code-review · jwynia — Claude Code skill: structured code review
A skill that gives code review a shape: what to check for correctness, security and performance, how to phrase comments, when a PR is too big.
npx skills add jwynia/agent-skills --skill code-review -a claude-codeWhat code-review does
The skill lays out a review method rather than running a linter. It names four focus areas: correctness, maintainability, performance and security. Each comes with questions to ask of a diff and with red flags such as N+1 queries, unbounded loops and synchronous I/O inside async code.
There is a code smell checklist with thresholds: a method past 50 lines, more than 5 parameters, duplication from 10 similar lines. Comments get severity tags — [BLOCKING], [MAJOR], [MINOR], [QUESTION] — and a pattern of observation, impact, suggestion. Tables cover cyclomatic and cognitive complexity ranges.
One point the skill keeps returning to: review effectiveness drops as the PR grows. Under 400 lines detection is at its best, past 800 it falls off by 90%. So a bloated diff is a reason to split it, not to read harder. The skill works with any programming language and pairs with github-agile for the PR workflow. It does not write new code or design architecture — other skills in the set handle that.
What it helps with
- check a diff before merge against one list
- tell a blocking issue from a style nit
- write a review comment that is not just a preference
- decide whether a large PR should be split
- self-review code before asking anyone else
Example prompts for the agent
- Review this PR with the code-review skill and sort findings by severity
- Check
src/orders/service.pyfor code smells and security problems - Rate the cyclomatic complexity of these methods and tell me what to refactor
How to install code-review
1Skills CLI (Vercel)
npx skills add jwynia/agent-skills --skill code-review -a claude-code2Manually: put the files in place
~/.claude/skills/code-review/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/code-review/
1Skills CLI (Vercel)
npx skills add jwynia/agent-skills --skill code-review -a codex2Manually: put the files in place
.agents/skills/code-review/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add jwynia/agent-skills --skill code-review -a cursor2Manually: put the files in place
.cursor/skills/code-review/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install jwynia/agent-skills code-review2Manually: put the files in place
.github/skills/code-review/SKILL.md1Skills CLI (Vercel)
npx skills add jwynia/agent-skills --skill code-review -a gemini-cli2Platform CLI
gemini skills install https://github.com/jwynia/agent-skills --path skills/tech/development/quality/code-reviewManually: put the files in place
.devin/skills/code-review/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add jwynia/agent-skills --skill code-review -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about code-review
How do I install code-review in Claude?
Run npx skills add jwynia/agent-skills --skill code-review -a claude-code. The skill file lands at ~/.claude/skills/code-review/SKILL.md.
What does code-review do?
It supplies a review structure: focus areas, a code smell checklist, complexity thresholds and comment conventions. Both a human reviewer and an agent get a systematic way to read code.
Which languages does the skill support?
Any programming language. For the PR workflow it integrates with github-agile.
Source text
SKILL.md · MIT
--- 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
© jwynia · MIT · jwynia/agent-skills
Similar skills
Everything for Code review and refactoring →code-review by other authors comes first.