agentleFS
darkweb19darkweb19/skills/performance-profiler/SKILL.md

performance-profiler

Skill0 starsChanged 28 days agoApache-2.0View on GitHub

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, runs load tests with k6 and Artillery. Always measures before and after. Use when investigating a slow endpoint, planning a performance budget, or hunting a memory leak in production.

21 other projects use a version of this, 6 of them edited.

Adopted by

Most recently taken up by

The file

Files
SKILL.md

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

# 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 256

Golden Rule: Measure First

# 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 improvement

Node.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

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.