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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
85 lines
3.3 KiB
Markdown
85 lines
3.3 KiB
Markdown
---
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title: "Performance Profiler — Agent Skill for Codex & OpenClaw"
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description: "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."
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---
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# Performance Profiler
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<div class="page-meta" markdown>
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<span class="meta-badge">:material-rocket-launch: Engineering - POWERFUL</span>
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<span class="meta-badge">:material-identifier: `performance-profiler`</span>
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<span class="meta-badge">:material-github: <a href="https://github.com/alirezarezvani/claude-skills/tree/main/engineering/skills/performance-profiler/SKILL.md">Source</a></span>
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</div>
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<div class="install-banner" markdown>
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<span class="install-label">Install:</span> <code>claude /plugin install engineering-advanced-skills</code>
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</div>
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**Tier:** POWERFUL
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**Category:** Engineering
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**Domain:** Performance Engineering
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---
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## Overview
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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.
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## Core Capabilities
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- **CPU profiling** — flamegraphs for Node.js, py-spy for Python, pprof for Go
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- **Memory profiling** — heap snapshots, leak detection, GC pressure
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- **Bundle analysis** — webpack-bundle-analyzer, Next.js bundle analyzer
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- **Database optimization** — EXPLAIN ANALYZE, slow query log, N+1 detection
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- **Load testing** — k6 scripts, Artillery scenarios, ramp-up patterns
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- **Before/after measurement** — establish baseline, profile, optimize, verify
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---
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## When to Use
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- App is slow and you don't know where the bottleneck is
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- P99 latency exceeds SLA before a release
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- Memory usage grows over time (suspected leak)
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- Bundle size increased after adding dependencies
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- Preparing for a traffic spike (load test before launch)
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- Database queries taking >100ms
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---
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## Quick Start
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```bash
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# Analyze a project for performance risk indicators
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python3 scripts/performance_profiler.py /path/to/project
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# JSON output for CI integration
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python3 scripts/performance_profiler.py /path/to/project --json
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# Custom large-file threshold
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python3 scripts/performance_profiler.py /path/to/project --large-file-threshold-kb 256
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```
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---
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## Golden Rule: Measure First
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```bash
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# Establish baseline BEFORE any optimization
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# Record: P50, P95, P99 latency | RPS | error rate | memory usage
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# Wrong: "I think the N+1 query is slow, let me fix it"
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# Right: Profile → confirm bottleneck → fix → measure again → verify improvement
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```
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---
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## Node.js Profiling
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→ See references/profiling-recipes.md for details
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## References
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- [references/profiling-recipes.md](https://github.com/alirezarezvani/claude-skills/tree/main/engineering/skills/performance-profiler/references/profiling-recipes.md) — Node.js/Python/Go profiling commands, flamegraph generation, heap snapshots
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- [references/optimization-playbook.md](https://github.com/alirezarezvani/claude-skills/tree/main/engineering/skills/performance-profiler/references/optimization-playbook.md) — before/after measurement template, quick-win optimization checklist (DB/Node/bundle/API), common pitfalls, best practices
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