code-review

name

code-review

description

Review code written by Claude Code or humans across multiple languages. Use when asked to review, audit, critique, or analyze code quality. Supports R, Python, JavaScript, SQL, C++, Rust, Go, Ansible, Kustomize/Kubernetes, Dockerfiles, Docker Compose, and Bash. Covers correctness, security, performance, testing, documentation, and architecture. Produces actionable output for Claude Code to fix issues plus human-readable REVIEW.md summaries.

Code Review Skill

Review code for correctness, security, performance, testing, documentation, and architecture. Produces two outputs:

1. Structured findings for Claude Code to act on
2. REVIEW.md human-readable summary

Review Workflow

0. MANDATORY: Use context7 Before Any Code Changes

CRITICAL: Before creating, editing, or suggesting code changes, ALWAYS use context7 to look up current documentation.

When to use context7:

• Before suggesting fixes or improvements
• When reviewing library/framework usage
• Before writing code examples or snippets
• When uncertain about API behavior or best practices

How to use:

1. Resolve library: context7 resolve <library-name>
2. Get docs: context7 get-library-docs --library <library> --topic <topic>

Example:

context7 resolve react
context7 get-library-docs --library react --topic "useEffect dependencies"

1. Determine Review Scope

Identify what's being reviewed:

• Single file: Review that file
• Directory: Review all relevant files
• Diff/PR: Focus on changed lines with surrounding context
• Entire codebase: Start with entry points, follow dependencies

2. Select Review Depth

Choose automatically based on context, or accept user override:

Depth	When to Use	Focus
Quick	Small changes, trivial files, time-sensitive	Critical issues only
Standard	Most reviews, single files, typical PRs	All categories, balanced
Deep	Pre-production, security-sensitive, complex systems	Exhaustive, security-focused

3. Detect Languages and Load References

Identify languages present, then load relevant reference files:

• R → references/r.md
• Python → references/python.md
• JavaScript → references/javascript.md
• SQL → references/sql.md
• C++ → references/cpp.md
• Rust → references/rust.md
• Go → references/go.md
• Ansible → references/ansible.md
• Kubernetes/Kustomize → references/kubernetes.md
• Dockerfile → references/dockerfile.md
• Docker Compose → references/docker-compose.md
• Bash → references/bash.md

4. Use context7 MCP for Documentation (MANDATORY)

ALWAYS query context7 when:

• Reviewing ANY library/framework usage (not just unfamiliar ones)
• Before suggesting code changes or fixes
• Checking if APIs are used correctly
• Verifying deprecated patterns
• Confirming best practices for specific versions
• Writing code examples or snippets in review feedback

Process:

1. Identify libraries/frameworks in the code being reviewed
2. Use context7 resolve <library> for each one
3. Use context7 get-library-docs to verify API usage and patterns
4. Only THEN proceed with review findings

Example queries:

• context7 resolve react then context7 get-library-docs --library react --topic "hooks"
• context7 resolve tensorflow then context7 get-library-docs --library tensorflow --topic "layers"
• context7 resolve tidyverse for R tidyverse patterns
• context7 resolve kubernetes for K8s manifest validation
• context7 resolve express for Node.js API patterns

Never skip this step - outdated or incorrect documentation can lead to poor review suggestions.

5. Spawn Subagents for Parallel Review

Use subagents to parallelize review work:

Language Subagent (one per language detected):

Task: Review [language] code in [files] for idioms, patterns, and language-specific issues.
Focus: Style, idioms, language-specific performance, common pitfalls.
Reference: Load references/[language].md
Output: Structured findings list

Security Subagent:

Task: Analyze [files] for security vulnerabilities.
Focus: Injection, auth issues, secrets exposure, unsafe operations, dependency risks.
Output: Security findings with severity and remediation

Architecture Subagent:

Task: Review overall structure and design of [files/project].
Focus: Coupling, cohesion, separation of concerns, design patterns, testability.
Output: Architecture findings and recommendations

6. Review Categories

Each category produces findings with severity ratings.

Correctness

• Logic errors and bugs
• Edge cases not handled
• Off-by-one errors
• Null/undefined handling
• Type mismatches
• Race conditions

Security

• Injection vulnerabilities (SQL, command, XSS)
• Authentication/authorization flaws
• Secrets in code
• Unsafe deserialization
• Path traversal
• Dependency vulnerabilities

Performance

• Algorithmic complexity issues
• Unnecessary allocations
• N+1 queries
• Missing caching opportunities
• Blocking operations
• Memory leaks

Testing

• Missing test coverage
• Untested edge cases
• Brittle tests
• Missing integration tests
• Inadequate mocking

Documentation

• Missing function/class docstrings
• Outdated comments
• Unclear variable names
• Missing README updates
• Undocumented public APIs

Architecture

• Tight coupling
• God objects/functions
• Circular dependencies
• Layer violations
• Missing abstractions
• Poor separation of concerns

7. Classify Findings

Rate each finding:

Severity	Definition	Action
Critical	Security vulnerability, data loss risk, crash in production	Must fix before merge
Major	Significant bug, performance issue, maintainability blocker	Should fix before merge
Minor	Code smell, style issue, minor inefficiency	Fix when convenient
Nitpick	Preference, very minor style, optional improvement	Consider fixing

8. Generate Outputs

Output 1: Claude Code Action Format

Produce structured findings Claude Code can act on directly:

## File: [filepath]

### [Line X-Y]: [Brief title]
**Severity**: Critical|Major|Minor|Nitpick
**Category**: Correctness|Security|Performance|Testing|Documentation|Architecture

**Issue**: [Clear description of the problem]

**Current code**:
[relevant code snippet]

**Suggested fix**:
[corrected code snippet]

**Rationale**: [Why this change improves the code]

---

Group findings by file, ordered by severity (Critical first).

Output 2: REVIEW.md Human Summary

Write to REVIEW.md in the project root:

# Code Review Summary

**Reviewed**: [files/scope]
**Depth**: Quick|Standard|Deep
**Date**: [timestamp]

## Overview

[2-3 sentence summary of overall code quality and key concerns]

## Findings by Severity

### Critical ([count])
- [one-line summary with file:line reference]

### Major ([count])
- [one-line summary with file:line reference]

### Minor ([count])
- [one-line summary with file:line reference]

### Nitpicks ([count])
- [one-line summary with file:line reference]

## Category Breakdown

| Category | Critical | Major | Minor | Nitpick |
|----------|----------|-------|-------|---------|
| Correctness | X | X | X | X |
| Security | X | X | X | X |
| Performance | X | X | X | X |
| Testing | X | X | X | X |
| Documentation | X | X | X | X |
| Architecture | X | X | X | X |

## Recommendations

[Prioritized list of recommended actions]

## Positive Observations

[Things done well - important for balanced feedback]

9. Iterate on Critical/Major Issues

After generating outputs:

1. Use context7 to verify fix approaches before implementing
2. If user confirms, apply fixes for Critical and Major issues
3. Re-review changed code to verify fixes don't introduce new issues
4. Update REVIEW.md with resolution status

REMINDER: Use context7 to look up correct API usage before suggesting or implementing any code changes.