deep-research

Orchestrate an 8-phase research pipeline with verified claims and citations.

5|2|Updated Jan 24, 2026
One-click install
npx skills add https://github.com/s1366560/agi-demos --skill deep-research-s1366560
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/s1366560/agi-demos/tree/main/.memstack/skills/deep-research
Command: npx skills add https://github.com/s1366560/agi-demos --skill deep-research-s1366560

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of conducting thorough, multi-source research, providing verified, citation-backed reports that go beyond simple web searches. It tackles complex questions that require deep analysis and synthesis.

Core Features & Use Cases

  • Comprehensive Research: Conducts deep analysis on complex topics.
  • Multi-Source Synthesis: Integrates information from numerous sources.
  • Verification & Citation: Ensures claims are backed by evidence and properly cited.
  • Use Case: Use this Skill to research the competitive landscape for a new product, analyze the latest scientific advancements in a field, or compare complex technical solutions for a critical business decision.

Quick Start

Use deep research to analyze the state of quantum computing 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 deep research and multi-source synthesis for complex topics?▼

You can automate deep research using an 8-phase pipeline that handles scope definition, parallel information retrieval, triangulation, and synthesis to generate verified, citation-backed reports.

What is the best way to ensure research claims are verified and properly cited?▼

To ensure research claims are verified and properly cited, use a pipeline that performs multi-source triangulation, critique, and structured citation management before packaging the final synthesis report.

How does automated report generation handle enterprise-grade information retrieval?▼

Automated report generation handles enterprise-grade information retrieval by executing parallel information gathering across numerous sources, followed by critique and packaging into structured output formats.

Can I use this automated research approach for competitive landscape analysis?▼

Yes, you can use this automated research approach to analyze competitive landscapes, compare technical solutions, or assess scientific advancements by leveraging its multi-source synthesis capabilities.

Do I need Python scripts to run the multi-source analysis and reporting pipeline?▼

Yes, the multi-source analysis and reporting pipeline utilizes Python scripts to orchestrate its 8-phase workflow, ensuring structured output and proper citation management.

When should I avoid using an automated deep research pipeline?▼

You should avoid using an automated deep research pipeline for simple queries that require only a basic web search, as this process is designed for complex questions requiring deep analysis and triangulation.