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Page Speed

Community
ominou5
page-speed

Page speed optimization guidelines and implementation patterns. Ensures all funnel pages meet Core Web Vitals targets for LCP < 2.5s, FID < 100ms, and CLS < 0.1.

Overview

Publisherominou5
Repositoryfunnel-architect-plugin
Skill namepage-speed
Stars
83
Forks
18
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 ominou5 on GitHub. Read the source before you install it.

Installation

Install the Page Speed 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/ominou5/funnel-architect-plugin.git /tmp/funnel-architect-plugin
mkdir -p .claude/skills
cp -r /tmp/funnel-architect-plugin/skills/page-speed .claude/skills/page-speed
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Page Speed 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 Page Speed 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 Page Speed 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.

Page Speed Optimization

Every funnel page must load fast. Slow pages kill conversions — a 1-second delay reduces conversions by 7%.

Core Web Vitals Targets

MetricTargetImpact
LCP (Largest Contentful Paint)< 2.5sMain content visible
FID (First Input Delay)< 100msPage is interactive
CLS (Cumulative Layout Shift)< 0.1No visual jumping
TTFB (Time to First Byte)< 800msServer responds fast

Required Optimizations

1. Critical CSS Inlining

Inline above-the-fold CSS directly in <head> to eliminate render-blocking:

html
<head>
  <style>
    /* Critical: hero, nav, above-fold layout only */
    .hero { /* ... */ }
    .nav { /* ... */ }
    .cta-primary { /* ... */ }
  </style>
  <!-- Defer the rest -->
  <link rel="preload" href="styles.css" as="style" onload="this.onload=null;this.rel='stylesheet'">
  <noscript><link rel="stylesheet" href="styles.css"></noscript>
</head>

2. Image Optimization

html
<!-- Always include width/height to prevent CLS -->
<img
  src="hero.webp"
  alt="Descriptive alt text"
  width="800"
  height="450"
  loading="lazy"
  decoding="async"
>

<!-- Responsive images with srcset -->
<img
  srcset="hero-400.webp 400w, hero-800.webp 800w, hero-1200.webp 1200w"
  sizes="(max-width: 600px) 400px, (max-width: 1000px) 800px, 1200px"
  src="hero-800.webp"
  alt="Descriptive alt text"
  width="800"
  height="450"
  loading="lazy"
>

3. Font Loading

css
@font-face {
  font-family: 'BrandFont';
  src: url('brand-font.woff2') format('woff2');
  font-display: swap; /* Always include this */
  font-weight: 400;
}
html
<!-- Preload critical fonts -->
<link rel="preload" href="brand-font.woff2" as="font" type="font/woff2" crossorigin>

4. Script Loading

html
<!-- Defer non-critical scripts -->
<script defer src="analytics.js"></script>
<script defer src="interactions.js"></script>

<!-- Async for independent scripts -->
<script async src="third-party-widget.js"></script>

<!-- Never do this -->
<!-- <script src="blocking.js"></script> in <head> -->

5. Preconnect to Third Parties

html
<head>
  <link rel="preconnect" href="https://fonts.googleapis.com">
  <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
  <link rel="preconnect" href="https://www.googletagmanager.com">
</head>

Performance Budget

ResourceBudget
Total page weight< 500KB
HTML< 50KB
CSS< 50KB
JavaScript< 100KB
Images (above fold)< 200KB
Fonts< 100KB
Third-party scripts< 50KB

Quick Audit Checklist

  • Viewport meta tag present
  • All images have width/height attributes
  • Below-fold images use loading="lazy"
  • No render-blocking scripts in <head>
  • font-display: swap on all @font-face
  • Critical CSS inlined
  • Third-party origins preconnected
  • No unused CSS/JS shipped
  • Images in WebP/AVIF format
  • Total page weight under 500KB

Frequently asked questions

What does the Page Speed AI skill do?

Page speed optimization guidelines and implementation patterns. Ensures all funnel pages meet Core Web Vitals targets for LCP < 2.5s, FID < 100ms, and CLS < 0.1.

Why use Page Speed on TypingMind?

Because you install it once and use it with any model. Page Speed 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 Page Speed in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ominou5/funnel-architect-plugin/tree/main/skills/page-speed. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Page Speed?

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 Page Speed?

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

Is the Page Speed AI skill free?

Yes. It is published on GitHub by ominou5 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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