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YuriNakayama
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research-clustering

Cluster research domains from text or keywords into 3–8 structured groups with strategies.

Updated Jan 2, 2026
Search Tags:#research#surveys#strategy#taxonomy#mapping#clustering#domain-identification
One-click install
npx skills add https://github.com/YuriNakayama/research --skill research-clustering
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-clustering
Source: https://github.com/YuriNakayama/research/tree/main/.claude/skills/research-clustering
Command: npx skills add https://github.com/YuriNakayama/research --skill research-clustering

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cluster and map research targets from text or keywords into a structured domain plan, enabling focused exploration and strategized investigation.

Core Features & Use Cases

  • Domain identification and clustering: extract core domains from input seeds and partition them into cohesive clusters with clear boundaries.
  • Multi-level structuring: support 3–8 clusters with optional two-level hierarchy to reflect natural domain sub-areas.
  • Output & guidance: provide an overview, relevant keywords, and a tailored research strategy for each cluster; in Detailed mode, include seed resources from survey papers to inform taxonomy mapping.

Quick Start

Provide a research theme or keywords to generate domain clusters, overviews, and a strategy for deeper investigation.

Frequently Asked Questions about research-clustering

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I map research domains from text into structured clusters?▼

To map research domains from text, provide a research theme or keywords to generate 3–8 structured clusters with overviews, relevant keywords, and tailored research strategies for focused exploration.

What is research clustering and when do I need a taxonomy map?▼

Research clustering is the process of identifying and structuring research domains from input seeds. You need a taxonomy map to enable focused exploration and strategized investigation of complex topics.

Can I generate a two-level hierarchy for research domain identification?▼

Yes, you can generate a multi-level structuring output. Research clustering supports 3–8 clusters with an optional two-level hierarchy to reflect natural domain sub-areas.

How do I extract a research strategy and keywords from survey papers?▼

By processing text or keyword groups in Detailed mode, the clustering mechanism leverages web search to discover related domains and includes seed resources from survey papers to inform taxonomy mapping.

What is the best way to structure research targets from raw text?▼

The best way to structure research targets is to input raw text or keyword groups into a clustering process that partitions them into cohesive clusters with clear boundaries and structured overviews.

Can I publish the generated clustering output as documentation?▼

Yes, the clustering output is generated as a structured format that can be published as documentation, providing overviews, keywords, and research strategies for each identified domain cluster.

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