How to Optimize Core Web Vitals (LCP, INP, CLS) for AI-Generated Landing Pages

Optimize Core Web Vitals for AI-generated landing pages by chaining specific skills in the Leonxlnx/taste-skill repository—using minimalist-skill for lightweight assets, imagegen-frontend-web for WebP/AVIF formats, and output-skill with scriptStrategy: "defer"—to achieve LCP under 2.5s, INP under 100ms, and CLS under 0.1.

The taste-skill repository provides a modular framework where markdown-based skills define workflows for AI-generated landing-page content. Each skill resides in the skills/ directory and controls specific rendering layers, from image generation to HTML assembly. By configuring these skills to manage asset delivery, script loading, and dimensional stability, you systematically tune Largest Contentful Paint (LCP), Interaction-to-Next-Paint (INP), and Cumulative Layout Shift (CLS) without sacrificing generative content quality.

Optimize Largest Contentful Paint (LCP) with Lightweight Assets

LCP measures the render time of the largest visible element, typically the hero image or primary heading. The skills/minimalist-skill/SKILL.md workflow reduces LCP by stripping non-essential decorative assets and limiting high-resolution image counts in hero sections. Pair this with skills/imagegen-frontend-web/SKILL.md, which outputs modern WebP/AVIF formats and automatically injects explicit width/height attributes along with loading="lazy" for below-the-fold assets, eliminating decode delays that push LCP beyond the 2.5s threshold.

Minimize Interaction-to-Next-Paint (INP) via Script Strategy

INP captures the latency of the slowest user interaction throughout the page lifecycle. In skills/output-skill/SKILL.md, set the scriptStrategy parameter to "defer" to prevent non-critical JavaScript from blocking the main thread during user gestures. The skills/stitch-skill/SKILL.md orchestrates fragment merging to respect loading order, ensuring interactive elements like buttons and forms become responsive before ancillary scripts execute, keeping INP below 100ms.

Eliminate Cumulative Layout Shift (CLS) with Explicit Dimensions

CLS occurs when visible elements shift position after initial render, often due to missing size attributes on images or dynamic content injection. Enable the preserve-size flag in skills/redesign-skill/SKILL.md to write explicit width/height attributes into all HTML fragments. The skills/brutalist-skill/SKILL.md and skills/soft-skill/SKILL.md workflows further stabilize layouts by declaring dimensions for videos and iframes, while injecting fallback CSS rules that reserve vertical space for AI-generated headings before text streams arrive, maintaining CLS under 0.1.

Step-by-Step Optimization Workflow

Follow this sequence to implement performance tuning across the three architectural layers:

1. Initialize the Minimalist skill to remove visual noise and reduce hero image weight.
2. Generate optimized images using ImageGen-frontend-web with --format webp and --quality 80 to produce next-gen assets.
3. Enforce dimensional constraints by activating preserve-size in the Redesign skill, ensuring all media carries explicit size attributes.
4. Defer non-critical JavaScript via the Output skill's scriptStrategy: "defer" setting, keeping critical CSS inline while pushing scripts to the bottom of the body.
5. Audit the generated page using Lighthouse or PageSpeed Insights to verify targets: LCP < 2.5s, INP < 100ms, CLS < 0.1.

Automating Performance Tuning with skill.sh

The repository includes skill.sh as a convenience wrapper for invoking skills from the command line. This script reads the corresponding SKILL.md files, loads hidden configuration blocks, and calls the underlying Instagit API.

# 1️⃣ Generate a lightweight hero image in WebP format

./skill.sh run imagegen-frontend-web \
  --format webp \
  --quality 80 \
  --output assets/hero.webp

# 2️⃣ Build the page with minimal layout and explicit sizes

./skill.sh run minimalist-skill \
  --hero assets/hero.webp \
  --headline "Delicious AI-Powered Design"

# 3️⃣ Stitch fragments together with deferred scripts

./skill.sh run stitch-skill \
  --defer-scripts true \
  --output dist/index.html

Adjust the flags to match your desired performance profile, ensuring the final dist/index.html meets Core Web Vitals thresholds before deployment.

Summary

• LCP optimization relies on skills/minimalist-skill/SKILL.md for lightweight heroes and skills/imagegen-frontend-web/SKILL.md for WebP/AVIF generation with explicit dimensions.
• INP reduction requires configuring scriptStrategy: "defer" in skills/output-skill/SKILL.md and proper fragment ordering via skills/stitch-skill/SKILL.md.
• CLS prevention depends on the preserve-size flag in skills/redesign-skill/SKILL.md and space reservation rules in skills/soft-skill/SKILL.md.
• Use skill.sh to chain these optimizations into automated workflows that produce performance-first AI landing pages.

Frequently Asked Questions

What is the taste-skill repository?

The taste-skill repository by Leonxlnx is a collection of markdown-based skill definitions that drive AI-generated landing-page content. Each skill describes a self-contained workflow for design, layout, or asset generation, which the Instagit platform stitches together to produce complete HTML pages according to the core definition in skills/taste-skill/SKILL.md.

How does the minimalist-skill improve LCP scores?

The skills/minimalist-skill/SKILL.md workflow improves Largest Contentful Paint by reducing the weight of hero sections through fewer high-resolution images and smaller type scales. This directly decreases the render time of the largest visible element, keeping LCP under the 2.5-second threshold recommended by Google.

Can I apply these optimizations to existing landing pages or only new AI-generated ones?

These optimizations are designed specifically for the AI generation pipeline defined in the taste-skill repository. While the principles apply broadly to any web page, the specific implementations—such as the preserve-size flag and scriptStrategy parameters—require execution through the Instagit platform and skill.sh wrapper as outlined in the respective SKILL.md files.

Which skill controls the final HTML output and script loading?

The skills/output-skill/SKILL.md controls final HTML rendering and supports the scriptStrategy parameter to inject async or defer attributes on scripts. This skill works in conjunction with skills/stitch-skill/SKILL.md to ensure the final page structure prioritizes critical rendering paths for optimal Core Web Vitals.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}