Analyze documents in your Yuque knowledge base, discover hidden connections between them (similar topics, complementary content), and suggest cross-reference links to build a knowledge network. For personal/individual use.
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.
All tools are from the yuque-mcp server:
yuque_list_books — List user's knowledge basesyuque_list_docs — List all documents in a knowledge baseyuque_get_doc — Read document content for analysisyuque_search — Search for potentially related documentsyuque_update_doc — Add cross-reference links to documentsAsk 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>"
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:
| Element | Description |
|---|---|
| Topics | Main subjects the document covers |
| Key Concepts | Important terms, frameworks, or ideas |
| Questions | Questions raised but not fully answered |
| References | External sources or concepts mentioned |
| Domain | The knowledge area (tech, management, personal, etc.) |
Compare documents pairwise and identify these types of connections:
| Connection Type | Description | Example |
|---|---|---|
| 🔄 Same Topic | Documents covering the same subject from different angles | Two articles about "distributed systems" |
| 🧩 Complementary | One document answers questions raised in another | A "why microservices" doc + a "microservices pitfalls" doc |
| 📚 Sequential | Documents that form a natural reading sequence | "Intro to X" → "Advanced X" → "X in Practice" |
| 🌱 Evolution | Earlier and later thinking on the same topic | A draft idea → a refined version months later |
| 🔗 Shared Concept | Documents that reference the same key concept | Multiple 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"
Present the discovered connections to the user:
## 🕸️ 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"]
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:
---
## 📎 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 ✅"
| Situation | Action |
|---|---|
| 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 empty | Inform 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 documents | Inform 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 fails | Present the suggested cross-references in chat for manual adding |
| Too many documents to analyze at once | Suggest narrowing scope: "知识库文档较多，建议先选一个主题方向分析" |