edge-performance-optimizer

name	edge-performance-optimizer
description	Automatically optimizes Cloudflare Workers performance during development, focusing on cold starts, bundle size, edge caching, and global latency
triggers	["bundle size changes","fetch calls","storage operations","dependency additions","sequential operations"]

Edge Performance Optimizer SKILL

Activation Patterns

This SKILL automatically activates when:

• New dependencies are added to package.json
• Large files or heavy imports are detected
• Sequential operations that could be parallelized
• Missing edge caching opportunities
• Bundle size increases significantly
• Storage operations without optimization patterns

Expertise Provided

Edge-Specific Performance Optimization

• Cold Start Optimization: Minimizes bundle size and heavy dependencies
• Global Distribution: Ensures edge caching for global performance
• CPU Time Optimization: Identifies CPU-intensive operations
• Storage Performance: Optimizes KV/R2/D1 access patterns
• Parallel Operations: Suggests parallelization opportunities
• Bundle Analysis: Monitors and optimizes bundle size

Specific Checks Performed

❌ Performance Anti-Patterns

// These patterns trigger immediate alerts:
import axios from 'axios';              // Heavy dependency (13KB)
import moment from 'moment';             // Heavy dependency (68KB)
import _ from 'lodash';                 // Heavy dependency (71KB)

// Sequential operations that could be parallel
const user = await env.USERS.get(id);
const settings = await env.SETTINGS.get(id);
const prefs = await env.PREFS.get(id);

✅ Performance Best Practices

// These patterns are validated as correct:
// Native Web APIs instead of heavy libraries
const response = await fetch(url);      // Built-in fetch (0KB)
const now = new Date();                // Native Date (0KB)

// Parallel operations
const [user, settings, prefs] = await Promise.all([
  env.USERS.get(id),
  env.SETTINGS.get(id),
  env.PREFS.get(id),
]);

Integration Points

Complementary to Existing Components

• edge-performance-oracle agent: Handles comprehensive performance analysis, SKILL provides immediate optimization
• workers-runtime-validator SKILL: Complements runtime checks with performance optimization
• es-deploy command: SKILL ensures performance standards before deployment

Escalation Triggers

• Complex performance architecture questions → edge-performance-oracle agent
• Global distribution strategy → cloudflare-architecture-strategist agent
• Performance troubleshooting → edge-performance-oracle agent

Validation Rules

P1 - Critical (Performance Killer)

• Large Dependencies: Heavy libraries like moment, lodash, axios
• Bundle Size: Over 200KB (kills cold start performance)
• Sequential Operations: Multiple sequential storage/network calls
• Missing Edge Caching: No caching for frequently accessed data

P2 - High (Performance Impact)

• Bundle Size: Over 100KB (slows cold starts)
• CPU Time: Operations approaching 50ms limit
• Lazy Loading: Dynamic imports that hurt cold start
• Large Payloads: Responses over 100KB without streaming

P3 - Medium (Optimization Opportunity)

• Bundle Size: Over 50KB (could be optimized)
• Missing Parallelization: Operations that could be parallel
• No Request Caching: Repeated expensive operations

Remediation Examples

Fixing Heavy Dependencies

// ❌ Critical: Heavy dependencies (150KB+ bundle)
import axios from 'axios';              // 13KB
import moment from 'moment';             // 68KB  
import _ from 'lodash';                 // 71KB
// Total: 152KB just for utilities!

// ✅ Correct: Native Web APIs (minimal bundle)
// Use fetch instead of axios
const response = await fetch(url);
const data = await response.json();

// Use native Date instead of moment
const now = new Date();
const tomorrow = new Date(Date.now() + 86400000);

// Use native methods instead of lodash
const unique = [...new Set(array)];
const grouped = array.reduce((acc, item) => {
  const key = item.category;
  if (!acc[key]) acc[key] = [];
  acc[key].push(item);
  return acc;
}, {});
// Total: < 5KB for utilities

Fixing Sequential Operations

// ❌ High: Sequential KV operations (3x network round-trips)
export default {
  async fetch(request: Request, env: Env) {
    const user = await env.USERS.get(userId);      // 10-30ms
    const settings = await env.SETTINGS.get(id);    // 10-30ms  
    const prefs = await env.PREFS.get(id);         // 10-30ms
    // Total: 30-90ms just for storage!
  }
}

