Multi Search

Intelligent multi-topic deep research tool supporting arbitrary material input, using independent research agents for parallel deep retrieval and systematic research document generation. Use this skill when users need to deeply research multiple related topics, conduct systematic information retrieval, or integrate multi-perspective analysis.

Multi-Topic Deep Research Skill

Overview

Intelligent multi-topic deep research tool that automatically analyzes materials and generates systematic research documents. Supports arbitrary material input, launching multiple independent research agents in parallel for deep retrieval, forming a concise research knowledge base.

Core Principles:

• Only perform information retrieval, summarization, and professional expression transformation
• No adding facts, no fabricating information
• Focus on single problems, concise output, just enough to solve the problem
• Universal design, applicable to legal, business, technical, academic, and other fields

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Trigger Conditions

Trigger with /multi-search command, or when users request:

• Deep research on multiple related topics
• Systematic information retrieval
• Multi-perspective analysis integration
• Structured research report generation

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Input Format

Method 1: File-based

text

/multi-search @document-path.md

Method 2: Direct Paste

text

/multi-search
[Paste material content]

Method 3: Specify Topics

text

/multi-search
Project: [Project Name]
Research Topics:
1. [Topic One]
2. [Topic Two]
3. [Topic Three]

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Processing Flow

Phase 1: Analysis Preparation

1. Read input materials
2. Extract research topic list
   • With clear topics: Use directly
   • Without clear topics: Auto-extract from materials
3. Topic splitting principles:
   • Clear direction: Each topic corresponds to a unique retrieval direction
   • Avoid overlap: Ensure no duplicate retrieval keywords between topics
   • Focus on problems: Each topic solves one specific problem
4. Determine project name and output location

Phase 2: Output Directory Detection

Detect project structure by priority:

1. Priority detection: output/ directory -> Use output/[project-name]/
2. Secondary detection: Current working directory -> Use ./[project-name]/
3. Fallback: User's current directory -> Use ./research/

Create directory: [output-dir]/03 - Deep Research/

Phase 3: Parallel Deep Research

Launch an independent general-purpose research agent for each research topic.

Context Transfer (Main Agent -> Research Agent):

• Project key information (background, objectives, core problems)
• Complete topic list and retrieval scope for each topic
• Assigned keyword directions (basis for avoiding duplicates)
• Specific requirement background

Deduplication Mechanism:

Each research agent must follow this process before starting retrieval:

1. Pre-retrieval Declaration:

   • Declare in current context: "I will search [Keyword A, Keyword B] for researching [Topic Name]"
   • Wait for main agent confirmation of no duplicates before starting

2. Main Agent Review:

   • Check if the agent's declared keywords duplicate assigned directions
   • If duplicates found, notify the agent to pivot to other directions

3. Dynamic Adjustment:

   • If a direction is already covered by other agents, pivot to related but different angles
   • Record adjusted retrieval directions

Deep Retrieval Requirements:

• 4-6 rounds of deep retrieval
• Auto-select WebSearch (discovery) or WebFetch (get full content)
• Differentiated keywords, ensuring each agent covers unique angles

Document Generation:

• Focus on solving a single core problem
• Concise and clear, just enough to solve the problem
• Include key source links
• Directly usable conclusions and recommendations

Phase 4: Integration Output

1. Generate research overview document (000.Research-Overview.md)
2. Integrate core findings from all research agents
3. Create inter-document navigation links
4. Add comprehensive recommendations and immediate action list

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Output Format

Directory Structure

text

[output-dir]/
└── [project-name]/
    └── 03 - Deep Research/
        ├── 000.Research-Overview.md
        ├── YYMMDD [Research Topic One].md
        ├── YYMMDD [Research Topic Two].md
        └── ...

Overview Document Format

markdown

# [Project Name] Deep Research Overview

**Generated**: YYYY-MM-DD
**Research Method**: N independent research agents, each conducting 4-6 rounds of deep retrieval
**Total Retrieval Rounds**: XX+ rounds
**Total Document Size**: XX KB

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## Research Deliverables

### N Concise Research Reports Completed

| No. | Research Topic | File Size | Core Value |
|-----|----------------|-----------|------------|
| 01 | [Topic One](./YYMMDD%20Topic-One.md) | XX KB | Brief description |

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## Core Findings

### Finding 1: [Most Important Finding]

**Basis**: [Brief explanation]

**Conclusion**: [Specific conclusion]

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## Comprehensive Recommendations

### I. Strategic Recommendations

**Recommended Approach**: [Specific approach]

### II. Immediate Action List

- [ ] Action item 1
- [ ] Action item 2

Detailed Research Document Format

markdown

# [Research Topic Title]

**Generated**: YYYY-MM-DD
**Research Depth**: XX+ rounds of deep retrieval, covering XXXX, XXXX, XXXX

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## Core Conclusions

[Most important findings and conclusions, 2-3 paragraphs, thorough and detailed]

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## I. [Main Content One]

### (1) Subsection

Body paragraph. Use inline link format for source citations:
- According to [Source Name](https://link)...
- Based on [Material](https://link)...

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## II. [Main Content Two]

[Continue structured content]

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## III. Application Recommendations

### (1) Key Recommendations

**Content**: [Specific content]

### (2) Precautions

⚠️ [Warning point]

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Link Specifications

Core Principle

All source links must be embedded inline at corresponding positions in the text

markdown

✅ Correct:
According to [research report](https://link)...

❌ Incorrect:
According to some report...
(References listed separately at end)

Link Notation Conventions

• 🔗 -> General web resources
• 📚 -> Academic literature
• 🏛️ -> Institutional websites
• 📄 -> Data sources

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Document Naming Conventions

Numbering System

• 00. - Research overview
• 01-09. - Core research
• 10-19. - Important research
• 20+. - Extended research

Title Guidelines

• ✅ Use concise titles
• ✅ Avoid special characters
• ✅ Length within 15 words
• ✅ Clearly reflect research subject

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Quality Standards

Research Agent Quality

• Focus on single problem: Each research agent solves only one core problem
• Retrieval depth: 4-6 rounds of retrieval (just enough)
• Concise output: Clear and concise, just enough to solve the problem
• Key citations: Cite key sources (just enough)
• Directly usable: Provide directly actionable conclusions and recommendations

Document Quality Standards

• Clear structure: Chapter titles with clear hierarchy
• Coherent narrative: Paragraph-style narrative, avoid excessive listing
• Accurate links: All links embedded inline at corresponding positions
• Consistent format: Follow unified format specifications
• Strong actionability: Provide specific steps, tools, commands

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Precautions

Prohibited Actions

• ❌ Do not create sub-subdirectories (e.g., "reference-materials/")
• ❌ Do not generate separate executive summary files
• ❌ Do not use excessive bullet-point listing format
• ❌ Do not list references separately at document end
• ❌ Do not add redundant progress tracking sections

Recommended Practices

• ✅ Use narrative paragraph expression
• ✅ Embed links at corresponding text positions
• ✅ Keep research overview concise
• ✅ Provide specific action recommendations
• ✅ Mark clear document numbers

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Dependencies

This skill relies on Claude Code built-in tools, no additional configuration needed:

• WebSearch: Search discovery
• WebFetch: Get full content
• Task: Launch independent research agents

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Changelog

Version	Date	Changes
v1.1.0	2025-03-15	Translated to English
v1.0.0	2025-02-15	Migrated from Command to Skill, renamed to multi-topic deep research (multi-search)