Byte-n

Byte-n / larkDocx2md

Public

飞书（lark）文档导出未 Markdown 格式，支持文档内的画板数据导出。AI 友好，支持 Agent Skill

16
4
100% credibility
Found Apr 24, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

A tool that downloads Feishu wiki documents and converts them into standard Markdown files while preserving layouts, images, tables, and whiteboards.

How It Works

1
🔍 Find the converter

You search for a simple way to turn your Feishu pages into easy-to-read Markdown files.

2
🔗 Link your Feishu account

You connect your Feishu workspace once with a secure login so it can access your documents.

3
⚙️ Choose your preferences

You pick where to save files and how to handle pictures or drawings, like downloading them locally or keeping links online.

4
📎 Paste your document link

You copy and paste the web address of any Feishu wiki page you want to convert.

5
🔄 Start the conversion

You click to download, and it grabs the page content, turning headings, lists, tables, and even drawings into Markdown.

✅ Enjoy your Markdown file

Your new Markdown file is ready in the folder, perfect for editing, sharing, or using anywhere.

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AI-Generated Review

What is larkDocx2md?

This TypeScript CLI tool exports Feishu (Lark) wiki documents to standard Markdown, handling 20+ block types like headings, lists, tables, code, and todos. Run `npx lark-docx2md download ` with app credentials to grab a doc and spit out MD files, complete with local images or online links. It shines on whiteboards, rendering them as SVG, base64, or AI-friendly YAML structures.

Why is it gaining traction?

Unlike basic Lark oapi scrapers, it parses lark doc markdown fully, preserving callouts, equations, and nested lists as lark flavored markdown that renders cleanly in GitHub or Obsidian. Agent mode streams output to stdout with error-only logs, perfect for lark github integration or AI skills like github lark bot workflows. Whiteboard YAML export stands out for agent processing without visual bloat.

Who should use this?

DevOps teams archiving Lark docs for GitHub repos via lark github webhook or lark import markdown pipelines. AI builders chaining it as an agent skill for lark document to markdown in RAG systems. Chinese devs ditching Feishu for Markdown-native tools like Notion or Slack bot markdown imports.

Verdict

Grab it for Lark-to-MD needs—solid CLI, clear docs, and agent-ready despite 16 stars and 1.0% credibility score signaling early maturity. Test on complex whiteboards first; lacks broad adoption but nails the niche.

(178 words)

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