Agent skill
code-review
Perform comprehensive code reviews covering bugs, style, performance, security, and best practices. Use this skill when the user mentions: review my code, check this code, code review, find bugs, improve code, refactor suggestions, security audit, performance optimization, code quality, static analysis.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/code-review-karmaloopai-jiva
Metadata
Additional technical details for this skill
- tags
-
code-quality security performance best-practices
- author
- Jiva Community
- version
- 1.0.0
SKILL.md
Code Review Skill
Overview
Perform comprehensive code reviews analyzing bugs, style issues, performance bottlenecks, security vulnerabilities, and adherence to best practices.
Workflow
1. Scan Code Structure
- Use
viewtool to read all relevant files in the codebase - Identify file types, frameworks, and languages used
- Map dependencies and module relationships
2. Analyze Code Quality
Check for the following categories:
Bugs & Logic Errors:
- Null/undefined handling
- Off-by-one errors
- Race conditions
- Memory leaks
- Incorrect algorithm implementation
Security Issues:
- SQL injection vulnerabilities
- XSS vulnerabilities
- Authentication/authorization flaws
- Sensitive data exposure
- Unsafe dependencies
Performance Problems:
- Inefficient algorithms (O(n²) where O(n) possible)
- Unnecessary database queries
- Memory overuse
- Blocking operations
- Missing caching
Code Style:
- Naming conventions
- Code formatting inconsistencies
- Magic numbers/strings
- Dead code
- Overly complex functions
Best Practices:
- DRY (Don't Repeat Yourself) violations
- SOLID principles adherence
- Error handling patterns
- Testing coverage
- Documentation quality
3. Categorize Findings
Group issues by:
- Critical: Security vulnerabilities, data loss risks
- High: Bugs that cause crashes/errors
- Medium: Performance issues, maintainability problems
- Low: Style issues, minor improvements
4. Provide Solutions
For each issue:
- Explain WHY it's a problem
- Show the problematic code snippet
- Provide a SPECIFIC fix with code examples
- Explain the benefits of the fix
5. Generate Report
Structure the output as:
# Code Review Report
## Summary
- Total files reviewed: X
- Issues found: Y (Z critical, W high, V medium, U low)
## Critical Issues
[List critical issues with fixes]
## High Priority Issues
[List high priority issues with fixes]
## Medium Priority Issues
[List medium priority issues with fixes]
## Low Priority Issues
[List low priority issues with fixes]
## Strengths
[Mention good practices found in the code]
## Recommendations
[Overall suggestions for improvement]
Resources
When to Use References
- Read
references/security_checklist.mdwhen analyzing security - Consult
references/performance_patterns.mdfor performance optimization - Check
references/language_guides/for language-specific best practices
Scripts (Future Enhancement)
scripts/run_linter.sh <file>- Run automated lintingscripts/complexity_analysis.py <file>- Calculate cyclomatic complexityscripts/security_scan.py <dir>- Run security vulnerability scanner
Example Usage
User: "Review this authentication code"
Process:
- Read authentication-related files with
viewtool - Check for common auth vulnerabilities (password storage, session management, etc.)
- Analyze token handling and encryption
- Check for privilege escalation risks
- Provide detailed report with fixes
Tips for Effective Reviews
- Be Specific: Don't just say "improve error handling" - show exactly how
- Prioritize: Focus on critical/high issues first
- Be Constructive: Acknowledge good code practices too
- Provide Context: Explain the "why" behind each suggestion
- Code Examples: Always show concrete before/after code
- Consider Trade-offs: Mention any downsides to suggested changes
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