@noanswer/context-compose/assets/rules/performance-best-practices.yaml

Orchestrate complex AI interactions with Context Compose. A powerful CLI and server for building, validating, and managing context for large language models using the Model Context Protocol (MCP).

version: 1
kind: rule
name: Performance Best Practices
description: Guidelines for writing high-performance, scalable, and efficient code.
prompt: |
  Choose efficient algorithms and data structures, and minimize unnecessary computations.
  Optimize network requests, reduce bundle size, and actively use lazy loading.
  Prevent memory leaks and profile code execution time to resolve bottlenecks.
  Actively implement caching strategies to speed up repetitive data access.
enhanced-prompt: |-
  ### Algorithms & Data Structures
  - **Efficient Selection**: Choose the most appropriate algorithms and data structures for the problem. Always consider time and space complexity to prevent performance degradation.
  - **Computation Optimization**: Minimize unnecessary or redundant calculations. Avoid repetitive computations within loops and use memoization to store and reuse results.

  ### Frontend Optimization
  - **Rendering Optimization**: Understand the browser rendering pipeline and minimize reflows and repaints. In frameworks using a virtual DOM, prevent unnecessary re-renders.
  - **Bundle Size Optimization**: Minimize JavaScript bundle size using techniques like tree shaking and code splitting. Compress assets like images and use modern formats like WebP.
  - **Loading Optimization**: Use lazy loading to defer the loading of non-critical components, images, and scripts. Inline critical CSS to speed up initial rendering.

  ### Backend & Network Optimization
  - **Database Optimization**: Optimize queries and create appropriate indexes to reduce database response times. Be wary of N+1 query problems and fetch only necessary data.
  - **Network Request Optimization**: Reduce the number of API requests and minimize payload size. Utilize HTTP/2 or HTTP/3 and use a CDN to deliver static content quickly.
  - **Caching Strategy**: Use in-memory caches (e.g., Redis, Memcached) or HTTP caching to reduce repetitive database queries or API calls. Establish a clear cache invalidation strategy.

  ### Code-Level Optimization
  - **Memory Management**: Prevent memory leaks by cleaning up event listeners, timers, and subscriptions when components are unmounted. Use WeakMap and WeakSet to aid garbage collection.
  - **Asynchronous Processing**: Convert synchronous, blocking code to asynchronous code to reduce the load on the main thread. Consider using Web Workers to offload heavy computations to a background thread.

  ### Measurement & Monitoring
  - **Profiling**: Regularly use browser developer tools (Lighthouse, Performance) or Node.js profilers to measure and analyze bottlenecks in your code.
  - **Performance Budgets**: Set performance budgets for key metrics like Core Web Vitals (e.g., LCP, TTI) and continuously monitor them in the CI/CD pipeline to prevent performance regressions.