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deep-research

Decompose research objectives into structured sub-questions and orchestrate subagents for analysis.

1|Updated Feb 3, 2026
Search Tags:#research#analysis#agent#decomposition#synthesis#long-context
One-click install
npx skills add https://github.com/aztr0nutzs/ClaW_VieW_v1.0 --skill deep-research-aztr0nutzs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/aztr0nutzs/ClaW_VieW_v1.0/tree/main/skills/deep-research-1.0.1
Command: npx skills add https://github.com/aztr0nutzs/ClaW_VieW_v1.0 --skill deep-research-aztr0nutzs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes rules (resource) components.

What problem does it solve?

This Skill tackles complex, multi-step research tasks that require planning, decomposition, and long-context reasoning across various tools and files, providing synthesized, data-driven insights.

Core Features & Use Cases

  • Multi-Step Research Planning: Decomposes high-level objectives into structured sub-questions and executable tasks.
  • Task Decomposition & Orchestration: Coordinates specialized subagents for parallel exploration and domain-specific analysis.
  • Large-Context Document Analysis: Analyzes extensive documentation and search results using long-context reasoning.
  • Synthesized Reporting: Integrates findings into coherent, well-supported analyses or recommendations.
  • Use Case: Research the impact of solid-state battery technology on the global EV supply chain over the next decade.

Quick Start

Use the deepsearch skill with the query "Conduct a comprehensive analysis of the current state of autonomous AI agents in enterprise environments".

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I conduct complex research across multiple files and tools?▼

Complex research across multiple files and tools is conducted by decomposing high-level objectives into structured sub-questions, orchestrating subagents for analysis, and synthesizing findings into a coherent report.

What is the best way to analyze large-context documents for enterprise research?▼

Analyzing large-context documents for enterprise research is best handled by a subagent orchestration approach that uses long-context reasoning to process extensive documentation and synthesize data-driven insights.

Do I need a specific API key to run multi-step research decomposition?▼

Yes, running multi-step research decomposition requires a Crafted API key to execute the planning, subagent orchestration, and aggregated analysis tasks.

Can I use this approach for iterative research and knowledge persistence?▼

Yes, you can use this approach for iterative research because it persists knowledge throughout the process, enabling ongoing analysis and continuous synthesis of new context into your reports.

How does task decomposition work for long-context analysis?▼

Task decomposition for long-context analysis works by breaking complex objectives into executable tasks, coordinating specialized subagents for parallel exploration, and aggregating insights from various sources.

Are there limitations when synthesizing insights from extensive search results?▼

Synthesizing insights from extensive search results is limited by the capacity of long-context reasoning and requires a valid Crafted API key to execute the subagent orchestration without interruption.

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