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Optimize

CommunityPopular
fengshao1227
optimize

Diagnoses and fixes UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

Overview

Publisherfengshao1227
Repositoryccg-workflow
Skill nameoptimize
Stars
5.9K
Forks
446
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by fengshao1227 on GitHub. Read the source before you install it.

Installation

Install the Optimize AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/fengshao1227/ccg-workflow.git /tmp/ccg-workflow
mkdir -p .claude/skills
cp -r /tmp/ccg-workflow/templates/skills/impeccable/optimize .claude/skills/optimize
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Optimize in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Optimize on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Optimize is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Identify and fix performance issues to create faster, smoother user experiences.

Assess Performance Issues

Understand current performance and identify problems:

  1. Measure current state:

    • Core Web Vitals: LCP, FID/INP, CLS scores
    • Load time: Time to interactive, first contentful paint
    • Bundle size: JavaScript, CSS, image sizes
    • Runtime performance: Frame rate, memory usage, CPU usage
    • Network: Request count, payload sizes, waterfall
  2. Identify bottlenecks:

    • What's slow? (Initial load? Interactions? Animations?)
    • What's causing it? (Large images? Expensive JavaScript? Layout thrashing?)
    • How bad is it? (Perceivable? Annoying? Blocking?)
    • Who's affected? (All users? Mobile only? Slow connections?)

CRITICAL: Measure before and after. Premature optimization wastes time. Optimize what actually matters.

Optimization Strategy

Create systematic improvement plan:

Loading Performance

Optimize Images:

  • Use modern formats (WebP, AVIF)
  • Proper sizing (don't load 3000px image for 300px display)
  • Lazy loading for below-fold images
  • Responsive images (srcset, picture element)
  • Compress images (80-85% quality is usually imperceptible)
  • Use CDN for faster delivery
html
<img 
  src="hero.webp"
  srcset="hero-400.webp 400w, hero-800.webp 800w, hero-1200.webp 1200w"
  sizes="(max-width: 400px) 400px, (max-width: 800px) 800px, 1200px"
  loading="lazy"
  alt="Hero image"
/>

Reduce JavaScript Bundle:

  • Code splitting (route-based, component-based)
  • Tree shaking (remove unused code)
  • Remove unused dependencies
  • Lazy load non-critical code
  • Use dynamic imports for large components
javascript
// Lazy load heavy component
const HeavyChart = lazy(() => import('./HeavyChart'));

Optimize CSS:

  • Remove unused CSS
  • Critical CSS inline, rest async
  • Minimize CSS files
  • Use CSS containment for independent regions

Optimize Fonts:

  • Use font-display: swap or optional
  • Subset fonts (only characters you need)
  • Preload critical fonts
  • Use system fonts when appropriate
  • Limit font weights loaded
css
@font-face {
  font-family: 'CustomFont';
  src: url('/fonts/custom.woff2') format('woff2');
  font-display: swap; /* Show fallback immediately */
  unicode-range: U+0020-007F; /* Basic Latin only */
}

Optimize Loading Strategy:

  • Critical resources first (async/defer non-critical)
  • Preload critical assets
  • Prefetch likely next pages
  • Service worker for offline/caching
  • HTTP/2 or HTTP/3 for multiplexing

Rendering Performance

Avoid Layout Thrashing:

javascript
// ❌ Bad: Alternating reads and writes (causes reflows)
elements.forEach(el => {
  const height = el.offsetHeight; // Read (forces layout)
  el.style.height = height * 2; // Write
});

// ✅ Good: Batch reads, then batch writes
const heights = elements.map(el => el.offsetHeight); // All reads
elements.forEach((el, i) => {
  el.style.height = heights[i] * 2; // All writes
});

Optimize Rendering:

  • Use CSS contain property for independent regions
  • Minimize DOM depth (flatter is faster)
  • Reduce DOM size (fewer elements)
  • Use content-visibility: auto for long lists
  • Virtual scrolling for very long lists (react-window, react-virtualized)

Reduce Paint & Composite:

  • Use transform and opacity for animations (GPU-accelerated)
  • Avoid animating layout properties (width, height, top, left)
  • Use will-change sparingly for known expensive operations
  • Minimize paint areas (smaller is faster)

Animation Performance

GPU Acceleration:

css
/* ✅ GPU-accelerated (fast) */
.animated {
  transform: translateX(100px);
  opacity: 0.5;
}

