Reading Digest logo

Reading Digest

Organization
yuque
reading-digest

Extract core insights, golden quotes, and action items from articles, then create structured Yuque reading notes. Use when the user wants key takeaways or a personal reading-notes base; trigger phrases include “帮我做阅读笔记”, “读书笔记”, and “extract key points from this article”.

Overview

Publisheryuque
Repositoryyuque-ecosystem
Skill namereading-digest
Stars
238
Forks
20
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 yuque on GitHub. Read the source before you install it.

Installation

Install the Reading Digest 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/yuque/yuque-ecosystem/tree/main/skills/reading-digest
  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/yuque/yuque-ecosystem.git /tmp/yuque-ecosystem
mkdir -p .claude/skills
cp -r /tmp/yuque-ecosystem/skills/reading-digest .claude/skills/reading-digest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Reading Digest 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 Reading Digest 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 Reading Digest 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.

Reading Digest — Structured Reading Notes Generator

Read an article or document, extract core insights, golden quotes, and action items, then generate structured reading notes and optionally save them to a Yuque knowledge base.

When to Use

  • User has finished reading an article and wants to capture key takeaways
  • User says "帮我做阅读笔记", "extract key points from this article", "读书笔记"
  • User shares a Yuque document link and wants structured notes
  • User wants to build a personal reading notes knowledge base

Required MCP Tools

All tools are from the yuque-mcp server:

  • yuque_get_doc — Read full document content
  • yuque_list_books — List user's knowledge bases (to find the target repo for saving)
  • yuque_create_doc — Create a new document (to save reading notes)
  • yuque_search — Search for existing reading notes to avoid duplicates

Workflow

Step 1: Get the Source Article

Case A — Yuque document link: Extract repo_id and doc_id from the URL and fetch the content:

Tool: yuque_get_doc
Parameters:
  repo_id: "<namespace>"
  doc_id: "<slug>"

Case B — User pastes article text directly: Use the provided text as the source content. No tool call needed.

Case C — User provides an external URL: Inform the user: "我目前只能处理语雀文档链接或直接粘贴的文本。如果是外部文章,请把内容粘贴给我。"

If the document is not found (404) or permission denied (403), inform the user and stop.

Step 2: Analyze and Extract

Read through the full content and extract the following elements:

  1. Core Insights (核心观点) — The main arguments or ideas the author presents (3-7 items)
  2. Golden Quotes (金句) — Memorable, well-crafted sentences worth saving (2-5 items)
  3. Action Items (行动项) — Concrete things the reader can do based on this article (0-5 items)
  4. Key Concepts (关键概念) — Important terms or frameworks introduced (0-5 items)
  5. Personal Relevance (个人关联) — How this might connect to the reader's existing knowledge

Step 3: Generate Structured Reading Notes

Format the reading notes as follows:

markdown
# 📖 阅读笔记:[原文标题]

> **来源**:[文档标题](文档链接)
> **作者**:[原文作者]
> **阅读日期**:YYYY-MM-DD
> **阅读耗时**:约 X 分钟(按 300 字/分钟估算)

## 一句话总结

[用一句话概括这篇文章的核心价值]

## 核心观点

1. **[观点标题]**:[展开说明,2-3 句话]
2. **[观点标题]**:[展开说明,2-3 句话]
3. **[观点标题]**:[展开说明,2-3 句话]

## 金句摘录

> [原文金句 1]

> [原文金句 2]

> [原文金句 3]

## 关键概念

| 概念 | 解释 |
|------|------|
| [概念 1] | [简要解释] |
| [概念 2] | [简要解释] |

## 行动项

- [ ] [具体可执行的行动 1]
- [ ] [具体可执行的行动 2]
- [ ] [具体可执行的行动 3]

## 我的思考

[基于文章内容,提出 1-2 个延伸思考问题,帮助读者深入反思]

---
*由 AI 辅助生成的阅读笔记*

If the article has no clear action items, omit that section. If there are no notable golden quotes, omit that section too. Adapt the template to fit the content.

Step 4: Save to Knowledge Base (Optional)

Ask the user: "要把这份阅读笔记保存到语雀知识库吗?如果要,请告诉我保存到哪个知识库。"

If the user specifies a knowledge base:

First, check if a reading notes document for this article already exists:

Tool: yuque_search
Parameters:
  query: "[原文标题] 阅读笔记"
  type: "doc"

If a duplicate is found, ask the user: "已经存在一份关于这篇文章的阅读笔记,要覆盖还是创建新的?"

Then create the document:

Tool: yuque_create_doc
Parameters:
  repo_id: "<target namespace>"
  title: "📖 阅读笔记:[原文标题]"
  body: "<generated reading notes in markdown>"

After saving, confirm: "阅读笔记已保存到「[知识库名称]」:[新文档链接]"

If the user doesn't want to save, just present the reading notes in the chat.

Guidelines

  • Always answer in the same language the user used (Chinese or English)
  • Golden quotes must be exact quotes from the original text — never paraphrase them
  • Action items should be specific and actionable, not vague ("学习 React hooks" not "多学习")
  • Core insights should capture the author's intent, not your interpretation
  • Estimate reading time based on ~300 Chinese characters/minute or ~200 English words/minute
  • If the article is very short (< 200 words), simplify the output — skip sections that don't apply
  • The "我的思考" section should pose genuine questions, not rhetorical ones

Error Handling

SituationAction
Document not found (404)Inform user the document may have been deleted or the link is incorrect
Permission denied (403)Tell user they may lack permission to access this document
Document content is emptyInform user: "该文档内容为空,无法生成阅读笔记"
Target repo not found when savingList user's repos with yuque_list_books and ask them to pick one
yuque_create_doc failsInform user the save failed, present the notes in chat instead
Article is not text-based (e.g., pure images)Inform user: "该文档主要是图片内容,无法提取文字进行分析"

Frequently asked questions

What does the Reading Digest AI skill do?

Extract core insights, golden quotes, and action items from articles, then create structured Yuque reading notes. Use when the user wants key takeaways or a personal reading-notes base; trigger phrases include “帮我做阅读笔记”, “读书笔记”, and “extract key points from this article”.

Why use Reading Digest on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yuque/yuque-ecosystem/tree/main/skills/reading-digest. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Reading Digest?

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 Reading Digest?

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

Is the Reading Digest AI skill free?

Yes. It is published on GitHub by yuque 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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