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wulawuluwulawulu/learn-claude-code-rs/skills/code-review/SKILL.md

code-review

Skill154 starsChanged 7 months agoMITView on GitHub

Perform thorough code reviews with security, performance, and maintainability analysis. Use when user asks to review code, check for bugs, or audit a codebase.

  • Installs packages

219 other projects use a version of this; 1 new project in the last 4 weeks, against 1 the 4 before.

Adopted by

Steady: 1 new project took it in the last 4 weeks, 1× the 4 weeks before.thin data

Week of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 1 new projectWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projectsWeek of Oct 25: 1 new projectWeek of Nov 1: 0 new projects
Sep 2026Oct 2026Nov 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 2 in all, so this is a hint, not a trend.

Most recently taken up by

Used with

Projects with it also use close-spec, design-with-images and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • dzhngSkill

    close-spec

    When a spec under specs/<feature>/ is done shipping (a write-spec build, or any planned task that produced a spec), archive it to specs/done/ and rewrite it from a build-plan into a durable rationale — the why, the principles, the invariants — pointing back to the real code for the how. Use when implementation has landed and the plan no longer matches what shipped, or the user says a feature/spec is finished. Pairs with [write-spec](../write-spec/SKILL.md) (the plan this closes) and [review](../review/SKILL.md) (run before closing).

    Also in 5 projects that use this

  • dzhngSkill

    design-with-images

    Explore UI and visual design with image generation, then iterate the real implementation against the user-selected concept. Use when brainstorming visual directions, offering mockup variants, or implementing an approved generated design; do not stop at the mockups or the first code approximation.

    Also in 5 projects that use this

  • PydanticSkill

    add-new-model

    Add support for a newly-released language or image generation model in pydantic-ai (e.g. openai:gpt-5.6, anthropic:claude-sonnet-5, openai:gpt-image-2). Use when a provider ships a new model id and you need to wire literals, profile flags, adapters, and tests to recognize it. Handles SDK-lag, gateway list conventions, capability probing, and direct image-model geometry.

    Also in 9 projects that use this

  • transitive-bullshitSkill

    compare-screenshots

    Compare screenshots against the intended design, distinguishing approved references from historical baselines. Use for iterative implementation matching, before/after visual review, objective image telemetry, or checking a lone capture for flat, empty, or badly framed content.

    Also in 5 projects that use this

  • Microsoft AzureSkill

    azsdk-common-apiview-feedback-resolution

    Analyze and resolve APIView review feedback on Azure SDK PRs. **UTILITY SKILL**. USE FOR: APIView comments, API review feedback, SDK API surface changes. DO NOT USE FOR: general code review, non-APIView feedback. INVOKES: azure-sdk-mcp:azsdk_apiview_get_comments, azure-sdk-mcp:azsdk_customized_code_update, azure-sdk-mcp:azsdk_typespec_delegate_apiview_feedback, azure-sdk-mcp:azsdk_run_typespec_validation, azure-sdk-mcp:azsdk_package_generate_code.

    Also in 6 projects that use this

  • Microsoft AzureSkill

    azsdk-common-generate-sdk-locally

    Generate and finalize Azure SDKs locally from TypeSpec, including build, checks, tests, changelog, metadata, and version updates by default. WHEN: "generate SDK locally", "build SDK", "run SDK tests", "run CI checks", "validate package", "run checks", "update changelog", "fix SDK build errors", "resolve SDK generation errors", "customize TypeSpec", "rename SDK client", "rename SDK model", "hide operation from SDK", "fix analyzer errors", "resolve customization drift", "create subclient", "update metadata", "update version". INVOKES: azsdk_verify_setup, azsdk_package_generate_code, azsdk_package_build_code, azsdk_package_run_check, azsdk_package_run_tests, azsdk_customized_code_update, azsdk_package_update_changelog_content, azsdk_package_update_metadata, azsdk_package_update_version.

