---|
| PR size | < 400 lines | > 800 lines |
| Review time | < 60 minutes | > 90 minutes |
| Review speed | 200-400 LOC/hour | > 500 LOC/hour |
| Reviewers | 2 | 4+ (diminishing returns) |
Quality Pyramid
| Level | Checks | Catches | Frequency |
|---|
| 1. Automated | Lint, types, unit tests, security scan | 60% | Every commit |
| 2. Integration | Integration tests, contracts, performance | 25% | Every PR |
| 3. Human Review | Design, logic, maintainability, context | 15% | Significant changes |
Review Focus Areas
1. Correctness
Questions:
- Does it solve the stated problem?
- Are edge cases handled?
- Is error handling complete?
- Are assumptions valid?
Validation: Test coverage, business logic, data integrity, concurrency handling
2. Maintainability
Questions:
- Is the code self-documenting?
- Can it be easily modified?
- Are abstractions appropriate?
- Is complexity justified?
Indicators: Clear naming, single responsibility, minimal coupling, high cohesion
3. Performance
Questions:
- Are there obvious bottlenecks?
- Is caching appropriate?
- Are queries optimized?
- Is memory managed?
Red Flags: N+1 queries, unbounded loops, synchronous I/O in async context, memory leaks
4. Security
Questions:
- Is input validated?
- Are secrets protected?
- Is authentication checked?
- Are permissions verified?
Critical Checks: No hardcoded secrets, SQL parameterized, XSS prevention, CSRF tokens
Code Smells Checklist
Method Level
| Smell | Threshold | Action |
|---|
| Long method | > 50 lines | Extract method |
| Long parameter list | > 5 params | Parameter object |
| Duplicate code | > 10 similar lines | Extract common |
| Dead code | Never called | Remove |
Class Level
| Smell | Symptoms | Action |
|---|
| God class | > 1000 lines, > 20 methods | Split class |
| Feature envy | Uses other class data excessively | Move method |
| Data clumps | Same parameter groups | Extract class |
Architecture Level
| Smell | Detection | Action |
|---|
| Circular dependencies | Dependency cycles | Introduce interface |
| Unstable dependencies | Depends on volatile modules | Dependency inversion |
Comment Guidelines
Comment Types
[BLOCKING] - Must fix before merge
- Security vulnerabilities, data corruption risks, breaking API changes
[MAJOR] - Should fix before merge
- Missing tests, performance issues, code duplication
[MINOR] - Can fix in follow-up
- Style inconsistencies, documentation typos, naming improvements
[QUESTION] - Seeking clarification
- Design decisions, business logic, external dependencies
Effective Comment Pattern
Observation + Impact + Suggestion
Example:
"This method is 200 lines long [observation].
This makes it hard to understand and test [impact].
Consider extracting helper methods [suggestion]."
Avoid
- Vague: "This could be better"
- Personal: "I don't like this"
- Nitpicky: "Missing period in comment"
- Overwhelming: 50+ minor style issues
Review Readiness Checklist
Before Requesting Review
PR Description Should Include
- Problem statement (why this change?)
- Solution approach (how does it solve it?)
- Testing strategy (how verified?)
- Breaking changes (if any)
- Review focus areas (where to look closely?)
Complexity Thresholds
Cyclomatic Complexity
| Range | Classification | Action |
|---|
| 1-10 | Simple | OK |
| 11-20 | Moderate | Consider refactoring |
| 21-50 | Complex | Refactor required |
| > 50 | Untestable | Must decompose |
Cognitive Complexity
| Range | Classification |
|---|
| < 7 | Clear |
| 7-15 | Acceptable |
| > 15 | Confusing - refactor needed |
Anti-Patterns
Rubber Stamp
Approving without thorough review. "LGTM" in < 1 minute.
Fix: Minimum review time, required comments, random audits.
Nitpicking
50+ style comments, missing real issues.
Fix: Automate style checks, focus on logic/design, limit minor comments.
Big Bang Review
2000+ line PRs that overwhelm.
Fix: Stack small PRs, feature flags, review drafts early.
Security Scanning Categories
Severity Classification
| Level | Definition | SLA |
|---|
| Critical | Remote code execution possible | Fix immediately |
| High | Data breach possible | Fix within 24 hours |
| Medium | Limited impact | Fix within sprint |
| Low | Minimal risk | Fix when convenient |
Review Metrics
Efficiency
| Metric | Target |
|---|
| First review turnaround | < 4 hours |
| Review cycles | < 3 |
| PR to merge time | < 24 hours |
Quality
| Metric | Target |
|---|
| Defect detection rate | > 80% |
| Post-merge defects | < 0.5 per PR |
| Review coverage | 100% |
Related Skills
- github-agile - PR workflow and GitHub integration
- task-decomposition - If PR too large, break it down
- requirements-analysis - For unclear requirements
