performance-profiler

# 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

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    "name": "performance-profiler",
    "slug": "performance-profiler",
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    "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.",
    "category": "Development",
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      "cursor"
    ],
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    "license": "MIT"
  },
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    "system": "# Performance Profiler\r\n\r\n**Tier:** POWERFUL  \r\n**Category:** Engineering  \r\n**Domain:** Performance Engineering  \r\n\r\n---\r\n\r\n## Overview\r\n\r\nSystematic 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.\r\n\r\n## Core Capabilities\r\n\r\n- **CPU profiling** — flamegraphs for Node.js, py-spy for Python, pprof for Go\r\n- **Memory profiling** — heap snapshots, leak detection, GC pressure\r\n- **Bundle analysis** — webpack-bundle-analyzer, Next.js bundle analyzer\r\n- **Database optimization** — EXPLAIN ANALYZE, slow query log, N+1 detection\r\n- **Load testing** — k6 scripts, Artillery scenarios, ramp-up patterns\r\n- **Before/after measurement** — establish baseline, profile, optimize, verify\r\n\r\n---\r\n\r\n## When to Use\r\n\r\n- App is slow and you don't know where the bottleneck is\r\n- P99 latency exceeds SLA before a release\r\n- Memory usage grows over time (suspected leak)\r\n- Bundle size increased after adding dependencies\r\n- Preparing for a traffic spike (load test before launch)\r\n- Database queries taking >100ms\r\n\r\n---\r\n\r\n## Quick Start\r\n\r\n```bash\r\n# Analyze a project for performance risk indicators\r\npython3 scripts/performance_profiler.py /path/to/project\r\n\r\n# JSON output for CI integration\r\npython3 scripts/performance_profiler.py /path/to/project --json\r\n\r\n# Custom large-file threshold\r\npython3 scripts/performance_profiler.py /path/to/project --large-file-threshold-kb 256\r\n```\r\n\r\n---\r\n\r\n## Golden Rule: Measure First\r\n\r\n```bash\r\n# Establish baseline BEFORE any optimization\r\n# Record: P50, P95, P99 latency | RPS | error rate | memory usage\r\n\r\n# Wrong: \"I think the N+1 query is slow, let me fix it\"\r\n# Right: Profile → confirm bottleneck → fix → measure again → verify improvement\r\n```\r\n\r\n---\r\n\r\n## Node.js Profiling\r\n→ See references/profiling-recipes.md for details\r\n\r\n## References\r\n\r\n- [references/profiling-recipes.md](references/profiling-recipes.md) — Node.js/Python/Go profiling commands, flamegraph generation, heap snapshots\r\n- [references/optimization-playbook.md](references/optimization-playbook.md) — before/after measurement template, quick-win optimization checklist (DB/Node/bundle/API), common pitfalls, best practices",
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      },
      {
        "title": "Copy into your agent skills directory",
        "detail": "Move the folder into your agent's skills directory — e.g. ~/.claude/skills/ (Claude Code), .codex/skills/, .cursor/skills/ or your project's .claude/skills/ folder — then restart or reload the session."
      },
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    "author": "SkillVault",
    "source": "https://skillvault.top/skills/performance-profiler",
    "exported_at": "2026-11-03T07:41:25.217Z"
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}

format: aiskill/v1
skill:
  name: performance-profiler
  slug: performance-profiler
  version: 1.0.0
  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.
  category: Development
  tags:
    - engineering
    - sql
    - python
    - performance
  platforms:
    - chatgpt
    - claude-code
    - cursor
  tested_environment: >-
    Agent Skills convention (SKILL.md) — works with Claude Code, Cursor, ChatGPT/Codex and
    compatible agents
  license: MIT
prompts:
  system: "# Performance Profiler\r\n\r\n**Tier:** POWERFUL  \r\n**Category:** Engineering  \r\n**Domain:** Performance Engineering  \r\n\r\n---\r\n\r\n## Overview\r\n\r\nSystematic 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.\r\n\r\n## Core Capabilities\r\n\r\n- **CPU profiling** — flamegraphs for Node.js, py-spy for Python, pprof for Go\r\n- **Memory profiling** — heap snapshots, leak detection, GC pressure\r\n- **Bundle analysis** — webpack-bundle-analyzer, Next.js bundle analyzer\r\n- **Database optimization** — EXPLAIN ANALYZE, slow query log, N+1 detection\r\n- **Load testing** — k6 scripts, Artillery scenarios, ramp-up patterns\r\n- **Before/after measurement** — establish baseline, profile, optimize, verify\r\n\r\n---\r\n\r\n## When to Use\r\n\r\n- App is slow and you don't know where the bottleneck is\r\n- P99 latency exceeds SLA before a release\r\n- Memory usage grows over time (suspected leak)\r\n- Bundle size increased after adding dependencies\r\n- Preparing for a traffic spike (load test before launch)\r\n- Database queries taking >100ms\r\n\r\n---\r\n\r\n## Quick Start\r\n\r\n```bash\r\n# Analyze a project for performance risk indicators\r\npython3 scripts/performance_profiler.py /path/to/project\r\n\r\n# JSON output for CI integration\r\npython3 scripts/performance_profiler.py /path/to/project --json\r\n\r\n# Custom large-file threshold\r\npython3 scripts/performance_profiler.py /path/to/project --large-file-threshold-kb 256\r\n```\r\n\r\n---\r\n\r\n## Golden Rule: Measure First\r\n\r\n```bash\r\n# Establish baseline BEFORE any optimization\r\n# Record: P50, P95, P99 latency | RPS | error rate | memory usage\r\n\r\n# Wrong: \"I think the N+1 query is slow, let me fix it\"\r\n# Right: Profile → confirm bottleneck → fix → measure again → verify improvement\r\n```\r\n\r\n---\r\n\r\n## Node.js Profiling\r\n→ See references/profiling-recipes.md for details\r\n\r\n## References\r\n\r\n- [references/profiling-recipes.md](references/profiling-recipes.md) — Node.js/Python/Go profiling commands, flamegraph generation, heap snapshots\r\n- [references/optimization-playbook.md](references/optimization-playbook.md) — before/after measurement template, quick-win optimization checklist (DB/Node/bundle/API), common pitfalls, best practices"
  user_template: ""
variables: []
install:
  steps:
    - title: Download & unzip
      detail: >-
        Download the .zip package from SkillVault and unzip it. The performance-profiler/ folder
        contains SKILL.md plus any companion scripts, references and assets.
    - title: Copy into your agent skills directory
      detail: >-
        Move the folder into your agent's skills directory — e.g. ~/.claude/skills/ (Claude Code),
        .codex/skills/, .cursor/skills/ or your project's .claude/skills/ folder — then restart or
        reload the session.
    - title: Use it
      detail: >-
        Describe the task in natural language; the agent loads the skill automatically when the
        request matches the skill description.
usage:
  steps: []
metadata:
  author: SkillVault
  source: https://skillvault.top/skills/performance-profiler
  exported_at: "2026-11-03T07:41:25.217Z"