Firecrawl Website Design Clone logo

Firecrawl Website Design Clone

Organization
firecrawl
firecrawl-website-design-clone

Extract any website's design system into an agent-ready DESIGN.md using Firecrawl scrape evidence. Use when the user wants colors, fonts, spacing, components, layout patterns, or brand/UI guidance from a website so AI agents can create new websites, clone a look, or build pages inspired by that design.

Overview

Publisherfirecrawl
Repositoryfirecrawl-workflows
Skill namefirecrawl-website-design-clone
Stars
175
Forks
38
Bundled files
Instructions only
LicenseISC
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 firecrawl on GitHub. Read the source before you install it.

Installation

Install the Firecrawl Website Design Clone 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.
    https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-website-design-clone
  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/firecrawl/firecrawl-workflows.git /tmp/firecrawl-workflows
mkdir -p .claude/skills
cp -r /tmp/firecrawl-workflows/skills/firecrawl-website-design-clone .claude/skills/firecrawl-website-design-clone
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Firecrawl Website Design Clone 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 Firecrawl Website Design Clone 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 Firecrawl Website Design Clone 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.

Firecrawl Website Design Clone

Use this when the user wants one URL turned into a practical design system file agents can use immediately.

Default outcome: extract any website's design system in one line and format it as DESIGN.md.

The skill should feel like a thin workflow around Firecrawl scrape: gather the page's visible content, structure, metadata, links, and available visual signals, then synthesize those findings into a clean design-system markdown file.

Onboarding Interview

Infer the source URL, target stack, and whether implementation is requested from context. If the user gives a URL and asks for a design system, proceed immediately.

Ask at most 1-3 concise questions only if blocked, such as the website URL, whether to output only DESIGN.md or also implement, or a required target stack.

Use the host agent's normal prompt or modal UI. Do not name a harness-specific question function.

Firecrawl Collection Plan

Use Firecrawl through the CLI or equivalent tool surface. Always start with two parallel scrapes of the supplied URL:

  1. The branding and images formats together for structured design tokens and the full set of page images.
  2. A full-page screenshot for visual context.

Example:

bash
firecrawl scrape "https://example.com" --format branding,images -o ".firecrawl/example-branding.json" --pretty &
firecrawl scrape "https://example.com" --full-page-screenshot -o ".firecrawl/example-screenshot.png" &
wait

Combining branding and images in one call still costs a single credit and is required: the branding block only surfaces curated brand assets (logo, favicon, ogImage, logoHref), so without images the agent will miss the page's actual content imagery (heroes, product shots, carousel slides, feature visuals, illustrations, accessory photos, end-of-page artwork, and similar). On a product page like tesla.com/cybertruck the branding block has no hero — only images returns the main Cybertruck hero (e.g. Cybertruck-Hero-Desktop-NA-SA-APAC.png) and the rest of the page's photography.

If the screenshot scrape returns a remote image URL (e.g. signed storage link) instead of a local file, download it to the same .firecrawl/ path so DESIGN.md can reference a stable local asset.

Use the structured branding output as the primary source for colors, typography, components, brand assets (logo, favicon, ogImage), personality, and confidence notes. Use the images list as the source of truth for the page's content imagery — hero photography, product shots, carousels, feature visuals, illustrations, and decorative graphics. Use the screenshot as the primary visual reference for layout, hierarchy, and overall feel. Add supplemental formats only when these are insufficient for the final artifact.

Collect:

  • branding data for colors, typography, spacing, buttons, logos, brand imagery, personality, and confidence
  • the full images list for hero, product, feature, and section imagery beyond the curated brand assets
  • a full-page screenshot saved locally in .firecrawl/ so it can be embedded in DESIGN.md
  • page markdown for headings, copy hierarchy, CTAs, navigation, and section order when needed
  • metadata and links for brand, product, and page-purpose clues when needed
  • HTML only when the branding output, images list, and screenshot are insufficient to infer classes, font names, CSS variables, or component structure
  • related pages only when the user asks for a broader site system

Do not over-crawl by default. The first version should be useful from a single representative page.

