Performance Optimization Coordinator

--- model: claude-opus-4-1 --- Optimize application performance end-to-end using specialized performance and optimization agents: [Extended thinking: This workflow coordinates multiple agents to identify and fix performance bottlenecks across the entire stack. From database queries to frontend rendering, each agent contributes their expertise to create a highly optimized application.] ## Phase 1: Performance Analysis ### 1. Application Profiling - Use Task tool with subagent_type="performance-engineer" - Prompt: "Profile application performance for: $ARGUMENTS. Identify CPU, memory, and I/O bottlenecks. Include flame graphs, memory profiles, and resource utilization metrics." - Output: Performance profile, bottleneck analysis, optimization priorities ### 2. Database Performance Analysis - Use Task tool with subagent_type="database-optimizer" - Prompt: "Analyze database performance for: $ARGUMENTS. Review query execution plans, identify slow queries, check indexing, and analyze connection pooling." - Output: Query optimization report, index recommendations, schema improvements ## Phase 2: Backend Optimization ### 3. Backend Code Optimization - Use Task tool with subagent_type="performance-engineer" - Prompt: "Optimize backend code for: $ARGUMENTS based on profiling results. Focus on algorithm efficiency, caching strategies, and async operations." - Output: Optimized code, caching implementation, performance improvements ### 4. API Optimization - Use Task tool with subagent_type="backend-architect" - Prompt: "Optimize API design and implementation for: $ARGUMENTS. Consider pagination, response compression, field filtering, and batch operations." - Output: Optimized API endpoints, GraphQL query optimization, response time improvements ## Phase 3: Frontend Optimization ### 5. Frontend Performance - Use Task tool with subagent_type="frontend-developer" - Prompt: "Optimize frontend performance for: $ARGUMENTS. Focus on bundle size, lazy loading, code splitting, and rendering performance. Implement Core Web Vitals improvements." - Output: Optimized bundles, lazy loading implementation, performance metrics ### 6. Mobile App Optimization - Use Task tool with subagent_type="mobile-developer" - Prompt: "Optimize mobile app performance for: $ARGUMENTS. Focus on startup time, memory usage, battery efficiency, and offline performance." - Output: Optimized mobile code, reduced app size, improved battery life ## Phase 4: Infrastructure Optimization ### 7. Cloud Infrastructure Optimization - Use Task tool with subagent_type="cloud-architect" - Prompt: "Optimize cloud infrastructure for: $ARGUMENTS. Review auto-scaling, instance types, CDN usage, and geographic distribution." - Output: Infrastructure improvements, cost optimization, scaling strategy ### 8. Deployment Optimization - Use Task tool with subagent_type="deployment-engineer" - Prompt: "Optimize deployment and build processes for: $ARGUMENTS. Improve CI/CD performance, implement caching, and optimize container images." - Output: Faster builds, optimized containers, improved deployment times ## Phase 5: Monitoring and Validation ### 9. Performance Monitoring Setup - Use Task tool with subagent_type="devops-troubleshooter" - Prompt: "Set up comprehensive performance monitoring for: $ARGUMENTS. Include APM, real user monitoring, and custom performance metrics." - Output: Monitoring dashboards, alert thresholds, SLO definitions ### 10. Performance Testing - Use Task tool with subagent_type="test-automator" - Prompt: "Create performance test suites for: $ARGUMENTS. Include load tests, stress tests, and performance regression tests." - Output: Performance test suite, benchmark results, regression prevention ## Coordination Notes - Performance metrics guide optimization priorities - Each optimization must be validated with measurements - Consider trade-offs between different performance aspects - Document all optimizations and their impact Performance optimization target: $ARGUMENTS