本文へ移動
cccskills
無料GitHub で公開

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.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md7.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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:

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.

# 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.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Extract structured company lists from directories with Firecrawl. Use for scraping YC, Crunchbase, Product Hunt, G2, startup directories, category directories, or custom company databases into JSON, CSV, CRM-ready lists, or research tables.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-workflows1892026年8月21日 更新

Monitor competitor pricing, features, changelogs, dashboards, and product changes with Firecrawl. Use for recurring competitive intelligence, pricing tier extraction, feature change tracking, or structured competitor alerts.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-workflows1892026年8月21日 更新

Pull metrics from analytics dashboards and internal web tools with Firecrawl browser. Use when the user needs dashboard reporting, cross-platform metric summaries, authenticated analytics extraction, date-range reports, or structured metrics from web dashboards.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-workflows1892026年8月21日 更新

Produce an intensive, cited analytical report: executive summary, multi-angle findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-workflows1892026年8月21日 更新

Walk through a product's key flows with Firecrawl browser and produce a structured UX/product walkthrough. Use for signup, onboarding, pricing, docs, dashboard, product demo prep, UX teardown, and first-run experience analysis.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-workflows1892026年8月21日 更新

Build a knowledge base from web content with Firecrawl. Use for local reference docs, RAG-ready chunks, fine-tuning datasets, documentation mirrors, topic corpora, or LLM-ready markdown organized from web sources.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-workflows1892026年8月21日 更新

firecrawl のスキルをすべて見る

このスキルの問題を報告する