NYC
skills/smithery/ai/code-review

code-review

SKILL.md

Code Review Skill

Conduct a thorough code review for quality, security, and maintainability with severity-rated feedback.

When to Use

This skill activates when:

  • User requests "review this code", "code review"
  • Before merging a pull request
  • After implementing a major feature
  • User wants quality assessment

What It Does

Delegates to the code-reviewer agent (Opus model) for deep analysis:

  1. Identify Changes

    • Run git diff to find changed files
    • Determine scope of review (specific files or entire PR)
  2. Review Categories

    • Security - Hardcoded secrets, injection risks, XSS, CSRF
    • Code Quality - Function size, complexity, nesting depth
    • Performance - Algorithm efficiency, N+1 queries, caching
    • Best Practices - Naming, documentation, error handling
    • Maintainability - Duplication, coupling, testability
  3. Severity Rating

    • CRITICAL - Security vulnerability (must fix before merge)
    • HIGH - Bug or major code smell (should fix before merge)
    • MEDIUM - Minor issue (fix when possible)
    • LOW - Style/suggestion (consider fixing)
  4. Specific Recommendations

    • File:line locations for each issue
    • Concrete fix suggestions
    • Code examples where applicable

Agent Delegation

Task(
  subagent_type="oh-my-claudecode:code-reviewer",
  model="opus",
  prompt="CODE REVIEW TASK

Review code changes for quality, security, and maintainability.

Scope: [git diff or specific files]

Review Checklist:
- Security vulnerabilities (OWASP Top 10)
- Code quality (complexity, duplication)
- Performance issues (N+1, inefficient algorithms)
- Best practices (naming, documentation, error handling)
- Maintainability (coupling, testability)

Output: Code review report with:
- Files reviewed count
- Issues by severity (CRITICAL, HIGH, MEDIUM, LOW)
- Specific file:line locations
- Fix recommendations
- Approval recommendation (APPROVE / REQUEST CHANGES / COMMENT)"
)

External Model Consultation (Preferred)

The code-reviewer agent SHOULD consult Codex for cross-validation.

Protocol

  1. Form your OWN review FIRST - Complete the review independently
  2. Consult for validation - Cross-check findings with Codex
  3. Critically evaluate - Never blindly adopt external findings
  4. Graceful fallback - Never block if tools unavailable

When to Consult

  • Security-sensitive code changes
  • Complex architectural patterns
  • Unfamiliar codebases or languages
  • High-stakes production code

When to Skip

  • Simple refactoring
  • Well-understood patterns
  • Time-critical reviews
  • Small, isolated changes

Tool Usage

Before first MCP tool use, call ToolSearch("mcp") to discover deferred MCP tools. Use mcp__x__ask_codex with agent_role: "code-reviewer". If ToolSearch finds no MCP tools, fall back to the code-reviewer Claude agent.

Note: Codex calls can take up to 1 hour. Consider the review timeline before consulting.

Output Format

CODE REVIEW REPORT
==================

Files Reviewed: 8
Total Issues: 15

CRITICAL (0)
-----------
(none)

HIGH (3)
--------
1. src/api/auth.ts:42
   Issue: User input not sanitized before SQL query
   Risk: SQL injection vulnerability
   Fix: Use parameterized queries or ORM

2. src/components/UserProfile.tsx:89
   Issue: Password displayed in plain text in logs
   Risk: Credential exposure
   Fix: Remove password from log statements

3. src/utils/validation.ts:15
   Issue: Email regex allows invalid formats
   Risk: Accepts malformed emails
   Fix: Use proven email validation library

MEDIUM (7)
----------
...

LOW (5)
-------
...

RECOMMENDATION: REQUEST CHANGES

Critical security issues must be addressed before merge.

Review Checklist

The code-reviewer agent checks:

Security

  • No hardcoded secrets (API keys, passwords, tokens)
  • All user inputs sanitized
  • SQL/NoSQL injection prevention
  • XSS prevention (escaped outputs)
  • CSRF protection on state-changing operations
  • Authentication/authorization properly enforced

Code Quality

  • Functions < 50 lines (guideline)
  • Cyclomatic complexity < 10
  • No deeply nested code (> 4 levels)
  • No duplicate logic (DRY principle)
  • Clear, descriptive naming

Performance

  • No N+1 query patterns
  • Appropriate caching where applicable
  • Efficient algorithms (avoid O(n²) when O(n) possible)
  • No unnecessary re-renders (React/Vue)

Best Practices

  • Error handling present and appropriate
  • Logging at appropriate levels
  • Documentation for public APIs
  • Tests for critical paths
  • No commented-out code

Approval Criteria

APPROVE - No CRITICAL or HIGH issues, minor improvements only REQUEST CHANGES - CRITICAL or HIGH issues present COMMENT - Only LOW/MEDIUM issues, no blocking concerns

Use with Other Skills

With Pipeline:

/pipeline review "implement user authentication"

Includes code review as part of implementation workflow.

With Ralph:

/ralph code-review then fix all issues

Review code, get feedback, fix until approved.

With Ultrawork:

/ultrawork review all files in src/

Parallel code review across multiple files.

Best Practices

  • Review early - Catch issues before they compound
  • Review often - Small, frequent reviews better than huge ones
  • Address CRITICAL/HIGH first - Fix security and bugs immediately
  • Consider context - Some "issues" may be intentional trade-offs
  • Learn from reviews - Use feedback to improve coding practices
Weekly Installs
2
Repository
smithery/ai
First Seen
13 days ago
Installed on
claude-code2
mcpjam1
openhands1
junie1
windsurf1
zencoder1