deep-research

Orchestrate a six-phase team-based deep-research workflow across X, web, and academic sources.

Updated Feb 9, 2026
One-click install
npx skills add https://github.com/kensaku63/skills --skill deep-research-kensaku63
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/kensaku63/skills/tree/main/deep-research
Command: npx skills add https://github.com/kensaku63/skills --skill deep-research-kensaku63

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates a multi-phase, team-based deep-research workflow to deliver fact-based insights and unique hypotheses.

Core Features & Use Cases

  • Phase-driven orchestration across six phases (needs analysis, X research, web deep-dive, integration, hypothesis, delivery).
  • Multi-source integration of X (Twitter), Web, and academic literature with citations and structured outputs.
  • Hypothesis generation and final reporting, including executive summaries and detailed fact reports.
  • Collaborative team agent workflow with task management and validation across phases.
  • Use cases: ideal for deep investigations on complex topics, market/tech trend analyses, and strategic decision support.

Quick Start

Provide the topic you want researched and the system will automatically orchestrate the six-phase deep-research workflow.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I automate deep research across web, academic literature, and Twitter?

You can automate deep research by deploying a multi-agent team that orchestrates phased workflows across web, academic literature, and X (Twitter) to gather data, generate hypotheses, and deliver structured fact-based reports.

What is multi-agent team orchestration for deep research workflows?

Multi-agent team orchestration is a process that coordinates specialized agents across six phases—needs analysis, X research, web deep-dive, integration, hypothesis, and delivery—to execute fact-based investigations and cross-source verification.

How do I generate unique hypotheses from cross-source verification of complex topics?

You generate unique hypotheses from cross-source verification by using a multi-agent workflow that integrates live data from X, web deep-dives, and academic literature, synthesizing findings into structured hypothesis documents during a dedicated phase.

Can I use multi-agent research for market trend analysis and strategic decision support?

Yes, multi-agent research is ideal for market trend analysis and strategic decision support, orchestrating parallel web deep-dives and live data gathering to produce executive summaries and detailed fact reports for complex investigations.

What is the best way to structure a final research report with citations and executive summaries?

The best way to structure a final research report is through a dedicated delivery phase that outputs structured deliverables, combining an executive summary, detailed fact reports with citations, and generated hypothesis documents.

How to start a deep investigation using team agents?

To start a deep investigation using team agents, simply provide your research topic and the system will automatically orchestrate the six-phase workflow spanning needs analysis, data gathering, integration, and final reporting.