deep-research

Execute autonomous multi-step research and generate cited reports with Gemini.

Updated Mar 7, 2026
One-click install
npx skills add https://github.com/involvex/llms-remote --skill deep-research-involvex
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/involvex/llms-remote/tree/main/.agents/skills/deep-research
Command: npx skills add https://github.com/involvex/llms-remote --skill deep-research-involvex

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires httpx, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates complex research tasks, transforming raw information into structured, actionable reports without manual intervention.

Core Features & Use Cases

  • Autonomous Planning & Execution: Plans, searches, reads, and synthesizes information across multiple steps.
  • Comprehensive Reporting: Generates detailed, cited research reports suitable for various professional needs.
  • Use Case: Use this skill to conduct a thorough market analysis for a new product, gathering data on competitors, market size, and trends, then synthesizing it into a comprehensive report.

Quick Start

Use the deep-research skill to research the history of Kubernetes.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I automate market analysis and literature reviews without manual information gathering?

To automate market analysis and literature reviews, you can use an autonomous multi-step research agent that plans, searches, reads, and synthesizes information into structured reports. This eliminates manual information gathering by executing comprehensive research workflows automatically.

What is autonomous multi-step research and how does it synthesize professional reports?

Autonomous multi-step research is a process where an agent independently plans, searches, reads, and synthesizes information across multiple steps. It transforms raw information into detailed, cited professional reports suitable for competitive landscaping and due diligence.

Do I need a Gemini API key and Python 3.8 to run autonomous research tasks?

Yes, you need Python 3.8 or higher and the GEMINI_API_KEY environment variable configured to run autonomous research tasks. These prerequisites allow the underlying agent to execute multi-step information gathering and synthesis.

Can I use this approach for competitive landscaping and technical due diligence?

Yes, you can use autonomous multi-step research for competitive landscaping and technical due diligence. The agent gathers data on competitors, market size, and trends, synthesizing the findings into a comprehensive, cited report for professional analysis.

What are the limitations of using an autonomous agent for complex information gathering?

A limitation of using an autonomous agent for information gathering is the dependency on external API availability and specific environment variables like GEMINI_API_KEY. Complex queries require multiple autonomous steps, which may increase processing time compared to manual targeted searches.