Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/alirezarezvani/claude-skills --skill performance-profilerAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
Performance Profiler
Tier: POWERFUL Category: Engineering Domain: Performance Engineering
Overview
Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU, memory, and I/O bottlenecks; generates flamegraphs; analyzes bundle sizes; optimizes database queries; detects memory leaks; and runs load tests with k6 and Artillery. Always measures before and after.
Core Capabilities
- CPU profiling — flamegraphs for Node.js, py-spy for Python, pprof for Go
- Memory profiling — heap snapshots, leak detection, GC pressure
- Bundle analysis — webpack-bundle-analyzer, Next.js bundle analyzer
- Database optimization — EXPLAIN ANALYZE, slow query log, N+1 detection
- Load testing — k6 scripts, Artillery scenarios, ramp-up patterns
- Before/after measurement — establish baseline, profile, optimize, verify
When to Use
- App is slow and you don't 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
Quick Start
bash
# Analyze a project for performance risk indicators
python3 scripts/performance_profiler.py /path/to/project
# JSON output for CI integration
python3 scripts/performance_profiler.py /path/to/project --json
# Custom large-file threshold
python3 scripts/performance_profiler.py /path/to/project --large-file-threshold-kb 256Golden Rule: Measure First
bash
# Establish baseline BEFORE any optimization
# Record: P50, P95, P99 latency | RPS | error rate | memory usage
# Wrong: "I think the N+1 query is slow, let me fix it"
# Right: Profile → confirm bottleneck → fix → measure again → verify improvementNode.js Profiling
→ See references/profiling-recipes.md for details
References
- references/profiling-recipes.md — Node.js/Python/Go profiling commands, flamegraph generation, heap snapshots
- references/optimization-playbook.md — before/after measurement template, quick-win optimization checklist (DB/Node/bundle/API), common pitfalls, best practices
