code-review-assistant
npx skills add https://github.com/kaelen-hou/skills-mvp --skill code-review-assistant
Agent 安装分布
Skill 文档
Code Review Assistant
Perform structured code reviews using checklists and automated analysis tools.
Review Workflow
- Gather context – Understand the scope of changes
- Run automated analysis – Execute scripts for metrics and security scans
- Apply checklists – Review using category-specific checklists
- 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]