AgentSkillsCN

Performance Engineering Standards

适用于所有框架的高性能软件开发通用标准。

SKILL.md
--- frontmatter
name: Performance Engineering Standards
description: Universal standards for high-performance software development across all frameworks.
metadata:
  labels: [performance, optimization, scalability, profiling]
  triggers:
    keywords: [performance, optimize, profile, scalability]

Performance Engineering Standards

Universal standards for high-performance software development across all frameworks.

Priority: P1 (OPERATIONAL)

Universal standards for building high-performance software across all frameworks and languages.

🚀 Core Principles

  • •Efficiency by Design: Minimize resource consumption (CPU, Memory, Network) without sacrificing readability.
  • •Measure First: Never optimize without a baseline. Use profiling tools before and after changes.
  • •Scalability: Design systems to handle increased load by optimizing time and space complexity.

💾 Resource Management

  • •Memory Efficiency:
    • •Avoid memory leaks: explicit cleanup of listeners, observers, and streams.
    • •Optimize data structures: use the most efficient collection for the use case (e.g., Set for lookups, List for iteration).
    • •Lazy Initialization: Initialize expensive objects only when needed.
  • •CPU Optimization:
    • •Algorithm Complexity: Aim for $O(1)$ or $O(n)$ where possible; avoid $O(n^2)$ in critical paths.
    • •Offload Work: Move heavy computations to background threads or workers.
    • •Minimize Re-computation: Use memoization for pure, expensive functions.

🌐 Network & I/O

  • •Payload Reduction: Use efficient serialization (JSON minification, Protobuf) and compression.
  • •Batching: Group multiple small requests into single bulk operations.
  • •Caching Strategy:
    • •Implement multi-level caching (Memory -> Storage -> Network).
    • •Use appropriate TTL (Time To Live) and invalidation strategies.
  • •Non-blocking I/O: Always use asynchronous operations for file system and network access.

⚡ UI/UX Performance

  • •Minimize Main Thread Work: Keep animations and interactions fluid by keeping the main thread free.
  • •Virtualization: Use lazy loading or virtualization for long lists/large datasets.
  • •Tree Shaking: Ensure build tools remove unused code and dependencies.

📊 Monitoring & Testing

  • •Benchmarking: Write micro-benchmarks for performance-critical functions.
  • •SLIs/SLOs: Define Service Level Indicators (latency, throughput) and Objectives.
  • •Load Testing: Test system behavior under peak and stress conditions.