scriptoriumadmin/claude-skills
1
0
Fork 0
mirror of https://github.com/alirezarezvani/claude-skills.git synced 2026-09-07 08:26:02 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions
claude-skills/docs/skills/engineering/performance-profiler.md
Claude 667cb3207b
docs: regenerate catalog pages for skills updated in PRs #843/#844 
mcp-server-builder, performance-profiler, ci-cd-pipeline-builder, and four
ra-qm-team skill sources changed after the last docs regeneration; refresh
their generated pages so the published site matches the SKILL.md sources.

https://claude.ai/code/session_015bYZ97nV4oRb3LbxCRFVcP
2026-06-12 05:58:43 +00:00

3.3 KiB
Raw Permalink Blame History

title description
Performance Profiler — Agent Skill for Codex & OpenClaw Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU, memory, and I/O bottlenecks, generates flamegraphs. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw.

Performance Profiler

:material-rocket-launch: Engineering - POWERFUL :material-identifier: `performance-profiler` :material-github: Source
Install: claude /plugin install engineering-advanced-skills

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