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Code Review Assistant

ASecurity

Comprehensive code review assistant that analyzes code for security vulnerabilities, performance issues, and code quality. Use when reviewing pull requests, conducting code audits, or analyzing code changes. Supports Python, JavaScript/TypeScript, and general code patterns. Includes automated analysis scripts and structured checklists.

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  • Added October 17, 2026
securityjavascripttypescriptpythongojavashellbashsqlrefactoringcode-review

Works with

  • api

Security analysis

A100/100

Scanned October 17, 2026

npx -y skills add diegosouzapw/awesome-omni-skill --skill code-review-assistant --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: code-review-assistant
description: Comprehensive code review assistant that analyzes code for security vulnerabilities, performance issues, and code quality. Use when reviewing pull requests, conducting code audits, or analyzing code changes. Supports Python, JavaScript/TypeScript, and general code patterns. Includes automated analysis scripts and structured checklists.
allowed-tools: Read, Grep, Glob, Bash
---

# 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:

```bash
# 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:

```bash
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:

```bash
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](references/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](references/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](references/QUALITY.md) for quality checklist covering:
- Naming conventions
- Function complexity
- DRY principle adherence
- Error handling patterns

## Review Output Format

Structure findings using this format:

```markdown
## 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]
```

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