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deep-research

Orchestrate multi-agent research pipelines for complex technical questions.

4|1|Updated Feb 20, 2026
Search Tags:#research#analysis#multi-agent#protocol design#adversarial critique#EIP analysis
One-click install
npx skills add https://github.com/lodekeeper/dotfiles --skill deep-research-lodekeeper
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/lodekeeper/dotfiles/tree/main/skills/deep-research
Command: npx skills add https://github.com/lodekeeper/dotfiles --skill deep-research-lodekeeper

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill tackles complex questions that require more than a single-shot answer, such as in-depth EIP analysis, architectural decisions, or protocol design, by employing a structured, multi-agent approach.

Core Features & Use Cases

  • Decomposition: Breaks down complex queries into manageable sub-questions.
  • Parallel Investigation: Utilizes specialized agents (explorer, specialist, adversary) and tools (web search, code analysis, deep reasoning) concurrently.
  • Adversarial Critique: Employs AI agents to rigorously review and challenge findings, ensuring thoroughness.
  • Formalized Output: Produces structured research documents, analyses, and proposals.
  • Use Case: Researching the potential impact of a new Ethereum Improvement Proposal (EIP) by analyzing its technical specification, surveying existing client implementations, and evaluating its economic implications.

Quick Start

Initiate a deep research task on the topic of 'cross-client consensus mechanisms' by running the deep-research skill.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How does multi-agent research handle complex protocol design analysis?▼

Multi-agent research orchestrates a pipeline that decomposes complex protocol design queries into parallel investigations, using specialized agents to concurrently analyze specifications and survey implementations.

What is adversarial critique in architectural decision analysis?▼

Adversarial critique in architectural decision analysis deploys specialized AI agents to rigorously review and challenge initial findings, ensuring thoroughness and validating structural integrity before finalizing formal output documents.

How do I analyze an Ethereum Improvement Proposal for technical and economic impact?▼

To analyze an Ethereum Improvement Proposal, use a structured research pipeline to break down the query, investigate technical specifications alongside client implementations concurrently, and evaluate economic implications.

Can I use deep reasoning tools for parallel investigation of EIP specifications?▼

Yes, deep reasoning tools like Oracle can be leveraged concurrently alongside web search and code analysis agents to perform parallel investigation of EIP specifications and architectural decisions.

When do I need a structured research pipeline for code analysis?▼

You need a structured research pipeline for code analysis when addressing complex questions that require decomposition, parallel investigation across specialized agents, and adversarial critique to produce formal output documents.

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