skills/kaelen-hou/skills-mvp/code-review-assistant

code-review-assistant

SKILL.md

Code Review Assistant

Perform structured code reviews using checklists and automated analysis tools.

Review Workflow

  1. Gather context - Understand the scope of changes
  2. Run automated analysis - Execute scripts for metrics and security scans
  3. Apply checklists - Review using category-specific checklists
  4. Synthesize findings - Compile issues with severity and recommendations

Quick Start

For a standard code review:

# 1. View changes
git diff HEAD~1

# 2. Analyze code complexity and metrics
python scripts/analyze.py <file_or_directory>

# 3. Scan for security patterns (optional)
python scripts/security_scan.py <file_or_directory>

Then apply the appropriate checklists based on the code type.

Automated Analysis

Code Metrics Analysis

Run scripts/analyze.py to get code metrics:

python scripts/analyze.py path/to/code --output json
python scripts/analyze.py src/ --recursive

Outputs:

  • Lines of code (total, code, comments, blank)
  • Function/method count and average length
  • Cyclomatic complexity estimates
  • File-level metrics summary

Security Pattern Scan

Run scripts/security_scan.py for quick security checks:

python scripts/security_scan.py path/to/code
python scripts/security_scan.py src/ --severity high

Detects:

  • Dangerous function calls (eval, exec, shell injection)
  • Hardcoded credentials patterns
  • SQL injection indicators
  • XSS vulnerability patterns

Review Checklists

Select checklists based on the type of changes being reviewed:

Security Review

When to use: Authentication changes, user input handling, API endpoints, database queries

See SECURITY.md for complete security checklist covering:

  • Injection vulnerabilities (SQL, XSS, command injection)
  • Authentication and authorization
  • Data exposure and encryption
  • Input validation

Performance Review

When to use: Database operations, loops, API calls, data processing

See PERFORMANCE.md for performance checklist covering:

  • N+1 query detection
  • Memory management
  • Algorithmic complexity
  • Caching opportunities

Code Quality Review

When to use: All code changes, especially new features and refactoring

See QUALITY.md for quality checklist covering:

  • Naming conventions
  • Function complexity
  • DRY principle adherence
  • Error handling patterns

Review Output Format

Structure findings using this format:

## Code Review Summary

**Files reviewed**: [count]
**Issues found**: Critical: X | High: Y | Medium: Z | Low: W

### Critical Issues
1. **[File:Line]** Description
   - Code: `snippet`
   - Fix: Recommendation

### High Priority Issues
[Same format]

### Positive Observations
- [Note well-implemented patterns]

### Recommendations
1. [Prioritized action items]
Weekly Installs
3
GitHub Stars
1
First Seen
Feb 15, 2026
Installed on
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