What To Extract

Infer and document the site's design language:

  • colors: primary, secondary, accents, backgrounds, borders, text, states
  • typography: font families if detectable, type scale, weights, line heights, heading/body treatment
  • spacing: container widths, section rhythm, grid gaps, padding scale, density
  • layout: page structure, hero patterns, cards, grids, nav, footer, responsive assumptions
  • components: buttons, inputs, cards, badges, nav items, pricing blocks, testimonials, feature rows, forms
  • imagery and icons: style, shape language, illustration/photo treatment, logo constraints; pull representative hero, product, feature, and section images from the full images list rather than relying on branding.images, which only carries logo, favicon, ogImage, and logoHref
  • motion and interaction: hover states, transitions, animation style when observable or inferable
  • voice and content patterns: CTA wording, heading style, product copy rhythm

When a value cannot be measured exactly from scrape output, label it as inferred and give a practical approximation.

Parallel Work

If appropriate, use sub-agents or equivalent parallel task runners. Natural splits include one page per researcher for multi-page sites, or one reviewer each for colors, typography, spacing, and components.

Each parallel researcher should return source URLs, extracted evidence, inferred design tokens, and confidence notes.

Final Deliverable

Create or return a DESIGN.md with this structure. Embed the full-page screenshot near the top so a coding agent gets visual context alongside the tokens.

markdown
# DESIGN.md: [Source Site]

## Source
- URL: [source URL]
- Capture date: [date]
- Evidence: [scrape/screenshot/html/links used]

## Reference Screenshot
![Full-page screenshot of [Source Site]](./.firecrawl/[source]-screenshot.png)

Use this screenshot as the visual source of truth for layout, hierarchy, density, and feel. Tokens below describe the same page in machine-readable form.

## Design Summary
[Short description of the visual language and what an agent should recreate]

## Design Tokens

### Colors
[Named color roles with hex values when known; mark inferred values clearly]

### Typography
[Fonts, fallback recommendations, scale, weights, heading/body rules]

### Spacing And Layout
[Spacing scale, containers, grids, radius, shadows, borders]

## Components
[Buttons, cards, nav, forms, hero, feature sections, pricing, footer, etc.]

## Page Patterns
[Section order, common layouts, responsive behavior]

## Content Style
[Voice, CTA style, heading patterns, copy density]

## Agent Build Instructions
[Concrete instructions an AI coding agent can follow to create a new site in this style]

## Rerun Inputs
workflow: firecrawl-website-design-clone
source_url: [url]
target_stack: [stack]
output: DESIGN.md

If the user asks to implement, first produce or update DESIGN.md, then use it as the source of truth for the build.

Quality Bar

  • Do not imply the user has rights to third-party logos, images, trademarks, or copy.
  • Prefer reusable design tokens over one-off observations.
  • Distinguish observed facts from inferred approximations.
  • Keep the output compact enough that another agent can paste it into context and build from it.
  • Preserve source URLs and scrape artifacts for review.

Frequently asked questions

What does the Firecrawl Website Design Clone AI skill do?

Extract any website's design system into an agent-ready DESIGN.md using Firecrawl scrape evidence. Use when the user wants colors, fonts, spacing, components, layout patterns, or brand/UI guidance from a website so AI agents can create new websites, clone a look, or build pages inspired by that design.

Why use Firecrawl Website Design Clone on TypingMind?

Because you install it once and use it with any model. Firecrawl Website Design Clone 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 Firecrawl Website Design Clone in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/firecrawl/firecrawl-workflows/tree/main/skills/firecrawl-website-design-clone. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Firecrawl Website Design Clone?

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 Firecrawl Website Design Clone?

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

Is the Firecrawl Website Design Clone AI skill free?

Yes. It is published on GitHub by firecrawl under the ISC 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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