Knowledge Connect logo

Knowledge Connect

Organization
yuque
knowledge-connect

Analyze Yuque documents to uncover related topics, complementary notes, and cross-reference opportunities. Use when the user wants connections or a knowledge graph; trigger phrases include “帮我找找文档之间的关联”, “哪些笔记是相关的”, “这篇文档和哪些笔记有关”, “connect my notes”, and “find related documents”.

Overview

Publisheryuque
Repositoryyuque-ecosystem
Skill nameknowledge-connect
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 Knowledge Connect 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/knowledge-connect
  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/knowledge-connect .claude/skills/knowledge-connect
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Knowledge Connect 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 Knowledge Connect 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 Knowledge Connect 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.

Knowledge Connect — Discover Links Between Your Notes

Analyze documents in your Yuque knowledge base, find hidden connections between them — similar topics, complementary content, shared concepts — and suggest cross-reference links to help you build a connected knowledge network.

When to Use

  • User wants to find connections between their notes
  • User says "帮我找找文档之间的关联", "哪些笔记是相关的", "connect my notes"
  • User just finished writing a document and wants to link it to related ones
  • User says "这篇文档和哪些笔记有关", "find related documents"
  • User wants to build a knowledge graph from their existing notes

Required MCP Tools

All tools are from the yuque-mcp server:

  • yuque_list_books — List user's knowledge bases
  • yuque_list_docs — List all documents in a knowledge base
  • yuque_get_doc — Read document content for analysis
  • yuque_search — Search for potentially related documents
  • yuque_update_doc — Add cross-reference links to documents

Workflow

Step 1: Determine the Scope

Ask the user what to analyze:

Case A — Single document: User provides a specific document link. Find connections for this one document.

Case B — Entire knowledge base: User specifies a knowledge base. Analyze all documents within it.

Case C — Across knowledge bases: User wants cross-repo connections. Analyze documents across multiple repos.

For Case B/C, first list available repos:

Tool: yuque_list_books

Then list documents in the target repo(s):

Tool: yuque_list_docs
Parameters:
  repo_id: "<namespace>"

Step 2: Analyze Documents

For each document in scope, fetch its content:

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

Extract the following from each document:

ElementDescription
TopicsMain subjects the document covers
Key ConceptsImportant terms, frameworks, or ideas
QuestionsQuestions raised but not fully answered
ReferencesExternal sources or concepts mentioned
DomainThe knowledge area (tech, management, personal, etc.)

Step 3: Discover Connections

Compare documents pairwise and identify these types of connections:

Connection TypeDescriptionExample
🔄 Same TopicDocuments covering the same subject from different anglesTwo articles about "distributed systems"
🧩 ComplementaryOne document answers questions raised in anotherA "why microservices" doc + a "microservices pitfalls" doc
📚 SequentialDocuments that form a natural reading sequence"Intro to X" → "Advanced X" → "X in Practice"
🌱 EvolutionEarlier and later thinking on the same topicA draft idea → a refined version months later
🔗 Shared ConceptDocuments that reference the same key conceptMultiple docs mentioning "second brain" methodology

For single-document analysis, also search for related documents:

Tool: yuque_search
Parameters:
  query: "[key topics from the document]"
  type: "doc"

Step 4: Present Connection Map

Present the discovered connections to the user:

markdown
## 🕸️ 知识关联分析

分析范围:[知识库名称] — [N] 篇文档
发现 [X] 组关联

### 关联 1:[主题/概念名称]

| 文档 | 关联类型 | 关联强度 |
|------|----------|----------|
| [文档 A 标题](链接) | 🔄 同主题 | ⭐⭐⭐ |
| [文档 B 标题](链接) | 🧩 互补 | ⭐⭐⭐ |
| [文档 C 标题](链接) | 🔗 共享概念 | ⭐⭐ |

**关联说明**:[为什么这些文档相关,它们之间的具体联系是什么]

**建议**:[具体的交叉引用建议,如 "在文档 A 的第二节末尾添加指向文档 B 的链接"]

### 关联 2:[主题/概念名称]

...

### 🏝️ 孤岛文档

以下文档暂未发现明显关联:
- [文档标题](链接) — 可能需要补充更多内容后再分析

### 💡 建议

1. [建议 1:如 "建议创建一篇索引文档,串联关于 X 主题的 5 篇笔记"]
2. [建议 2:如 "文档 A 和文档 B 观点互补,可以合并成一篇完整的指南"]

Step 5: Add Cross-References (Optional)

Ask the user: "要自动在相关文档中添加交叉引用链接吗?"

If confirmed, for each document that needs cross-references:

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

Append a "Related Notes" section at the end:

markdown

---

## 📎 相关笔记

- 🔄 [相关文档标题](链接) — [一句话说明关联]
- 🧩 [相关文档标题](链接) — [一句话说明关联]

*由 AI 分析生成的关联推荐 — YYYY-MM-DD*
Tool: yuque_update_doc
Parameters:
  repo_id: "<namespace>"
  doc_id: "<slug>"
  body: "<original content + related notes section>"

Confirm: "已为 [N] 篇文档添加了交叉引用链接 ✅"

Guidelines

  • Always answer in the same language the user used (Chinese or English)
  • Connection strength should be based on actual content overlap, not just title similarity
  • Be specific about why documents are connected — vague "they're related" is not helpful
  • Don't force connections — if two documents aren't meaningfully related, don't link them
  • For large knowledge bases (> 50 docs), suggest analyzing in batches by topic area
  • The "孤岛文档" section is valuable — it helps users identify notes that need more context
  • When adding cross-references, never modify the original content — only append at the end
  • Suggest creating index/hub documents for topics with 3+ related notes

Error Handling

SituationAction
Document not found (404)Skip the document and note it in the report
Permission denied (403)Tell user they may lack permission to access this document
Knowledge base is emptyInform user: "该知识库还没有文档,先写几篇笔记再来分析关联吧"
Knowledge base has < 3 documentsInform user: "文档数量较少,建议积累更多笔记后再做关联分析,效果会更好"
yuque_update_doc failsPresent the suggested cross-references in chat for manual adding
Too many documents to analyze at onceSuggest narrowing scope: "知识库文档较多,建议先选一个主题方向分析"

Frequently asked questions

What does the Knowledge Connect AI skill do?

Analyze Yuque documents to uncover related topics, complementary notes, and cross-reference opportunities. Use when the user wants connections or a knowledge graph; trigger phrases include “帮我找找文档之间的关联”, “哪些笔记是相关的”, “这篇文档和哪些笔记有关”, “connect my notes”, and “find related documents”.

Why use Knowledge Connect on TypingMind?

Because you install it once and use it with any model. Knowledge Connect 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 Knowledge Connect in TypingMind?

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

Which AI models can use Knowledge Connect?

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 Knowledge Connect?

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

Is the Knowledge Connect 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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