    Also in 6 projects that use this

  • +4 more from dzhng
  • +2 more from Azure

The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 182 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Understand context: Read PR description, linked issues

    line 151
  2. Distinctive:

    Read top-down: Start with main entry points

    line 153
  3. Distinctive:

    Security scan: Run automated tools

    line 155
  4. Distinctive:

    Manual review: Use checklist above

    line 156

“Common” is measured: kept by at least 6 in 10 of the 182 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Code Review Skill

You now have expertise in conducting comprehensive code reviews. Follow this structured approach:

Review Checklist

1. Security (Critical)

Check for:

  • Injection vulnerabilities: SQL, command, XSS, template injection
  • Authentication issues: Hardcoded credentials, weak auth
  • Authorization flaws: Missing access controls, IDOR
  • Data exposure: Sensitive data in logs, error messages
  • Cryptography: Weak algorithms, improper key management
  • Dependencies: Known vulnerabilities (check with npm audit, pip-audit)
# Quick security scans
npm audit                    # Node.js
pip-audit                    # Python
cargo audit                  # Rust
grep -r "password\|secret\|api_key" --include="*.py" --include="*.js"

2. Correctness

Check for:

  • Logic errors: Off-by-one, null handling, edge cases
  • Race conditions: Concurrent access without synchronization
  • Resource leaks: Unclosed files, connections, memory
  • Error handling: Swallowed exceptions, missing error paths
  • Type safety: Implicit conversions, any types

3. Performance

Check for:

  • N+1 queries: Database calls in loops
  • Memory issues: Large allocations, retained references
  • Blocking operations: Sync I/O in async code
  • Inefficient algorithms: O(n^2) when O(n) possible
  • Missing caching: Repeated expensive computations

4. Maintainability

Check for:

  • Naming: Clear, consistent, descriptive
  • Complexity: Functions > 50 lines, deep nesting > 3 levels
  • Duplication: Copy-pasted code blocks
  • Dead code: Unused imports, unreachable branches
  • Comments: Outdated, redundant, or missing where needed

5. Testing

Check for:

  • Coverage: Critical paths tested
  • Edge cases: Null, empty, boundary values
  • Mocking: External dependencies isolated
  • Assertions: Meaningful, specific checks

Review Output Format

## Code Review: [file/component name]

### Summary
[1-2 sentence overview]

### Critical Issues
1. **[Issue]** (line X): [Description]
   - Impact: [What could go wrong]
   - Fix: [Suggested solution]

### Improvements
1. **[Suggestion]** (line X): [Description]

### Positive Notes
- [What was done well]

### Verdict
[ ] Ready to merge
[ ] Needs minor changes
[ ] Needs major revision

Common Patterns to Flag

Python

# Bad: SQL injection
cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")
# Good:
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))

# Bad: Command injection
os.system(f"ls {user_input}")
# Good:
subprocess.run(["ls", user_input], check=True)

# Bad: Mutable default argument
def append(item, lst=[]):  # Bug: shared mutable default
# Good:
def append(item, lst=None):
    lst = lst or []

JavaScript/TypeScript

// Bad: Prototype pollution
Object.assign(target, userInput)
// Good:
Object.assign(target, sanitize(userInput))

// Bad: eval usage
eval(userCode)
// Good: Never use eval with user input

// Bad: Callback hell
getData(x => process(x, y => save(y, z => done(z))))
// Good:
const data = await getData();
const processed = await process(data);
await save(processed);

Review Commands

# Show recent changes
git diff HEAD~5 --stat
git log --oneline -10

# Find potential issues
grep -rn "TODO\|FIXME\|HACK\|XXX" .
grep -rn "password\|secret\|token" . --include="*.py"

# Check complexity (Python)
pip install radon && radon cc . -a

# Check dependencies
npm outdated  # Node
pip list --outdated  # Python

Review Workflow

  1. Understand context: Read PR description, linked issues
  2. Run the code: Build, test, run locally if possible
  3. Read top-down: Start with main entry points
  4. Check tests: Are changes tested? Do tests pass?
  5. Security scan: Run automated tools
  6. Manual review: Use checklist above
  7. Write feedback: Be specific, suggest fixes, be kind

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