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/analyze-performance

Performance analysis based on Core Web Vitals with UX scoring. Trigger with "analyze performance", "improve speed", "check Core Web Vitals", "page speed", "improve LCP", "identify performance issues".

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claude-code-cookbook
1.1k200 skills9 agents39 commands8 MCP
Install
$ npx -y skills add wasabeef/claude-code-cookbook --skill analyze-performance --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/analyze-performance

Context preview

The summary Claude sees to decide when to auto-load this skill.

Performance analysis based on Core Web Vitals with UX scoring. Trigger with "analyze performance", "improve speed", "check Core Web Vitals", "page speed", "improve LCP", "identify performance issues".

SKILL.md

analyze-performance.SKILL.md
description: 'Performance analysis based on Core Web Vitals with UX scoring. Trigger with "analyze performance", "improve speed", "check Core Web Vitals", "page speed", "improve LCP", "identify performance issues".'
allowed-tools:
  - Read
  - Grep
  - Glob
  - Bash

Performance analysis based on Core Web Vitals

Analyzes application performance from a user experience perspective and quantifies experience improvements from optimizations. Calculates UX scores based on Core Web Vitals and proposes prioritized optimization strategies.

UX Performance Score

User Experience Score: B+ (78/100)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

⏱️ Core Web Vitals
├─ LCP (Loading): 2.3s [Good] Target<2.5s ✅
├─ INP (Interaction): 95ms [Good] Target<200ms ✅
├─ CLS (Visual Stability): 0.08 [Good] Target<0.1 ✅
├─ FCP (First Paint): 1.8s [Good] Target<1.8s ✅
├─ TTFB (Server): 450ms [Needs Work] Target<200ms ⚠️
└─ TTI (Interactive): 3.5s [Needs Work] Target<3.8s ⚠️

📊 Perceived Speed
├─ Initial Load: 2.3s [Industry avg: 3.0s]
├─ Page Navigation: 1.1s [Industry avg: 1.5s]
├─ Search Results: 0.8s [Industry avg: 1.2s]
├─ Form Submission: 1.5s [Industry avg: 2.0s]
└─ Image Loading: Lazy loading implemented ✅

😊 User Satisfaction Prediction
├─ Bounce Rate: 12% (Industry avg: 20%)
├─ Completion Rate: 78% (Target: 85%)
├─ NPS Score: +24 (Industry avg: +15)
└─ Return Rate: 65% (Target: 70%)

📊 User Experience Impact
├─ 0.5s faster display → -7% bounce rate
├─ 5% bounce reduction → +15% session length
├─ Search improvement → +15% time on site
└─ Overall UX improvement: +25%

🎯 Expected Improvement Effects (Priority Order)
├─ [P0] TTFB improvement (CDN) → LCP -0.3s = +15% perceived speed
├─ [P1] JS bundle optimization → TTI -0.8s = -20% interactive time
├─ [P2] Image optimization (WebP) → -40% transfer = -25% load time
└─ [P3] Cache strategy → 50% faster repeat visits

Usage

# Comprehensive UX score analysis
find . -name "*.js" -o -name "*.ts" | xargs wc -l | sort -rn | head -10
"Calculate UX performance score and evaluate Core Web Vitals"

# Performance bottleneck detection
grep -r "for.*await\|forEach.*await" . --include="*.js"
"Detect async processing bottlenecks and analyze UX impact"

# User experience impact analysis
grep -r "addEventListener\|setInterval" . --include="*.js" | grep -v "removeEventListener\|clearInterval"
"Analyze performance impact on user experience"

Basic Examples

# Bundle size and load time
npm ls --depth=0 && find ./public -name "*.js" -o -name "*.css" | xargs ls -lh
"Identify bundle size and asset optimization improvements"

# Database performance
grep -r "SELECT\|findAll\|query" . --include="*.js" | head -20
"Analyze database query optimization points"

# Dependency performance impact
npm outdated && npm audit
"Evaluate performance impact of outdated dependencies"

Analysis Perspectives

1. Code-Level Problems

  • **O(n²) Algorithms**: Detect inefficient array operations
  • **Synchronous I/O**: Identify blocking processes
  • **Redundant Processing**: Remove unnecessary calculations or requests
  • **Memory Leaks**: Manage event listeners and timers

2. Architecture-Level Problems

  • **N+1 Queries**: Database access patterns
  • **Missing Cache**: Repeated calculations or API calls
  • **Bundle Size**: Unnecessary libraries or code splitting
  • **Resource Management**: Connection pools and thread usage

3. Technical Debt Impact

  • **Legacy Code**: Performance degradation from old implementations
  • **Design Issues**: High coupling from poor responsibility distribution
  • **Insufficient Testing**: Missing performance regression detection
  • **Monitoring Gaps**: Early problem detection system

Performance Improvement ROI Matrix

Improvement ROI = (Time Savings + Quality Improvement) ÷ Implementation Effort

| Priority | UX Impact | Implementation Difficulty | Time Savings | Example | Effort | Effect | | ------------------------------- | --------- | ------------------------- | ------------ | ------------------- | ------ | ------------- | | **[P0] Implement Now** | High | Low | > 50% | CDN implementation | 8h | Response -60% | | **[P1] Early Implementation** | High | Medium | 20-50% | Image optimization | 16h | Load -30% | | **[P2] Planned Implementation** | Low | High | 10-20% | Code splitting | 40h | Initial -15% | | **[P3] Hold/Monitor** | Low | Low | < 10% | Minor optimizations | 20h | Partial -5% |

Priority Criteria

  • **P0 (Immediate)**: High UX impact × Low difficulty = Maximum ROI
  • **P1 (Early)**: High UX impact × Medium difficulty = High ROI
  • **P2 (Planned)**: Low UX impact × High difficulty = Medium ROI
  • **P3 (Hold)**: Low UX impact × Low difficulty = Low ROI

Performance Metrics and UX Improvement Correlation

| Metric | Improvement | Perceived Speed | User Satisfaction | Implementation Effort | | -------------------------- | ----------- | --------------- | -------------------- | --------------------- | | **LCP (Loading)** | -0.5s | +30% | -7% bounce rate | 16h | | **INP (Interaction)** | -50ms | +15% | -20% stress | 8h | | **CLS (Visual Stability)** | -0.05 | +10% | -50% misclicks | 4h | | **TTFB (Server)** | -200ms | +25% | +40% perceived speed | 24h | | **TTI (Interactive)** | -1.0s | +35% | +15% completion rate | 32h | | **Bundle Size** | -30% | +20% | +25% first visit | 16h |

Measurement and Tools

Node.js / JavaScript

# Profiling
node --prof app.js
clinic docto
Read more
Ships withclaude-code-cookbook

A collection of commands, roles, and automation scripts for Claude Code. Automate your workflow without unnecessary confirmations, allowing you to focus on what matters.

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