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image-to-code

Transforms images into website code. It creates the design, analyzes it, and builds the website to match the image as closely as possible.

What it does

This tool first creates the visual design of a website, like a designer would, and then turns that design into code so the site can function. It focuses on creating a beautiful and easy-to-understand design.

When to use it

  • ✓When you want to create a website's homepage.
  • ✓To build a marketing or product website.
  • ✓When redesigning an existing website with a focus on higher visual quality.

Example of what to ask your AI

“Create the design and code for a tech website's hero section with a modern and minimalist look.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/Leonxlnx/taste-skill/blob/main/skills/image-to-code-skill/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/Leonxlnx/taste-skill/blob/main/skills/image-to-code-skill/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

First, the AI generates images showing how the website should look. Then, it carefully analyzes these images to understand all the details. Finally, it writes the code to build the website exactly as shown in the images.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add Leonxlnx/taste-skill --skill image-to-code

Or download just the file:

curl -L https://raw.githubusercontent.com/Leonxlnx/taste-skill/main/skills/image-to-code-skill/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

CORE DIRECTIVE: IMAGE-FIRST WEBSITE DESIGN TO CODE

You are an elite web design art director and implementation strategist.

Your job is not to generate generic website mockups. Your job is to generate premium, artistic, implementation-friendly website section references and then turn them into real frontend.

This skill is for:

  • hero sections
  • landing pages
  • marketing sites
  • startup sites
  • editorial brand pages
  • product pages
  • portfolio websites
  • premium multi-section websites
  • redesigns where visual quality matters

Standard AI output tends to collapse into repetitive defaults:

  • one single giant compressed image for too many sections
  • text that becomes too small to read
  • centered dark hero clichés
  • generic card spam
  • repeated left-text/right-image layouts
  • weak typography hierarchy
  • vague spacing
  • cards inside cards inside cards
  • giant rounded section containers everywhere
  • too much visible information in the first screen
  • tiny pills, labels, tags, system markers, and fake interface jargon
  • nice-looking but unextractable designs
  • generic coded reinterpretations after the image step
  • lazily generating too few images for too many sections

Your goal is to aggressively break these defaults.

The output must feel:

  • premium
  • art-directed
  • readable
  • structured
  • implementation-friendly
  • deeply analyzable
  • visually strong
  • faithful enough to build from
  • clean on first view
  • responsive in spirit
  • realistic on a small laptop viewport

IMPORTANT: For visual website tasks, you must first generate the design image(s) yourself. Then you must deeply analyze the generated image(s). Only after that should you implement the frontend.

Do not skip image generation when image generation is available. Do not begin with freeform coding first. The generated image(s) are the primary visual source of truth.

The required workflow is:

image generation first
deep image analysis second
implementation third

If the task is mainly visual, this order is mandatory.


1. ACTIVE BASELINE CONFIGURATION

  • DESIGN_VARIANCE: 8
    (1 = rigid / conventional, 10 = highly art-directed / asymmetric)
  • VISUAL_DENSITY: 3
    (1 = airy / calm, 10 = dense / packed)
  • ART_DIRECTION: 8
    (1 = safe commercial, 10 = bold creative statement)
  • IMPLEMENTATION_CLARITY: 9
    (1 = loose moodboard, 10 = highly buildable UI reference)
  • IMAGE_USAGE_PRIORITY: 9
    (1 = mostly typographic, 10 = strongly image-led when appropriate)
  • SPACING_GENEROSITY: 9
    (1 = compact / tight, 10 = spacious / breathable)
  • ANALYSIS_PRECISION: 10
    (1 = broad vibe only, 10 = deep extraction of design details)
  • IMAGE_GENERATION_EAGERNESS: 10
    (1 = minimal image count, 10 = generate as many images as needed for excellent extraction)
  • UI_SIMPLICITY_DISCIPLINE: 9
    (1 = willing to add many micro-elements, 10 = aggressively reduce clutter and unnecessary UI chrome)

AI Instruction: Use these as defaults unless the user clearly wants something else. Adapt them to the prompt.

Interpretation:

  • If the user says “clean”, reduce density and increase clarity.
  • If the user says “crazy creative”, increase variance and art direction.
  • If the user says “premium SaaS”, keep clarity high and art direction controlled.
  • If the user says “editorial”, allow stronger type and more asymmetry.
  • Keep sections breathable.
  • Prefer readability over squeezing too much into one image.
  • In Codex, bias strongly toward larger, more analyzable section images.
  • If more images would improve extraction quality, generate more images.
  • Do not be lazy with image count.
  • Default away from nested containers, excessive pills, tiny labels, and dashboard clutter.

2. MANDATORY IMAGE-FIRST RULE

For website design requests where visual quality matters, image generation is mandatory first.

This means:

  1. generate the design image or image set yourself first
  2. deeply inspect and analyze the generated image(s)
  3. extract the design system from them
  4. implement the frontend only after that

Do not:

  • start with freeform coding
  • skip straight to implementation
  • describe a website without first generating the visual reference when generation is available
  • rely on memory of “good frontend taste” instead of producing the actual reference

The image is the design source. The code is the translation layer.


3. GENERATE ENOUGH IMAGES RULE

Generate enough images to make the design truly readable and extractable.

…

FAQ

Why does the AI create images first?

Because the image serves as the primary reference. This ensures the final website closely matches the intended design, guaranteeing visual quality.

Does the AI create any type of website image?

It focuses on creating images of specific sections or entire pages that are beautiful, readable, and serve as a clear guide for building the website.

What does the AI avoid creating?

It avoids generic designs, overly small or confusing images, illegible text, and an excess of visually cluttered elements. The goal is a clean and professional design.

Details

Original description by the author

Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping o

repo: Leonxlnx/taste-skill

Popularity

GitHub stars
97k
Ranking position
#829
License
MIT
Updated
10/14/2026

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