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Wechat Article Extract

CommunityPopular
freestylefly
wechat-article-extract

从微信聊天记录导出文件中识别公众号文章链接或分享卡片,提取标题、公众号名称、发布时间、正文和图片,并保留原文链接。当用户要求整理、摘录或归档聊天记录里的公众号文章时使用。

Overview

Publisherfreestylefly
RepositoryWeChatBridge
Skill namewechat-article-extract
Stars
1.4K
Forks
424
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Wechat Article Extract 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/freestylefly/WeChatBridge/tree/main/shared/Skills/wechat-article-extract
  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/freestylefly/WeChatBridge.git /tmp/WeChatBridge
mkdir -p .claude/skills
cp -r /tmp/WeChatBridge/shared/Skills/wechat-article-extract .claude/skills/wechat-article-extract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wechat Article Extract 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 Wechat Article Extract 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 Wechat Article Extract 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.

公众号文章提取

从微信聊天记录导出文件(ZIP 或已解压的文本/图片)中找出所有公众号文章,逐篇提取成结构化结果。

输入

  • 微信「合并转发」导出的聊天记录 ZIP,或其中解压出的文本文件、HTML 和图片附件。
  • 文章可能以三种形态出现:
    1. 聊天记录里的 mp.weixin.qq.com 链接;
    2. 分享卡片(标题 + 公众号名 + 链接,可能带封面图);
    3. 已随记录一起导出的文章正文或截图。

步骤

  1. 扫描全部附件文本,找出公众号文章的链接和分享卡片,按聊天中的出现顺序编号。
  2. 对每篇文章提取:
    • 标题:卡片标题或正文首行标题;
    • 公众号:卡片或正文中的账号名称;
    • 发布时间:卡片或正文中的日期,没有就写「未标注」;
    • 正文:如果记录里包含正文文本则整理成干净的段落;只有链接则标注「仅有链接,未含正文」;
    • 图片:附件中属于该文章的图片文件名列表,按顺序排列;
    • 原文链接:完整的 mp.weixin.qq.com URL。
  3. 如果链接对应的正文不在附件中,不要编造内容——明确标注「仅链接,无法读取正文」。

输出

每篇文章一节,用 Markdown 输出:

markdown
## 1. {标题}
- 公众号:{名称}
- 发布时间:{时间}
- 原文链接:{URL}
- 图片:{文件名列表或「无」}

{整理后的正文,或「仅有链接,未含正文」}

结尾附一个汇总表:编号、标题、公众号、是否有正文。

注意

  • 只处理公众号文章;普通网页链接、小程序卡片不算,但在汇总表末尾列一行「跳过的其他链接」。
  • 保持原文措辞,不做改写或评价。
  • 图片引用使用附件内的原始文件名,不复制或重命名文件。

Frequently asked questions

What does the Wechat Article Extract AI skill do?

从微信聊天记录导出文件中识别公众号文章链接或分享卡片,提取标题、公众号名称、发布时间、正文和图片,并保留原文链接。当用户要求整理、摘录或归档聊天记录里的公众号文章时使用。

Why use Wechat Article Extract on TypingMind?

Because you install it once and use it with any model. Wechat Article Extract 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 Wechat Article Extract in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/freestylefly/WeChatBridge/tree/main/shared/Skills/wechat-article-extract. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wechat Article Extract?

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 Wechat Article Extract?

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

Is the Wechat Article Extract AI skill free?

Yes. It is published on GitHub by freestylefly 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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