// ✅ Correct: Parallel operations (single round-trip)
export default {
  async fetch(request: Request, env: Env) {
    const [user, settings, prefs] = await Promise.all([
      env.USERS.get(userId),
      env.SETTINGS.get(id),
      env.PREFS.get(id),
    ]);
    // Total: 10-30ms (single round-trip)
  }
}

Fixing Missing Edge Caching

// ❌ Critical: No edge caching (slow globally)
export default {
  async fetch(request: Request, env: Env) {
    const config = await fetch('https://api.example.com/config');
    // Every request goes to origin!
    // Sydney user → US origin = 200ms+ just for config
  }
}

// ✅ Correct: Edge caching pattern
export default {
  async fetch(request: Request, env: Env) {
    const cache = caches.default;
    const cacheKey = new Request('https://example.com/config', {
      method: 'GET'
    });

    // Try cache first
    let response = await cache.match(cacheKey);

    if (!response) {
      // Cache miss - fetch from origin
      response = await fetch('https://api.example.com/config');
      
      // Cache at edge with 1-hour TTL
      response = new Response(response.body, {
        ...response,
        headers: {
          ...response.headers,
          'Cache-Control': 'public, max-age=3600',
        }
      });
      
      await cache.put(cacheKey, response.clone());
    }

    // Sydney user → Sydney edge cache = < 10ms
    return response;
  }
}

Fixing CPU Time Issues

// ❌ High: Large synchronous processing (CPU time bomb)
export default {
  async fetch(request: Request, env: Env) {
    const users = await env.DB.prepare('SELECT * FROM users').all();
    // If 10,000 users, this loops for 100ms+ CPU time
    const enriched = users.results.map(user => {
      return {
        ...user,
        fullName: `${user.firstName} ${user.lastName}`,
        // ... expensive computations
      };
    });
  }
}

// ✅ Correct: Bounded operations
export default {
  async fetch(request: Request, env: Env) {
    // Option 1: Limit at database level
    const users = await env.DB.prepare(
      'SELECT * FROM users LIMIT ? OFFSET ?'
    ).bind(10, offset).all();  // Only 10 users, bounded CPU

    // Option 2: Stream processing for large datasets
    const { readable, writable } = new TransformStream();
    // Process in chunks without loading everything into memory

    // Option 3: Offload to Durable Object
    const id = env.PROCESSOR.newUniqueId();
    const stub = env.PROCESSOR.get(id);
    return stub.fetch(request);  // DO can run longer
  }
}

MCP Server Integration

When Cloudflare MCP server is available:

• Query real performance metrics (cold start times, CPU usage)
• Analyze global latency by region
• Get latest performance optimization techniques
• Check bundle size impact on cold starts

Benefits

Immediate Impact

• Faster Cold Starts: Reduces bundle size and heavy dependencies
• Better Global Performance: Ensures edge caching for worldwide users
• Lower CPU Usage: Identifies and optimizes CPU-intensive operations
• Reduced Latency: Parallelizes operations and adds caching

Long-term Value

• Consistent Performance Standards: Ensures all code meets performance targets
• Better User Experience: Faster response times globally
• Cost Optimization: Reduced CPU time usage lowers costs

Usage Examples

During Dependency Addition

// Developer types: npm install moment
// SKILL immediately activates: "❌ CRITICAL: moment is 68KB and will slow cold starts. Use native Date instead for 0KB impact."

During Storage Operations

// Developer types: sequential KV gets
// SKILL immediately activates: "⚠️ HIGH: Sequential KV operations detected. Use Promise.all() to parallelize and reduce latency by 3x."

During API Development

// Developer types: fetch without caching
// SKILL immediately activates: "⚠️ HIGH: No edge caching for API call. Add Cache API to serve from edge locations globally."

Performance Targets

Bundle Size

• Excellent: < 10KB
• Good: < 50KB
• Acceptable: < 100KB
• Needs Improvement: > 100KB
• Action Required: > 200KB

Cold Start Time

• Excellent: < 3ms
• Good: < 5ms
• Acceptable: < 10ms
• Needs Improvement: > 10ms
• Action Required: > 20ms

Global Latency (P95)

• Excellent: < 100ms
• Good: < 200ms
• Acceptable: < 500ms
• Needs Improvement: > 500ms
• Action Required: > 1000ms

This SKILL ensures Workers performance by providing immediate, autonomous optimization of performance patterns, preventing common performance issues and ensuring fast global response times.