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Video Information Reading

CommunityPopular
freestylefly
video-information-reading

从微信聊天记录导出文件中找出视频链接或本地视频附件,整理可获得的逐字稿、内容摘要、关键结论和时间点,并保留来源。当用户要求解读、总结或归档聊天记录里的视频内容时使用。

Overview

Publisherfreestylefly
RepositoryWeChatBridge
Skill namevideo-information-reading
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 Video Information Reading 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/video-information-reading
  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/video-information-reading .claude/skills/video-information-reading
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Video Information Reading 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 Video Information Reading 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 Video Information Reading 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.

视频信息读取

从微信聊天记录导出文件(ZIP 或已解压内容)中找出所有视频内容,整理成可检索的结构化笔记。

输入

  • 视频可能以三种形态出现:
    1. 聊天记录里的视频平台链接(视频号、B 站、抖音、YouTube 等);
    2. 视频号/小程序分享卡片(标题 + 来源 + 封面图);
    3. 随记录导出的本地视频文件(mp4 等)或视频截图。

步骤

  1. 扫描全部附件文本,找出视频链接、分享卡片和视频文件,按聊天中出现顺序编号。
  2. 对每条视频提取:
    • 来源:平台名称(视频号 / bilibili / 抖音 / 本地文件等);
    • 标题:卡片标题或文件名;
    • 链接或文件名:完整 URL 或附件内文件名;
    • 可获得的信息:附件文本中已有的简介、字幕、转写、截图文字——全部保留;
    • 关键时间点:如果附件中含字幕或转写,标出重要话题开始的时间点;没有就写「无时间信息」。
  3. 对每条视频写一段摘要:基于附件里实际存在的文字信息归纳;只有链接没有内容时,标注「仅有链接,无法读取内容」,不要根据标题猜测正文。

输出

每条视频一节,用 Markdown 输出:

markdown
## 1. {标题}
- 来源:{平台}
- 链接/文件:{URL 或文件名}
- 时长:{已知时长或「未知」}

### 摘要
{基于附件信息的摘要,或「仅有链接,无法读取内容」}

### 关键时间点
- {mm:ss} {话题}(无则写「无时间信息」)

结尾附汇总表:编号、标题、来源、是否有可读内容。

注意

  • 只处理视频;图片和普通文件不算,但在汇总表末尾列一行「跳过的其他附件」。
  • 无法播放视频文件本身时,如实说明,只整理附件中已有的文字信息。
  • 保留附件中原始字幕/转写的时间戳格式,不做换算。

Frequently asked questions

What does the Video Information Reading AI skill do?

从微信聊天记录导出文件中找出视频链接或本地视频附件,整理可获得的逐字稿、内容摘要、关键结论和时间点,并保留来源。当用户要求解读、总结或归档聊天记录里的视频内容时使用。

Why use Video Information Reading on TypingMind?

Because you install it once and use it with any model. Video Information Reading 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 Video Information Reading in TypingMind?

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

Which AI models can use Video Information Reading?

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 Video Information Reading?

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

Is the Video Information Reading 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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