performance-principles
Performance guidelines and patterns for this system.
When & Why to Use This Skill
This Claude skill provides a comprehensive framework of performance guidelines and architectural patterns designed to optimize system efficiency, minimize latency, and ensure long-term scalability. It serves as a technical North Star for developers to balance code clarity with high-performance execution across both backend and frontend layers.
Use Cases
- Code Review Checklist: Use these principles as a standardized rubric during peer reviews to catch common pitfalls like N+1 queries, expensive computations, and synchronous bottlenecks.
- System Design & Planning: Apply the backend and frontend guidelines during the initial architecture phase to implement efficient query patterns, caching strategies, and lazy-loading from day one.
- Performance Auditing & Optimization: Evaluate existing legacy systems against the 'Common Pitfalls' to identify high-impact optimization targets and improve algorithmic efficiency.
- SLA & Monitoring Setup: Utilize the monitoring section to define performance budgets (e.g., 95th percentile latency) and implement essential instrumentation for critical system paths.
| name | performance-principles |
|---|---|
| description | Performance guidelines and patterns for this system. |
Performance Principles
General Principles
- Optimize for correct, clear code first; then optimize hot paths.
- Measure before optimizing when possible.
- Prefer algorithmic improvements over micro-optimizations.
Common Pitfalls
- N+1 queries in database access.
- Unbounded in-memory collections for large datasets.
- Synchronous calls in latency-sensitive paths.
- Repeated expensive computations without caching.
Guidelines by Layer
Backend
- Use efficient query patterns and indices.
- Batch calls where practical.
- Apply backpressure and rate limiting where needed.
Frontend
- Avoid unnecessary re-renders.
- Lazy-load heavy components and routes.
- Cache data appropriately (client & server).
Monitoring & Metrics
- Ensure critical paths have basic instrumentation:
- Latency, error rate, throughput.
- Define performance budgets (e.g., 95th percentile latency thresholds).
When to Escalate
- If a change risks breaching performance budgets.
- If complexity grows significantly (e.g., big-O behavior worsens).