SkillsLib.ai

Performance Tuning

Optimize Core Web Vitals, bundle size, and rendering for faster Next.js and React apps

4.2(25 reviews)
100+ downloads
Updated Nov 2026
Verified SafeSecurity VerifiedThis skill was analyzed by our AI security scanner for harmful content including data exfiltration, system manipulation, credential theft, and prompt injection. No threats were detected.

What You Can Do

Diagnose and fix performance bottlenecks across your entire stack. Measure Core Web Vitals against 2026 standards, analyze bundle size bloat, identify unused dependencies, and optimize rendering strategies and caching. You'll receive specific code changes, configuration tweaks, and architecture recommendations tailored to your framework.

Features

Core Web Vitals Analysis

Measures LCP, INP, CLS against industry benchmarks and provides targeted fixes for each metric

Bundle Size Auditing

Identifies largest chunks, bloated dependencies, and unused packages with replacement suggestions

Rendering Strategy Optimization

Recommends SSR vs CSR, code splitting, dynamic imports, and lazy loading patterns

Image & Font Loading

Optimizes image formats, lazy loading, font subsetting, and preload/prefetch strategies

Caching Configuration

Sets up browser caching, CDN strategies, and service worker patterns for fast repeat visits

Database Query Performance

Analyzes N+1 queries, missing indexes, and connection pooling for Python backends

Lighthouse Integration

Runs automated audits and parses results to prioritize optimizations by impact

Example Output

Example 1: Bundle Analysis Report

  • Total JS: 285KB gzip → 120KB gzip (58% reduction)
  • Removed moment.js (300KB) → replaced with date-fns (2KB)
  • Code-split lazy routes: Dashboard chunk 85KB → 32KB
  • Recommended: Enable gzip compression in nginx, upgrade lodash to lodash-es

Example 2: Core Web Vitals Fix

  • LCP: 3.8s → 1.9s (fix: preload hero image, use next/image)
  • INP: 450ms → 180ms (fix: move blocking script to worker, debounce input handler)
  • CLS: 0.18 → 0.05 (fix: reserve space for ads, set explicit dimensions)

Example 3: Database Query Optimization

  • Identified 8 N+1 queries in user dashboard
  • Added indexes on user_id, created_at columns
  • Connection pool tuned: min 5 → 10, max 20 → 40
  • Query time reduced from 2.3s to 340ms

What's Included

  • SKILL.md: Complete performance tuning framework with measurement targets and command references
  • Lighthouse Audit Script: Ready-to-run commands for local performance testing
  • Bundle Analysis Checklist: Step-by-step dependency audit and replacement suggestions
  • Core Web Vitals Targets Table: 2026 good/needs-work/poor thresholds for LCP, INP, CLS
  • Performance Quick Wins: Common bloat sources and high-impact fixes by framework

Who It's For

  • Full-stack engineers optimizing Next.js or React applications
  • Performance engineers auditing and improving web vitals
  • Backend developers tuning Python database queries and caching
  • DevOps engineers configuring CDN and caching strategies
  • Product managers focused on conversion and SEO improvements

Best For

  • Fixing slow page loads and Core Web Vitals failures
  • Reducing JavaScript bundle size and improving time-to-interactive
  • Diagnosing N+1 queries and database bottlenecks
  • Optimizing image, font, and asset loading strategies
  • Planning code-splitting and lazy-loading architecture
  • Analyzing Lighthouse reports and prioritizing improvements

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