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Docs Crawler

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CaesiumY
docs-crawler

Crawl an entire documentation or design-system website into one LLM-ready Markdown corpus. Discovers every page from the site's sitemap.xml (with a same-origin link-following fallback when there is no sitemap), extracts each page's main content as clean Markdown, downloads each page's images (and inline base64 images) into a local folder referenced by relative paths, and renders JavaScript-heavy pages with a headless browser. Use this whenever someone wants the WHOLE of a multi-page docs site, design-system site, API reference, component library, or knowledge base turned into Markdown — for example "crawl this docs site", "turn this design system site into markdown", "make an LLM or RAG corpus from these docs", "mirror the entire documentation", "archive the whole knowledge base", or "give an AI the full X documentation". It applies even when the user never says the word "crawl" — any request to capture, ingest, archive, or convert a whole site's documentation pages into text fits. The design-md skill also calls it during research to gather a brand's published design-system docs. Do not use it for reading or summarizing a single page, for scraping structured data such as prices into a spreadsheet, or for generating a sitemap.

Overview

PublisherCaesiumY
Repositoryko-design-md
Skill namedocs-crawler
Stars
65
Forks
5
Bundled files
16
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.

  • 16 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by CaesiumY on GitHub. Read the source before you install it.

Installation

Install the Docs Crawler 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/CaesiumY/ko-design-md/tree/main/.claude/skills/docs-crawler
  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/CaesiumY/ko-design-md.git /tmp/ko-design-md
mkdir -p .claude/skills
cp -r /tmp/ko-design-md/.claude/skills/docs-crawler .claude/skills/docs-crawler
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Docs Crawler 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 Docs Crawler 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 Docs Crawler 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.

docs-crawler

Crawl a documentation website into a single Markdown corpus that an LLM can consume as context.

When to use

The user wants to capture a multi-page documentation, design-system, or reference site as Markdown — to feed an LLM, archive it, or research a design system. This skill is also invoked by the design-md skill's research phase.

Inputs

  • Site URL (required) — the documentation site, e.g. https://socarframe.socar.kr/. Any page on the site works; page discovery starts from the site's sitemap.xml.
  • Output directory (optional) — where to write the corpus. Defaults to ./{host}-docs/ in the current working directory.

If the user has not provided a URL, ask for one — do not guess.

Running the crawl

From the repository root:

pnpm crawl:docs <site-url> [--out <dir>] [--external-images]

Equivalent direct form:

pnpm exec tsx .claude/skills/docs-crawler/scripts/crawl.ts <site-url> [--out <dir>]

The engine discovers pages via sitemap.xml (falling back to same-origin link-following), fetches each page, extracts the main content, and converts it to Markdown. It prints per-page progress and a final summary line.

By default it also localizes images: every external image and inline base64 data: image is downloaded into crawl/images/ and the Markdown is rewritten to relative paths, so the corpus is self-contained for renderers that can't fetch external URLs (Claude Design, offline previews). Pass --external-images to skip downloading and keep the original external URLs instead.

Output

These artifacts are written under the output directory:

  • crawl-corpus.md — every successful page merged into one document, with a table of contents and a Source: URL per page. This is the primary deliverable.
  • crawl/pages/{NNN}-{slug}.md — one file per page, each with source_url / title / method frontmatter.
  • crawl/images/ — downloaded image files (skipped with --external-images), referenced from the corpus and page files by relative paths.
  • crawl/manifest.json — a per-URL audit log (status, fetch method, extracted character count, error reason).

After crawling

Report back to the user:

  • How many pages succeeded versus failed (from the summary line or crawl/manifest.json).
  • The path to crawl-corpus.md.
  • If any pages failed, list them from the manifest with the reason (e.g. disallowed by robots.txt, no extractable content).

Do not paste the whole corpus into the conversation — point the user at the file. The corpus can be large.

Output location and the design-md skill

The --out argument controls where everything is written. When the design-md skill calls this crawler during its research phase, it passes --out pointing at its cache directory (.claude/cache/design-md/{slug}/), so the resulting crawl-corpus.md (and the localized crawl/images/) land where research-collector can read and cite them. The whole cache directory is gitignored, so downloaded images stay out of version control. Nothing special is needed for that case — just run the crawl with the given --out.

Notes and edge cases

  • No sitemap — discovery automatically falls back to following same-origin links from the start URL.
  • JavaScript-rendered sites — if a page returns an empty shell, the engine re-fetches it through a headless browser. Chromium is installed automatically on first need (~150 MB, one-time). Static sites never launch a browser.
  • Images are downloaded into crawl/images/ by default and referenced by relative paths, so the corpus is self-contained — this covers external <img> URLs and inline base64 data: images alike. A non-base64 (percent-encoded) data: URI, or any image whose bytes fail to download or decode, instead becomes an inline-image-omitted placeholder (alt and title text are kept) so raw base64 never bloats the corpus. With --external-images the crawler downloads nothing: external URLs stay as-is and inline data: images collapse to the placeholder.
  • Few or no images is normal, especially for design-system sites — modern docs and design-system sites (Docusaurus and similar) render icons and component visuals as inline <svg>, CSS, or live DOM rather than <img> files; any real <img> (e.g. a navbar logo) is usually site chrome the content extractor correctly drops. An image-light or image-free corpus is expected in that case — it is not a crawl failure. Capture visuals separately (screenshots) if the research needs them.
  • robots.txt is respected; disallowed paths are skipped.
  • Page cap — at most 200 pages per crawl.
  • Zero pages crawled — the engine exits non-zero and prints the reason (bad URL, blocked, or an empty site). Surface that to the user rather than reporting success.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Docs Crawler AI skill do?

Crawl an entire documentation or design-system website into one LLM-ready Markdown corpus. Discovers every page from the site's sitemap.xml (with a same-origin link-following fallback when there is no sitemap), extracts each page's main content as clean Markdown, downloads each page's images (and inline base64 images) into a local folder referenced by relative paths, and renders JavaScript-heavy pages with a headless browser. Use this whenever someone wants the WHOLE of a multi-page docs site, design-system site, API reference, component library, or knowledge base turned into Markdown — for...

Why use Docs Crawler on TypingMind?

Because you install it once and use it with any model. Docs Crawler 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 Docs Crawler in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CaesiumY/ko-design-md/tree/main/.claude/skills/docs-crawler. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Docs Crawler?

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 Docs Crawler?

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

Is the Docs Crawler AI skill free?

Yes. It is published on GitHub by CaesiumY 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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