code-review

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

• Feature fully implemented
• All tests written and passing
• Self-review performed
• No commented code or debug statements
• Coverage threshold met
• Linting clean
• Build succeeds
• Documentation updated
• PR description explains problem and solution

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