code-review
Perform code reviews following Sentry engineering practices. Use when reviewing pull requests, examining code changes, or providing feedback on code quality. Covers security, performance, testing, and design review.
When & Why to Use This Skill
This Claude skill automates the code review process by applying Sentry's rigorous engineering standards to your development workflow. It helps teams maintain high code quality by systematically identifying runtime errors, performance bottlenecks like N+1 queries, security vulnerabilities, and architectural inconsistencies across Python, Django, TypeScript, and React codebases.
Use Cases
- Pull Request Auditing: Automatically review incoming pull requests to ensure they meet security, performance, and testing standards before human intervention.
- Performance Optimization: Detect inefficient ORM queries, unbounded operations, and unnecessary memory allocations that could impact system scalability.
- Security Hardening: Proactively identify potential SQL injection risks, XSS vulnerabilities, and improper access control gaps in new code changes.
- Architectural Alignment: Verify that new component interactions make logical sense and align with existing project patterns and long-term goals.
- Technical Debt Prevention: Flag breaking API changes or database schema modifications that lack proper migration paths or backwards compatibility.
| name | code-review |
|---|---|
| description | Perform code reviews following Sentry engineering practices. Use when reviewing pull requests, examining code changes, or providing feedback on code quality. Covers security, performance, testing, and design review. |
Sentry Code Review
Follow these guidelines when reviewing code for Sentry projects.
Review Checklist
Identifying Problems
Look for these issues in code changes:
- Runtime errors: Potential exceptions, null pointer issues, out-of-bounds access
- Performance: Unbounded O(n²) operations, N+1 queries, unnecessary allocations
- Side effects: Unintended behavioral changes affecting other components
- Backwards compatibility: Breaking API changes without migration path
- ORM queries: Complex Django ORM with unexpected query performance
- Security vulnerabilities: Injection, XSS, access control gaps, secrets exposure
Design Assessment
- Do component interactions make logical sense?
- Does the change align with existing project architecture?
- Are there conflicts with current requirements or goals?
Test Coverage
Every PR should have appropriate test coverage:
- Functional tests for business logic
- Integration tests for component interactions
- End-to-end tests for critical user paths
Verify tests cover actual requirements and edge cases. Avoid excessive branching or looping in test code.
Long-Term Impact
Flag for senior engineer review when changes involve:
- Database schema modifications
- API contract changes
- New framework or library adoption
- Performance-critical code paths
- Security-sensitive functionality
Feedback Guidelines
Tone
- Be polite and empathetic
- Provide actionable suggestions, not vague criticism
- Phrase as questions when uncertain: "Have you considered...?"
Approval
- Approve when only minor issues remain
- Don't block PRs for stylistic preferences
- Remember: the goal is risk reduction, not perfect code
Common Patterns to Flag
Python/Django
# Bad: N+1 query
for user in users:
print(user.profile.name) # Separate query per user
# Good: Prefetch related
users = User.objects.prefetch_related('profile')
TypeScript/React
// Bad: Missing dependency in useEffect
useEffect(() => {
fetchData(userId);
}, []); // userId not in deps
// Good: Include all dependencies
useEffect(() => {
fetchData(userId);
}, [userId]);
Security
# Bad: SQL injection risk
cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")
# Good: Parameterized query
cursor.execute("SELECT * FROM users WHERE id = %s", [user_id])