Research

Coordinate multi-agent searches and synthesize structured reports on-demand.

12|Updated Aug 16, 2019
One-click install
npx skills add https://github.com/phatblat/dotfiles --skill research-phatblat
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Research
Source: https://github.com/phatblat/dotfiles/tree/main/.claude/skills/Research
Command: npx skills add https://github.com/phatblat/dotfiles --skill research-phatblat

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a comprehensive system for conducting in-depth research, analyzing complex topics, and extracting valuable insights from various content sources, overcoming limitations of basic search.

Core Features & Use Cases

  • Multi-modal Research: Supports quick, standard, and extensive research modes using multiple AI agents.
  • Deep Content Analysis: Extracts "alpha" (novel, surprising insights) from content like videos and articles.
  • Specialized Workflows: Includes dedicated modes for interview preparation, AI trend analysis, and deep investigations.
  • Use Case: When asked to "research the future of AI," this Skill can perform extensive research, synthesize findings from multiple agents, and identify key trends and predictions.

Quick Start

Use the research skill to do a quick research on the latest advancements in quantum computing.

Frequently Asked Questions about Research

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

FAQPage Schema
How do I conduct deep research and synthesize complex information beyond a simple web search?

Deep research across multiple AI agents synthesizes findings from various sources, overcoming basic search limitations to provide multi-faceted understanding of complex topics. It extracts valuable insights through structured investigation protocols.

Can I extract novel insights and analysis from video content or articles?

Yes, deep content analysis extracts alpha, or novel and surprising insights, from content like videos and articles. This specialized workflow identifies valuable information that basic retrieval methods often miss.

What is the best way to prepare for an interview or analyze AI trends programmatically?

Specialized workflows offer dedicated modes for interview preparation and AI trend analysis. These protocols structure your investigation to identify key predictions and synthesize multi-faceted topic understanding.

Does this multi-agent research approach support different modes depending on complexity?

Yes, multi-modal research supports quick, standard, and extensive research modes. You can select the appropriate tier based on the complexity of the information retrieval and synthesis challenges you need to solve.

How do I perform a quick investigation on a topic like quantum computing advancements?

Use the quick research mode to rapidly investigate topics like latest advancements in quantum computing. This tier utilizes multiple AI agents to retrieve and synthesize information efficiently for faster results.

When should I avoid using an extensive research mode for content extraction?

Avoid extensive research modes when you need rapid answers or face strict time constraints. Reserve extensive multi-agent synthesis for complex information retrieval challenges requiring detailed, multi-faceted topic understanding.