--- name: yuque-personal-knowledge-connect description: Discover connections between documents, build knowledge networks, and establish bidirectional links across your personal Yuque knowledge base. For personal/individual use — operates on your own docs. license: Apache-2.0 compatibility: Requires yuque-mcp server connected to a Yuque account with personal Token metadata: author: chen201724 version: "1.0" --- # 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: "" doc_id: "" ``` 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: "" 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: "" ``` ### Step 3: Read and Analyze Connections For each potentially related document (top 5-10): ``` Tool: yuque_get_doc Parameters: repo_id: "" doc_id: "" ``` 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: ```markdown # 🗺️ 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](链接)** - 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 | 文档 | 知识库 | 关联类型 | 关联说明 | |------|--------|----------|----------| | [标题](链接) | [库名] | 🔗 直接相关 | [为什么相关] | | [标题](链接) | [库名] | 🧩 互补 | [互补点说明] | ### 延伸阅读 | 文档 | 知识库 | 关联类型 | 关联说明 | |------|--------|----------|----------| | [标题](链接) | [库名] | 📚 前置知识 | [说明] | | [标题](链接) | [库名] | 🔀 交叉引用 | [共同概念] | --- ## 🧠 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: "" doc_id: "" body: "\n\n---\n\n## 🔗 相关文档\n\n- [相关文档 1](链接) — [关联说明]\n- [相关文档 2](链接) — [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: "" title: "🗺️ 知识图谱:[主题]" body: "" format: "markdown" ``` ### Step 7: Confirm ```markdown ✅ 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 |