Smart Search logo

Smart Search

Organization
yuque
smart-search

Search personal Yuque knowledge bases with natural-language queries and synthesize answers with source links. Use when the user wants to find information in their own documents; trigger phrases include “搜一下我的文档”, “我的知识库里有没有...”, “搜索我的语雀/知识库”, and “search my Yuque”.

Overview

Publisheryuque
Repositoryyuque-ecosystem
Skill namesmart-search
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 Smart Search 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/smart-search
  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/smart-search .claude/skills/smart-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Smart Search 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 Smart Search 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 Smart Search 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.

Smart Search — Yuque Personal Knowledge Base Search & Q&A

Search across your personal Yuque knowledge bases using natural language, read relevant documents, and synthesize a clear answer with references.

When to Use

  • User asks a question that might be answered by their personal Yuque docs
  • User wants to find specific information in their own knowledge base
  • User says "搜一下我的文档", "search my Yuque", "我的知识库里有没有..."

Required MCP Tools

All tools are from the yuque-mcp server:

  • yuque_search — Search documents by keyword
  • yuque_get_doc — Read full document content by slug/id

Workflow

Step 1: Extract Search Keywords

From the user's natural language query, extract 1-3 concise Chinese keywords. Yuque search works best with short, specific terms.

Examples:

  • "我的部署流程文档在哪?" → keywords: 部署流程
  • "How do I handle error logging?" → keywords: 错误日志 or 日志处理
  • "我之前写的技术评审笔记" → keywords: 技术评审

Step 2: Search Documents

Call yuque_search with the extracted keywords:

Tool: yuque_search
Parameters:
  query: "<keywords>"
  type: "doc"

If the search returns no results:

  1. Try alternative keywords (synonyms, broader terms)
  2. Try splitting compound terms (e.g., "部署流程" → "部署" or "流程")
  3. If still no results, tell the user honestly: "在你的语雀知识库中未找到相关文档,建议尝试其他关键词或确认文档是否存在。"

Step 3: Filter and Rank Results

From the search results, select the top 3-5 most relevant documents based on:

  • Title relevance to the query
  • Document update time (prefer recent)
  • Repository context (focus on user's personal repos)

Step 4: Read Document Content

For each selected document, fetch the full content:

Tool: yuque_get_doc
Parameters:
  repo_id: "<namespace>"    # e.g., "username/my-notes" (from search result's book.namespace)
  doc_id: "<slug>"          # e.g., "api" (from search result's target.slug)

Note: The search result contains nested data. Extract these key fields:

  • target.slug → use as doc_id
  • target.book.namespace → use as repo_id
  • target.title → document title
  • target.updated_at → last update time

Read up to 3 documents. If the first document fully answers the question, you may skip the rest.

Step 5: Synthesize and Respond

Compose the answer in the following format:

markdown
## 回答

[直接回答用户的问题,2-4 句话,简洁明了]

## 关键要点

- **要点 1**:[从文档中提取的关键信息]
- **要点 2**:[从文档中提取的关键信息]
- **要点 3**:[从文档中提取的关键信息]

## 参考文档

1. [文档标题](文档链接) — 来自「知识库名称」,更新于 YYYY-MM-DD
2. [文档标题](文档链接) — 来自「知识库名称」,更新于 YYYY-MM-DD

Guidelines

  • Always answer in the same language the user used (Chinese or English)
  • Quote specific content from documents when relevant — use > blockquotes
  • If documents contain conflicting information, note the discrepancy and mention which doc is more recent
  • If the answer is only partially found, say what you found and what's missing
  • Never fabricate information not present in the documents
  • Include document links so the user can read the full source
  • This skill searches the knowledge bases accessible to the configured Yuque token

Error Handling

SituationAction
yuque_search returns emptyTry alternative keywords, then inform user
yuque_get_doc fails (404)Skip this doc, note it may have been deleted
yuque_get_doc fails (403)Tell user they may lack permission to access this doc
API timeoutRetry once, then inform user of connectivity issue
Too many resultsFocus on top 3 by relevance, mention there are more results available

Frequently asked questions

What does the Smart Search AI skill do?

Search personal Yuque knowledge bases with natural-language queries and synthesize answers with source links. Use when the user wants to find information in their own documents; trigger phrases include “搜一下我的文档”, “我的知识库里有没有...”, “搜索我的语雀/知识库”, and “search my Yuque”.

Why use Smart Search on TypingMind?

Because you install it once and use it with any model. Smart Search 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 Smart Search in TypingMind?

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

Which AI models can use Smart Search?

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 Smart Search?

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

Is the Smart Search 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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