Knowledge Connect — Discover Document Relationships & Build Knowledge Networks

Help the user discover hidden connections between their documents, find related content, and build a knowledge network with bidirectional links across their personal Yuque knowledge base.

When to Use

• User wants to find documents related to a specific topic

• User says "有哪些相关文档", "find related docs", "帮我建立知识关联"

• User wants to build a knowledge map or graph for a topic

• User says "这个主题还有哪些相关的", "帮我串联一下知识", "构建知识图谱"

Required MCP Tools

All tools are from the yuque-mcp server:

• yuque_search — Search for related documents by keyword

• yuque_get_doc — Read document content to analyze connections

• yuque_list_repos — List personal repos to scan

• yuque_list_docs — List documents in repos for broader discovery

• yuque_update_doc — Add cross-reference links to documents

• yuque_create_doc — Create knowledge map documents

Workflow

Step 1: Identify the Starting Point

The user may provide:

• A specific document to find connections for

• A topic or keyword to explore

• A request to map an entire knowledge area

If starting from a document:

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

Extract key concepts, terms, and themes from the document.

Step 2: Discover Related Documents

Search for related content using extracted keywords:

Tool: yuque_search Parameters: query: "<keyword 1>" type: "doc"

Repeat with different keywords to cast a wider net. Use:

• Direct topic keywords

• Synonyms and related terms

• Key people or project names mentioned

• Technical terms and concepts

Also scan repos for broader discovery:

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

Step 3: Read and Analyze Connections

For each potentially related document (top 5-10):

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

Analyze the relationship type:

Relationship Description Example

🔗 直接相关 Same topic, different angle 两篇都讲微服务架构

🧩 互补 Fills gaps in each other 一篇讲设计，一篇讲实现

📚 前置/后续 Sequential knowledge 入门篇 → 进阶篇

🔀 交叉引用 Shared concepts across topics 都提到了 Redis 缓存策略

⚡ 矛盾/对比 Conflicting viewpoints 两篇对同一问题有不同方案

Step 4: Build the Knowledge Map

Present the discovered connections:

🗺️ 知识关联图：[主题/文档标题]

基于「[起始文档]」发现的知识网络 扫描范围：X 个知识库，XX 篇文档 生成时间：YYYY-MM-DD

🎯 中心节点

起始文档标题

• 知识库：[库名]
• 核心概念：[概念1]、[概念2]、[概念3]

🔗 关联文档

直接相关

延伸阅读

🧠 知识网络

[中心文档] ├── 🔗 [直接相关文档 1] │ └── 🔀 [交叉引用文档 A] ├── 🧩 [互补文档 2] ├── 📚 [前置文档 3] │ └── 📚 [更前置文档 B] └── ⚡ [对比文档 4]

💡 发现与建议

• 知识聚类：[发现的知识聚类模式]
• 知识缺口：[发现缺少的关联文档或主题]
• 建议行动：
  1. [建议创建的文档或补充的内容]
  2. [建议建立的新关联]

本知识图谱由 AI 助手自动生成，关联关系基于内容分析。

Step 5: (Optional) Add Cross-References

If the user agrees, add "相关文档" sections to the connected documents:

Tool: yuque_update_doc Parameters: repo_id: "<namespace>" doc_id: "<slug>" body: "<original content>\n\n---\n\n## 🔗 相关文档\n\n- 相关文档 1 — [关联说明]\n- 相关文档 2 — [关联说明]\n"

Ask before modifying any existing document:

• "要在这些文档中添加相互引用链接吗？"

Step 6: (Optional) Save Knowledge Map

Tool: yuque_create_doc Parameters: repo_id: "<namespace>" title: "🗺️ 知识图谱：[主题]" body: "<knowledge map content>" format: "markdown"

Step 7: Confirm

✅ 知识关联分析完成！

🗺️ 发现 X 篇相关文档，建立了 X 个关联

关联概览

• 🔗 直接相关：X 篇
• 🧩 互补文档：X 篇
• 📚 前置/后续：X 篇
• 🔀 交叉引用：X 篇

💡 建议：[最重要的一条建议]

Guidelines

• Start broad, then narrow — search with multiple keywords to find unexpected connections

• Quality over quantity — 5 strong connections are better than 20 weak ones

• Explain why documents are related, not just that they are

• Always ask before modifying existing documents (adding cross-references)

• The knowledge map should be actionable — include specific suggestions for strengthening the knowledge network

• Identify knowledge gaps — what's missing is as valuable as what's connected

• For large knowledge bases, focus on one topic area at a time

• Default language is Chinese

Error Handling

Situation Action

yuque_search returns few results Broaden keywords; try synonyms and related terms

Starting document has no clear connections Suggest the document may be on a new topic; offer to search broader

Too many connections found (>15) Prioritize by relevance strength; group into clusters

yuque_update_doc fails when adding links Skip that document; note it in the report

User's knowledge base is very small Acknowledge limited scope; suggest topics to write about to build the network