Agent skill · data analytics · borghei
performance-profiler
Performance profiling for Node.js, Python, and Go: CPU flamegraphs, memory leak detection, bundle analysis, query optimization, and k6 load testing. Use when diagnosing slow endpoints, memory growth, large bundles, or traffic spikes.
Why this skill is useful
Adds specific profiling scripts and methodologies for performance optimization that the AI wouldn't reliably generate on its own.
What it needs
Requires clinic, k6, pprof, py-spy, webpack-bundle-analyzer installed locally. About 4k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
Performance Profiler Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU bottlenecks with flamegraphs, detects memory leaks with heap snapshots, analyzes bundle sizes, optimizes database queries, detects N+1 patterns, and runs load tests with k6 and Artillery. Enforces a measure-first methodology: establish baseline, identify bottleneck, fix, and verify improvement. Golden Rule — Measure First: Profile → Confirm bottleneck → Fix → Measure again → Verify improvement. Every optimization needs baseline metrics, profiler evidence, the fix, post-fix metrics, and a delta. Full rule in references/cpu-and-memory-profiling.md. Core Capabilities CPU profiling — Clinic.js/V8 flamegraphs (Node), py-spy/cProfile/scalene (Python), pprof (Go), Chrome DevTools (browser). Memory profiling — heap snapshots and before/after comparison, GC pressure analysis, leak detection, retained object graphs. Database optimization — EXPLAIN ANALYZE plan reading, N+1 detection and batching, slow query logs, missing-index identification, connection pool sizing. Bundle analysis — webpack/Next.js analyzers, tree-shaking, dynamic imports, heavy dependency identification. Load testing — k6 ramp-up scripts, SLA threshold enforcement in CI, P50/P95/P99 latency tracking, concurrent user simulation. When to Use App is slow and you do not know where the bottleneck is. P99 latency exceeds SLA before a release. Memory usage grows over time (suspected leak). Bundle size increased after adding dependencies. Preparing for a traffic spike (load test before launch). Database queries taking >100ms, or verifying no regressions after a dependency upgrade. Clarify First Before profiling, confirm these inputs. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/performance-profiler