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SKILL.md
Ai Code Reviewer
ASecurityAn intelligent, AI-powered code review assistant that analyzes code quality, identifies bugs, suggests improvements, and enforces best practices across multiple programming languages.
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- Added September 29, 2026
Works with
Security analysis
100/100Pro scans all 3 files and shows the line behind each finding
npx -y skills add Arry8/openclaw-edge --skill ai-code-reviewer --agent claude-codeAre you the author of Ai Code Reviewer?
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[](https://www.skillsdirectory.com/skills/arry8-ai-code-reviewer)# AI Code Reviewer
An intelligent, AI-powered code review assistant that analyzes code quality, identifies bugs, suggests improvements, and enforces best practices across multiple programming languages.
## Description
Use when: user asks to review code, analyze code quality, find bugs, suggest improvements, check for security vulnerabilities, or enforce coding standards.
NOT for: generating new code from scratch (use coding-agent), deploying code, or running tests.
## Capabilities
### 1. Code Quality Analysis
- Detect code smells and anti-patterns
- Identify complexity issues (cyclomatic complexity, cognitive complexity)
- Find duplicate code blocks
- Analyze code maintainability
### 2. Bug Detection
- Null pointer / undefined reference checks
- Type mismatches and casting issues
- Resource leaks (memory, file handles, connections)
- Race conditions and concurrency issues
- Off-by-one errors and boundary conditions
### 3. Security Analysis
- SQL injection vulnerabilities
- XSS (Cross-Site Scripting) risks
- CSRF vulnerabilities
- Hardcoded credentials detection
- Insecure cryptographic practices
- Input validation gaps
### 4. Performance Analysis
- N+1 query detection
- Unnecessary re-renders (React/Vue)
- Memory leak patterns
- Inefficient algorithms
- Blocking operations in async contexts
### 5. Best Practices Enforcement
- Language-specific conventions (PEP8, ESLint rules, etc.)
- Documentation coverage
- Test coverage suggestions
- Error handling patterns
- Logging best practices
## Supported Languages
| Language | Support Level | Special Features |
|----------|--------------|------------------|
| TypeScript/JavaScript | ⭐⭐⭐ Full | React, Node.js, Vue patterns |
| Python | ⭐⭐⭐ Full | Django, FastAPI, async patterns |
| Java | ⭐⭐⭐ Full | Spring Boot, concurrency |
| Go | ⭐⭐ High | Goroutines, channels |
| Rust | ⭐⭐ High | Ownership, lifetimes |
| C/C++ | ⭐⭐ High | Memory safety |
| Ruby | ⭐⭐ High | Rails patterns |
| PHP | ⭐⭐ High | Laravel, security |
| Swift | ⭐⭐ High | iOS patterns |
| Kotlin | ⭐⭐ High | Android, coroutines |
## Usage Examples
### Basic Code Review
```
Review this code for bugs and improvements:
function fetchUser(id) {
return fetch('/api/users/' + id)
.then(r => r.json())
}
```
### Security-Focused Review
```
Check this authentication code for security issues:
app.post('/login', (req, res) => {
const { username, password } = req.body;
const user = db.query(`SELECT * FROM users WHERE username='${username}'`);
// ...
});
```
### Performance Review
```
Analyze this React component for performance issues:
function UserList({ users }) {
const [filtered, setFiltered] = useState([]);
useEffect(() => {
setFiltered(users.filter(u => u.active));
}, [users]);
return filtered.map(u => <UserCard key={u.id} user={u} />);
}
```
## Output Format
The skill provides structured feedback in the following format:
```markdown
## Code Review Summary
**Overall Score:** 7.5/10
**Risk Level:** Medium
### 🔴 Critical Issues (Must Fix)
1. [SECURITY] SQL Injection vulnerability at line 15
- Current: `db.query(\`SELECT * FROM users WHERE id=${id}\`)`
- Fix: Use parameterized queries
- Impact: Data breach risk
### 🟡 Warnings (Should Fix)
1. [PERFORMANCE] N+1 query detected in loop at line 42
- Consider batch fetching
### 🟢 Suggestions (Nice to Have)
1. [STYLE] Consider extracting magic number to constant
2. [DOCS] Add JSDoc for public function
### ✅ Positive Observations
- Good error handling in async functions
- Consistent naming conventions
- Well-structured module organization
```
## Configuration
Add to your `openclaw.yaml`:
```yaml
skills:
ai-code-reviewer:
severity_threshold: warning # critical, warning, suggestion
languages:
- typescript
- python
- java
custom_rules:
- no-console-log
- require-error-handling
ignore_patterns:
- "**/*.test.ts"
- "**/generated/**"
```
## Integration with Git
The skill can automatically review:
- Staged changes before commit
- Pull request diffs
- Specific commits
```
Review my staged changes
Review PR #123
Review the last 3 commits
```
## API Reference
### `reviewCode(code: string, options?: ReviewOptions): Promise<ReviewResult>`
```typescript
interface ReviewOptions {
language?: string; // Auto-detected if not specified
severity?: 'critical' | 'warning' | 'suggestion';
focus?: ('security' | 'performance' | 'quality' | 'style')[];
context?: string; // Additional context about the code
maxIssues?: number; // Limit number of reported issues
}
interface ReviewResult {
score: number; // 0-10
riskLevel: 'low' | 'medium' | 'high' | 'critical';
issues: Issue[];
positives: string[];
summary: string;
suggestions: Suggestion[];
}
interface Issue {
id: string;
severity: 'critical' | 'warning' | 'suggestion';
category: string;
message: string;
line?: number;
column?: number;
fix?: string;
impact?: string;
}
```
## Best Practices for Using This Skill
1. **Provide context**: Tell the skill what the code is supposed to do
2. **Specify focus areas**: If you're only concerned about security, say so
3. **Include dependencies**: Mention frameworks/libraries being used
4. **Iterative review**: Fix critical issues first, then re-review
## Limitations
- Cannot execute code (static analysis only)
- May miss runtime-specific issues
- Custom framework patterns may need explicit context
- Large files (>1000 lines) are analyzed in chunks
## Related Skills
- `coding-agent`: For writing new code
- `github`: For PR integration
- `security`: For deeper security audits
Files in this skill
- SKILL.md
- package.json
- src/index.ts
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