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performance-profiler — Claude Code skill for profiling

This skill investigates CPU, memory, I/O, and database bottlenecks in Node.js, Python, and Go apps. Use it when tracking down a slow endpoint or rising memory use.

Install into Claude Code · Plugin marketplace All methods and platforms ↓ 
/plugin marketplace add alirezarezvani/claude-skills
/plugin install engineering-advanced-skills@claude-code-skills
Open on GitHub

What performance-profiler does

The skill covers CPU and memory profiling, leak detection, garbage-collection pressure, bundle analysis, and slow database queries. Its listed tools include flamegraphs, py-spy, pprof, heap snapshots, EXPLAIN ANALYZE, and slow query logs. Load tests use k6 or Artillery. It calls for a baseline measurement before changes and another measurement afterward.

The package includes scripts/performance_profiler.py, which scans a project for performance risk indicators; pass --json for output intended for CI. Python 3 is needed to run the script. Deeper profiling also depends on having a workload and the relevant tools for the application. Install it when you can validate a suspected bottleneck with measurements; otherwise, its optimization guidance has little to verify against.

What it helps with

  • trace a bottleneck behind a slow endpoint
  • check for memory leaks and rising memory use
  • inspect a bundle size increase
  • find slow queries and N+1 patterns
  • load-test an app before launch

Example prompts for the agent

  • Scan this project for performance risk indicators and return JSON.
  • Investigate why this endpoint is slow. Measure first, then identify the bottleneck.
  • Memory use keeps growing. Help me check for a leak and measure it.

How to install performance-profiler

1Plugin marketplace

/plugin marketplace add alirezarezvani/claude-skills
/plugin install engineering-advanced-skills@claude-code-skills

This installs the whole engineering-advanced-skills plugin with all its skills

2Skills CLI (Vercel)

npx skills add alirezarezvani/claude-skills --skill performance-profiler -a claude-code

3Manually: put the files in place

~/.claude/skills/performance-profiler/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/performance-profiler/

From the same set349

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Questions about performance-profiler

How do I install performance-profiler in Claude Code?

Run npx skills add alirezarezvani/claude-skills --skill performance-profiler -a claude-code.

What does performance-profiler do?

It helps investigate CPU, memory, I/O, bundle size, and database query performance in Node.js, Python, and Go apps. It uses before-and-after measurements to check changes.

Which tools does it use for load testing?

The skill lists k6 and Artillery for load testing. Running its project analysis script requires Python 3.

Source text

SKILL.md · MIT 
---
name: "performance-profiler"
description: "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."
---

# 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 256
```

---

## Golden 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 improvement
```

---

## Node.js Profiling
→ See references/profiling-recipes.md for details

## References

- [references/profiling-recipes.md](references/profiling-recipes.md) — Node.js/Python/Go profiling commands, flamegraph generation, heap snapshots
- [references/optimization-playbook.md](references/optimization-playbook.md) — before/after measurement template, quick-win optimization checklist (DB/Node/bundle/API), common pitfalls, best practices

© Alireza Rezvani · MIT · alirezarezvani/claude-skills

See also

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