perflisted

# Performance Mode **Recommended model tier:** smart (opus) - this skill requires complex reasoning Systematic approach to identifying and fixing performance issues. ## Prerequisites Before starting: - Identify the specific operation or endpoint that is slow - Understand what "fast enough" means (target latency, throughput) - Ensure you can measure performance reproducibly ## Workflow ### Step 1: Establish Baseline Measurement **Never optimize without data.** Measure current performance: ```bash # Node.js - simple timing time node script.js # Node.js - CPU profiling node --cpu-prof script.js # Creates CPU.*.cpuprofile - analyze in Chrome DevTools # Go - benchmarks go test -bench=. -benchmem ./... # API endpoint curl -w "@curl-format.txt" -o /dev/null -s "http://localhost:3000/api/endpoint" ``` **Record baseline metrics:** - Execution time (p50, p95, p99 if available) - Memory usage - Number of operations per second - Number of I/O operations ### Step 2: Identify Hotspots Find where time is being spent: ```bash # Node.js profiling node --cpu-prof app.js # Then load .cpuprofile in Chrome DevTools > Performance # Go profiling go test -cpuprofile=cpu.prof -bench=. go tool pprof -http=:8080 cpu.prof ``` ``` # Get structural overview of suspect files (signatures + line ranges, not full content) mcp__plugin_aide_aide__code_outline file="path/to/hotspot.ts" # Find functions/classes in suspect area by name mcp__plugin_aide_aide__code_search query="processData" kind