shareai-lab/code-review

Code Review Skill

You now have expertise in conducting comprehensive code reviews. Follow this structured approach:

Review Checklist

1. Security (Critical)

Check for:

• [ ] Injection vulnerabilities: SQL, command, XSS, template injection
• [ ] Authentication issues: Hardcoded credentials, weak auth
• [ ] Authorization flaws: Missing access controls, IDOR
• [ ] Data exposure: Sensitive data in logs, error messages
• [ ] Cryptography: Weak algorithms, improper key management
• [ ] Dependencies: Known vulnerabilities (check with npm audit, pip-audit)

# Quick security scans
npm audit                    # Node.js
pip-audit                    # Python
cargo audit                  # Rust
grep -r "password\|secret\|api_key" --include="*.py" --include="*.js"

2. Correctness

Check for:

• [ ] Logic errors: Off-by-one, null handling, edge cases
• [ ] Race conditions: Concurrent access without synchronization
• [ ] Resource leaks: Unclosed files, connections, memory
• [ ] Error handling: Swallowed exceptions, missing error paths
• [ ] Type safety: Implicit conversions, any types

3. Performance

Check for:

• [ ] N+1 queries: Database calls in loops
• [ ] Memory issues: Large allocations, retained references
• [ ] Blocking operations: Sync I/O in async code
• [ ] Inefficient algorithms: O(n^2) when O(n) possible
• [ ] Missing caching: Repeated expensive computations

4. Maintainability

Check for:

• [ ] Naming: Clear, consistent, descriptive
• [ ] Complexity: Functions > 50 lines, deep nesting > 3 levels
• [ ] Duplication: Copy-pasted code blocks
• [ ] Dead code: Unused imports, unreachable branches
• [ ] Comments: Outdated, redundant, or missing where needed

5. Testing

Check for:

• [ ] Coverage: Critical paths tested
• [ ] Edge cases: Null, empty, boundary values
• [ ] Mocking: External dependencies isolated
• [ ] Assertions: Meaningful, specific checks

Review Output Format

## Code Review: [file/component name]

### Summary
[1-2 sentence overview]

### Critical Issues
1. **[Issue]** (line X): [Description]
   - Impact: [What could go wrong]
   - Fix: [Suggested solution]

### Improvements
1. **[Suggestion]** (line X): [Description]

### Positive Notes
- [What was done well]

### Verdict
[ ] Ready to merge
[ ] Needs minor changes
[ ] Needs major revision

Common Patterns to Flag

Python

# Bad: SQL injection
cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")
# Good:
cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))

# Bad: Command injection
os.system(f"ls {user_input}")
# Good:
subprocess.run(["ls", user_input], check=True)

# Bad: Mutable default argument
def append(item, lst=[]):  # Bug: shared mutable default
# Good:
def append(item, lst=None):
    lst = lst or []

JavaScript/TypeScript

// Bad: Prototype pollution
Object.assign(target, userInput)
// Good:
Object.assign(target, sanitize(userInput))

// Bad: eval usage
eval(userCode)
// Good: Never use eval with user input

// Bad: Callback hell
getData(x => process(x, y => save(y, z => done(z))))
// Good:
const data = await getData();
const processed = await process(data);
await save(processed);

Review Commands

# Show recent changes
git diff HEAD~5 --stat
git log --oneline -10

# Find potential issues
grep -rn "TODO\|FIXME\|HACK\|XXX" .
grep -rn "password\|secret\|token" . --include="*.py"

# Check complexity (Python)
pip install radon && radon cc . -a

# Check dependencies
npm outdated  # Node
pip list --outdated  # Python

Review Workflow

1. Understand context: Read PR description, linked issues
2. Run the code: Build, test, run locally if possible
3. Read top-down: Start with main entry points
4. Check tests: Are changes tested? Do tests pass?
5. Security scan: Run automated tools
6. Manual review: Use checklist above
7. Write feedback: Be specific, suggest fixes, be kind