📰
AutomationTypeScript

WeChat Article Extractor

by zhuzhaoyun

WeChat Article Extractor is an Automation skill for Claude Code, published by zhuzhaoyun in Molio.

241 stars35 forkson zhuzhaoyun/MolioAdded 2026/09/02+1% in starsRepository updated 2026/09/02
claude-codeknowledge-managementllmwikilocal-firstobsidianweb-clipperwechat-bot
Install in seconds
Install WeChat Article Extractor
Copy WeChat Article Extractor into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/zhuzhaoyun/Molio/tree/main/apps/daemon/src/tools/skills/wechat-article-extractor ~/.claude/skills/wechat-article-extractor

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/zhuzhaoyun/Molio.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
apps/daemon/src/tools/skills/wechat-article-extractor/SKILL.md in zhuzhaoyun/Molio
Installs to
~/.claude/skills/wechat-article-extractor
Collection
One of 8 skills cataloged from this repository
Category
Automation1648 skills

What WeChat Article Extractor does

WeChat Article Extractor converts mp.weixin.qq.com articles into structured Markdown, preserving tables, code blocks, and image placeholders. Use it when a WeChat article link needs extraction without WebFetch.

WeChat Article Extractor is cataloged under Automation on DirSkills. WeChat Article Extractor comes from a repository tagged claude-code, knowledge-management, llmwiki, local-first and obsidian.

Documentation

README

WeChat Article Extractor

提取微信公众号文章内容为结构化 Markdown,保留表格、代码块、图片占位。

⚠️ 重要:禁止使用 WebFetch

WebFetch 对 mp.weixin.qq.com 会被企业安全策略拦截。必须使用本 skill 的 extract.js 脚本提取文章内容。

使用方法

从 URL 提取

node "<skill_dir>/extract.js" "https://mp.weixin.qq.com/s?__biz=...&mid=...&idx=...&sn=..."

其中 <skill_dir> 是本 skill 所在目录的绝对路径(即包含此 SKILL.md 的目录)。

从本地 HTML 文件提取

node "<skill_dir>/extract.js" --html /path/to/article.html [source_url]

输出格式

成功(退出码 0)

  • stdout: Markdown 格式的文章正文(保留表格、代码块、图片占位)
  • stderr: 一行 JSON 元数据:
{"title":"文章标题","author":"作者","account":"公众号名称","publishTime":"2024/01/15 10:30:00","url":"原始链接","type":"post","chars":12345}

失败(退出码非 0)

This is the opening of the README. Read the full README on GitHub.

Frequently asked about WeChat Article Extractor

  • What else does zhuzhaoyun publish alongside WeChat Article Extractor?

    WeChat Article Extractor is one of 8 skills that DirSkills catalogs from zhuzhaoyun/Molio, the repository it ships in. Its siblings there include Docling, Remotion and Wiki Build. Each one is a separate skill with its own page in this directory, installs the same way WeChat Article Extractor does, and is maintained by zhuzhaoyun in that same repository. The rest of the collection is listed on the zhuzhaoyun/Molio page.

  • How does WeChat Article Extractor compare to other Automation skills?

    WeChat Article Extractor ranks #1504 by stars among the 1648 Automation skills in this catalog. The most-starred ones next to it are Autonomous Loops, Autonomous Agent Harness and Automation Audit Ops. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of WeChat Article Extractor against them. Open each page to compare what they document and how they install.

More from zhuzhaoyun/Molio

WeChat Article Extractor is one of 8 skills cataloged on DirSkills from zhuzhaoyun/Molio.

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Wiki Build

Wiki Build 构建或重建本地知识库,把源文件整理成分层 Wiki 索引、摘要页、实体页和概念页,并维护交叉链接与日志。它适合初始建库、索引迁移和超长源文件的分段构建。
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Wiki Lint

Wiki Lint checks a local wiki for broken links, orphan pages, missing frontmatter, empty sections, contradictions, stale content, and index drift. Use it to audit knowledge-base health and generate a lint report with follow-up suggestions.
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Wiki Query answers questions and supports writing or analysis using a knowledge base’s wiki and source files. It reads the wiki first, then source files if needed, and cites [[wikilink]] sources instead of relying on memory.
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