/* ❌ CPU-bound (slow) */
.animated {
  left: 100px;
  width: 300px;
}

Smooth 60fps:

  • Target 16ms per frame (60fps)
  • Use requestAnimationFrame for JS animations
  • Debounce/throttle scroll handlers
  • Use CSS animations when possible
  • Avoid long-running JavaScript during animations

Intersection Observer:

javascript
// Efficiently detect when elements enter viewport
const observer = new IntersectionObserver((entries) => {
  entries.forEach(entry => {
    if (entry.isIntersecting) {
      // Element is visible, lazy load or animate
    }
  });
});

React/Framework Optimization

React-specific:

  • Use memo() for expensive components
  • useMemo() and useCallback() for expensive computations
  • Virtualize long lists
  • Code split routes
  • Avoid inline function creation in render
  • Use React DevTools Profiler

Framework-agnostic:

  • Minimize re-renders
  • Debounce expensive operations
  • Memoize computed values
  • Lazy load routes and components

Network Optimization

Reduce Requests:

  • Combine small files
  • Use SVG sprites for icons
  • Inline small critical assets
  • Remove unused third-party scripts

Optimize APIs:

  • Use pagination (don't load everything)
  • GraphQL to request only needed fields
  • Response compression (gzip, brotli)
  • HTTP caching headers
  • CDN for static assets

Optimize for Slow Connections:

  • Adaptive loading based on connection (navigator.connection)
  • Optimistic UI updates
  • Request prioritization
  • Progressive enhancement

Core Web Vitals Optimization

Largest Contentful Paint (LCP < 2.5s)

  • Optimize hero images
  • Inline critical CSS
  • Preload key resources
  • Use CDN
  • Server-side rendering

First Input Delay (FID < 100ms) / INP (< 200ms)

  • Break up long tasks
  • Defer non-critical JavaScript
  • Use web workers for heavy computation
  • Reduce JavaScript execution time

Cumulative Layout Shift (CLS < 0.1)

  • Set dimensions on images and videos
  • Don't inject content above existing content
  • Use aspect-ratio CSS property
  • Reserve space for ads/embeds
  • Avoid animations that cause layout shifts
css
/* Reserve space for image */
.image-container {
  aspect-ratio: 16 / 9;
}

Performance Monitoring

Tools to use:

  • Chrome DevTools (Lighthouse, Performance panel)
  • WebPageTest
  • Core Web Vitals (Chrome UX Report)
  • Bundle analyzers (webpack-bundle-analyzer)
  • Performance monitoring (Sentry, DataDog, New Relic)

Key metrics:

  • LCP, FID/INP, CLS (Core Web Vitals)
  • Time to Interactive (TTI)
  • First Contentful Paint (FCP)
  • Total Blocking Time (TBT)
  • Bundle size
  • Request count

IMPORTANT: Measure on real devices with real network conditions. Desktop Chrome with fast connection isn't representative.

NEVER:

  • Optimize without measuring (premature optimization)
  • Sacrifice accessibility for performance
  • Break functionality while optimizing
  • Use will-change everywhere (creates new layers, uses memory)
  • Lazy load above-fold content
  • Optimize micro-optimizations while ignoring major issues (optimize the biggest bottleneck first)
  • Forget about mobile performance (often slower devices, slower connections)

Verify Improvements

Test that optimizations worked:

  • Before/after metrics: Compare Lighthouse scores
  • Real user monitoring: Track improvements for real users
  • Different devices: Test on low-end Android, not just flagship iPhone
  • Slow connections: Throttle to 3G, test experience
  • No regressions: Ensure functionality still works
  • User perception: Does it feel faster?

Remember: Performance is a feature. Fast experiences feel more responsive, more polished, more professional. Optimize systematically, measure ruthlessly, and prioritize user-perceived performance.

Frequently asked questions

What does the Optimize AI skill do?

Diagnoses and fixes UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

Why use Optimize on TypingMind?

Because you install it once and use it with any model. Optimize is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Optimize in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fengshao1227/ccg-workflow/tree/main/templates/skills/impeccable/optimize. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Optimize?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Optimize?

As many as you like. As long as a model supports skills, you can use Optimize with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Optimize AI skill free?

Yes. It is published on GitHub by fengshao1227 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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