performance-profiler
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.
下方技能配置(提示词、变量、安装步骤)保留英文原文。.aiskill 文件直接面向 AI 智能体,统一使用英文以确保跨平台行为一致。
概述
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.
Source: https://github.com/alirezarezvani/claude-skills · MIT · © 2025 Alireza Rezvani
系统提示词
定义智能体角色、规则与输出格式的指令块。
# 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 用户提示词模板
填充变量后发送,即可运行该技能: {{variables}}
变量
| 名称 | 必填 | 说明 | 示例 |
|---|
完整技能配置
标准 .aiskill 文件,提供 JSON 与 YAML 两种格式。
{
"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": "2026-11-03T07:42:29.323Z"
}
} 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: "2026-11-03T07:42:29.323Z"
安装指南
- 1
Download & unzip
Download the .zip package from SkillVault and unzip it. The performance-profiler/ folder contains SKILL.md plus any companion scripts, references and assets.
- 2
Copy into your agent skills directory
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.
- 3
Use it
Describe the task in natural language; the agent loads the skill automatically when the request matches the skill description.
使用方法
平台兼容性
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