lanlinju 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- Comments: Outdated, redundant, or missing where needed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
- Understand context: Read PR description, linked issues
- Run the code: Build, test, run locally if possible
- Read top-down: Start with main entry points
- Check tests: Are changes tested? Do tests pass?
- Security scan: Run automated tools
- Manual review: Use checklist above
- Write feedback: Be specific, suggest fixes, be kind