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    zhaono1

    performance-engineer

    zhaono1/performance-engineer
    Coding
    4

    About

    SKILL.md

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    About

    Performance optimization specialist for improving application speed and efficiency. Use when investigating performance issues or optimizing code.

    SKILL.md

    Performance Engineer

    Specialist in analyzing and optimizing application performance, identifying bottlenecks, and implementing efficiency improvements.

    When This Skill Activates

    Activates when you:

    • Report performance issues
    • Need performance optimization
    • Mention "slow" or "latency"
    • Want to improve efficiency

    Performance Analysis Process

    Phase 1: Identify the Problem

    1. Define metrics

      • What's the baseline?
      • What's the target?
      • What's acceptable?
    2. Measure current performance

      # Response time
      curl -w "@curl-format.txt" -o /dev/null -s https://example.com/users
      
      # Database query time
      # Add timing logs to queries
      
      # Memory usage
      # Use profiler
      
    3. Profile the application

      # Node.js
      node --prof app.js
      
      # Python
      python -m cProfile app.py
      
      # Go
      go test -cpuprofile=cpu.prof
      

    Phase 2: Find the Bottleneck

    Common bottleneck locations:

    Layer Common Issues
    Database N+1 queries, missing indexes, large result sets
    API Over-fetching, no caching, serial requests
    Application Inefficient algorithms, excessive logging
    Frontend Large bundles, re-renders, no lazy loading
    Network Too many requests, large payloads, no compression

    Phase 3: Optimize

    Database Optimization

    N+1 Queries:

    // Bad: N+1 queries
    const users = await User.findAll();
    for (const user of users) {
      user.posts = await Post.findAll({ where: { userId: user.id } });
    }
    
    // Good: Eager loading
    const users = await User.findAll({
      include: [{ model: Post, as: 'posts' }]
    });
    

    Missing Indexes:

    -- Add index on frequently queried columns
    CREATE INDEX idx_user_email ON users(email);
    CREATE INDEX idx_post_user_id ON posts(user_id);
    

    API Optimization

    Pagination:

    // Always paginate large result sets
    const users = await User.findAll({
      limit: 100,
      offset: page * 100
    });
    

    Field Selection:

    // Select only needed fields
    const users = await User.findAll({
      attributes: ['id', 'name', 'email']
    });
    

    Compression:

    // Enable gzip compression
    app.use(compression());
    

    Frontend Optimization

    Code Splitting:

    // Lazy load routes
    const Dashboard = lazy(() => import('./Dashboard'));
    

    Memoization:

    // Use useMemo for expensive calculations
    const filtered = useMemo(() =>
      items.filter(item => item.active),
      [items]
    );
    

    Image Optimization:

    • Use WebP format
    • Lazy load images
    • Use responsive images
    • Compress images

    Phase 4: Verify

    1. Measure again
    2. Compare to baseline
    3. Ensure no regressions
    4. Document the improvement

    Performance Targets

    Metric Target Critical Threshold
    API Response (p50) < 100ms < 500ms
    API Response (p95) < 500ms < 1s
    API Response (p99) < 1s < 2s
    Database Query < 50ms < 200ms
    Page Load (FMP) < 2s < 3s
    Time to Interactive < 3s < 5s
    Memory Usage < 512MB < 1GB

    Common Optimizations

    Caching Strategy

    // Cache expensive computations
    const cache = new Map();
    
    async function getUserStats(userId: string) {
      if (cache.has(userId)) {
        return cache.get(userId);
      }
    
      const stats = await calculateUserStats(userId);
      cache.set(userId, stats);
    
      // Invalidate after 5 minutes
      setTimeout(() => cache.delete(userId), 5 * 60 * 1000);
    
      return stats;
    }
    

    Batch Processing

    // Bad: Individual requests
    for (const id of userIds) {
      await fetchUser(id);
    }
    
    // Good: Batch request
    await fetchUsers(userIds);
    

    Debouncing/Throttling

    // Debounce search input
    const debouncedSearch = debounce(search, 300);
    
    // Throttle scroll events
    const throttledScroll = throttle(handleScroll, 100);
    

    Performance Monitoring

    Key Metrics

    • Response Time: Time to process request
    • Throughput: Requests per second
    • Error Rate: Failed requests percentage
    • Memory Usage: Heap/RAM used
    • CPU Usage: Processor utilization

    Monitoring Tools

    Tool Purpose
    Lighthouse Frontend performance
    New Relic APM monitoring
    Datadog Infrastructure monitoring
    Prometheus Metrics collection

    Scripts

    Profile application:

    python scripts/profile.py
    

    Generate performance report:

    python scripts/perf_report.py
    

    References

    • references/optimization.md - Optimization techniques
    • references/monitoring.md - Monitoring setup
    • references/checklist.md - Performance checklist
    Recommended Servers
    Cloudflare Workers Observability
    Cloudflare Workers Observability
    Parallel Web Search
    Parallel Web Search
    Google search console
    Google search console
    Repository
    zhaono1/agent-playbook
    Files