
Code Review
- 449 installs
- 30.1k repo stars
- Updated August 4, 2026
- davila7/claude-code-templates
This is a copy of code-review by getsentry - installs and ranking accrue to the original listing.
code-review is a Claude Code skill that applies Sentry engineering review checklists to pull requests for developers who need structured security, performance, testing, and design feedback before merging.
About
code-review is a davila7/claude-code-templates skill encoding Sentry engineering practices for agent-driven pull request review. Agents scan changes for runtime errors such as null pointer risks and out-of-bounds access, performance problems including unbounded O(n²) loops and N+1 queries, unintended side effects on other components, and backwards compatibility breaks. The skill triggers when reviewing pull requests, examining diffs, or giving code quality feedback across security, performance, testing, and design dimensions. It complements generic review prompts with Sentry-specific expectations rather than subjective nitpicking. Developers reach for code-review when Claude agents must audit Sentry-style Python or backend changes before merge, especially when teams want consistent checklist coverage instead of ad hoc comments on each pull request during ship-phase quality gates and pre-release reviews.
- Runs 12 distinct review modes including architecture, security, performance and readability
- Produces severity-bucketed findings with concrete remediation steps
- Works directly with Claude Code, Cursor and generic LLM agents
- Hard-gate: never merge without first running full review checklist
- Outputs annotated diff + summary report for next-skill handoff
Code Review by the numbers
- 449 all-time installs (skills.sh)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 449 |
|---|---|
| repo stars | ★ 30.1k |
| Last updated | August 4, 2026 |
| Repository | davila7/claude-code-templates ↗ |
How do you review pull requests with Sentry standards?
Get structured, high-signal feedback on code changes before merging.
Who is it for?
Developers on Sentry-style codebases who want Claude agents to review PRs with a consistent runtime, performance, and compatibility checklist.
Skip if: Teams needing framework-specific reviews such as Flutter or PostgreSQL-only audits where Sentry general backend checklist is too narrow.
When should I use this skill?
The user asks to review a pull request, examine code changes, or provide Sentry-style feedback on quality, security, or performance.
What you get
Structured review comments on security, performance, testing gaps, design issues, and backwards-compatibility risks.
- Structured PR review feedback
- Pre-merge risk and compatibility notes
By the numbers
- Review checklist spans four problem classes: runtime, performance, side effects, and backwards compatibility
Files
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])References
Related skills
How it compares
Pick code-review over generic review skills when Sentry-style backend checklist coverage on runtime and compatibility matters more than SOLID-only templates.
FAQ
What issues does the Sentry code-review skill prioritize?
code-review prioritizes runtime errors like null pointers and out-of-bounds access, performance problems such as O(n²) operations and N+1 queries, unintended side effects on other components, and backwards compatibility breaks. It also covers security, testing, and design review
When should Claude agents invoke code-review?
code-review triggers when reviewing pull requests, examining code changes, or providing feedback on code quality. Agents follow the Sentry checklist rather than subjective nitpicks, making it suitable for pre-merge audits requested explicitly or when quality gates are needed on d