clean-web-markdown

name	clean-web-markdown
description	Retrieve clean markdown from webpages for AI agents using protocol-level content negotiation and crawl-to-markdown fallbacks. Use when users ask to fetch/read/summarize websites with low-noise markdown, to improve web_fetch quality, or to process JS-heavy pages via Jina/Firecrawl. Chinese trigger cues include: "抓网页正文", "提取网页 Markdown", "网页转 Markdown", "读取网页并总结", "这个链接帮我清洗一下".

clean-web-markdown

Use this skill to get low-noise markdown from web pages with a deterministic fallback chain.

Usage cues (EN + 中文)

Trigger this skill when requests match patterns like:

• "fetch this page as clean markdown"
• "summarize this URL, skip noisy HTML"
• "抓网页正文"
• "提取网页 Markdown"
• "网页转 Markdown"
• "读取网页并总结"
• "这个链接帮我清洗一下"

Workflow

1. Normalize input URL.
2. Try Cloudflare-style markdown negotiation first:
   • send Accept: text/markdown
   • keep normal browser-like user-agent
3. If response is not usable markdown, fallback to Jina Reader:
   • request https://r.jina.ai/<url>
4. If user provides Firecrawl API key and page is still problematic, try Firecrawl scrape API.
5. Return markdown + source strategy used.

Use in agent web access flow

When agent needs website content:

• Prefer this skill before raw HTML extraction.
• Keep web_fetch as fallback when markdown service fails.
• For JS-heavy pages or paywall-like structure:
  • try Jina first
  • then Firecrawl (if key available)

Commands

Direct script

python3 scripts/fetch_markdown.py "https://example.com/article"

Force strategy

python3 scripts/fetch_markdown.py "https://example.com/article" --strategy cloudflare
python3 scripts/fetch_markdown.py "https://example.com/article" --strategy jina
python3 scripts/fetch_markdown.py "https://example.com/article" --strategy firecrawl --firecrawl-api-key "$FIRECRAWL_API_KEY"

Output contract

Script returns JSON:

• ok: boolean
• strategy: selected provider
• url: original url
• markdown: cleaned markdown text
• error: present when failed

References

• Strategy details and decision matrix: references/strategy-matrix.md