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code-review

code-review

github.com/jwyniaTesting & quality180499 installsUpdated 35w ago
Repository

About code-review

code-review is a systematic review skill for human reviewers and AI agents, intended for pre-merge checks, self-review, and PR preparation. It organizes checks around correctness, maintainability, performance, and security, with comment categories and a readiness checklist.

Key features

  1. 01Check correctness and edge cases
  2. 02Assess maintainability and code smells
  3. 03Inspect performance and security risks
  4. 04Organize comments by severity
  5. 05Use a PR readiness checklist

Use cases

  1. 01Review code changes before merge
  2. 02Self-review before submitting a PR
  3. 03Assess code quality and provide categorized feedback

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/jwynia/agent-skills --skill code-review

After installing, type/code-reviewin Claude Code to confirm it loaded.

Details

From the project README

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

FactorOptimalDegraded
PR size< 400 lines> 800 lines
Review time< 60 minutes> 90 minutes
Review speed200-400 LOC/hour> 500 LOC/hour
Reviewers24+ (diminishing returns)

Quality Pyramid

LevelChecksCatchesFrequency
1. AutomatedLint, types, unit tests, security scan60%Every commit
2. IntegrationIntegration tests, contracts, performance25%Every PR
3. Human ReviewDesign, logic, maintainability, context15%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
SmellThresholdAction
Long method> 50 linesExtract method
Long parameter list> 5 paramsParameter object
Duplicate code> 10 similar linesExtract common
Dead codeNever calledRemove
Class Level
SmellSymptomsAction
God class> 1000 lines, > 20 methodsSplit class
Feature envyUses other class data excessivelyMove method
Data clumpsSame parameter groupsExtract class
Architecture Level
SmellDetectionAction
Circular dependenciesDependency cyclesIntroduce interface
Unstable dependenciesDepends on volatile modulesDependency 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
RangeClassificationAction
1-10SimpleOK
11-20ModerateConsider refactoring
21-50ComplexRefactor required
> 50UntestableMust decompose
Cognitive Complexity
RangeClassification
< 7Clear
7-15Acceptable
> 15Confusing - 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
LevelDefinitionSLA
CriticalRemote code execution possibleFix immediately
HighData breach possibleFix within 24 hours
MediumLimited impactFix within sprint
LowMinimal riskFix when convenient

Review Metrics

Efficiency
MetricTarget
First review turnaround< 4 hours
Review cycles< 3
PR to merge time< 24 hours
Quality
MetricTarget
Defect detection rate> 80%
Post-merge defects< 0.5 per PR
Review coverage100%

Related Skills

  • github-agile - PR workflow and GitHub integration
  • task-decomposition - If PR too large, break it down
  • requirements-analysis - For unclear requirements

Comments

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