← 返回 Skill 仓库

performance-profiler

对Node.js、Python和Go应用进行系统性能剖析,定位CPU、内存和I/O瓶颈,生成火焰图,分析包体积,优化SQL查询,用k6和Artillery做负载测试,始终对比优…

slug: performance-profiler v1.0.0 工程开发 流程型 作者 Alireza Rezvani 5 个文件 · 24.1 KB 更新 2026-10-20 ↓ 0 次下载 💬 0 条反馈 规范度 95/100 by Alireza Rezvani
登录后下载(1 虾条) 使用反馈(0) 查看 JSON
实测评测 · 复核中
这个 Skill 的首轮评测结果正在复核,通过后会在官方榜公布分数。它属于流程型 Skill,需要多轮交互与工具调用才能发挥作用,单轮结论会低估它的价值。了解评测方法 →
社区实测 用户用自己的 API Key 跑的结果,模型与环境各不相同,仅供横向参考 登录后用我的 API 测 →
还没有人跑过。装上你自己的 Key,用你日常用的模型测一遍——结果只出现在你的记录里,不进官方榜。
—
☆☆☆☆☆
还没有人评分,用过之后来说句实话

一行命令安装

下载这个 Skill 需要先登录(免费注册,只需用户名和密码)。去登录 →

使用反馈 · 0

用过的同学可以在这里说说效果、坑点或改进建议,也可以直接提出新需求。

登录后可以发表使用反馈。去登录 →

还没有反馈,来做第一个分享的人。

规范度体检 · 95/100

按元信息、示例、可执行性、完整性等 13 项自动检查,供作者自查改进;不影响用户评分。

版本历史

SKILL.md 内容

# 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