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deep-research

Execute an 8-phase research pipeline and generate reports in markdown, HTML, and PDF.

Updated Mar 3, 2026
Search Tags:#research#verification#analysis#reporting#synthesis#knowledge discovery
One-click install
npx skills add https://github.com/shimseonjo/lectuer_factory --skill deep-research-shimseonjo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/shimseonjo/lectuer_factory/tree/main/.claude/skills/deep-research
Command: npx skills add https://github.com/shimseonjo/lectuer_factory --skill deep-research-shimseonjo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill tackles complex research questions that require in-depth analysis, multi-source verification, and structured reporting, going far beyond simple web searches.

Core Features & Use Cases

  • Comprehensive Analysis: Conducts enterprise-grade research, synthesizing information from 10+ verified sources.
  • Multi-Source Verification: Ensures claims are backed by evidence through triangulation and credibility scoring.
  • Structured Reporting: Delivers professional reports with executive summaries, detailed analysis, and actionable recommendations.
  • Use Case: Use this Skill to compare competing technologies, analyze market trends, or review scientific literature for critical decision-making.

Quick Start

Use deep research to analyze the current state of AI agent frameworks in 2025.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I automate comprehensive research and generate a verified analysis report?▼

You can automate comprehensive research using an 8-phase pipeline that handles scope definition, parallel information retrieval, triangulation, and synthesis to generate verified analysis reports in markdown, HTML, and PDF formats.

What is the best way to verify sources and ensure citation credibility during research?▼

Source verification and citation credibility are ensured through a multi-source triangulation process that cross-references claims across 10+ verified sources and applies credibility scoring to back every finding with evidence.

Can I use automated research for comparing competing technologies and market trends?▼

Yes, automated research is designed for comparing competing technologies, analyzing market trends, and reviewing scientific literature by synthesizing multi-source data into structured reports with actionable recommendations.

How does multi-source synthesis work for complex knowledge discovery?▼

Multi-source synthesis works by executing parallel information retrieval, triangulating data across multiple sources, and applying critique and refinement phases to structure detailed findings into executive summaries and actionable recommendations.

Does deep research require any external dependencies or API connections to run?▼

No external dependencies are required to run the research pipeline, as the skill operates independently using its internal scripts, references, and assets to execute the full information retrieval and reporting workflow.

What are the limitations of automated research for scientific literature review?▼

Automated research limitations include reliance on source availability for triangulation and the need for human judgment during the critique phase, as the pipeline synthesizes existing verified sources rather than generating primary experimental data.

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