rabbit-hole

Orchestrate multi-agent investigations across codebases, web pages, documentation, and academic papers.

2|Updated Mar 1, 2026
One-click install
npx skills add https://github.com/synapseradio/ai-skills --skill rabbit-hole
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rabbit-hole
Source: https://github.com/synapseradio/ai-skills/tree/main/skills/rabbit-hole
Command: npx skills add https://github.com/synapseradio/ai-skills --skill rabbit-hole

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill tackles complex research questions that require synthesizing information from multiple sources, ensuring all findings are rigorously validated and cited.

Core Features & Use Cases

  • Multi-Source Investigation: Searches and analyzes information across codebases, web pages, documentation, and academic papers.
  • Automated Validation: Verifies all extracted citations to ensure accuracy and reliability.
  • Structured Synthesis: Presents findings in a clear, organized report, highlighting convergence, divergence, and knowledge gaps.
  • Use Case: When researching a complex technical topic like "How does React's concurrent rendering work under the hood?", this Skill can systematically explore official documentation, relevant code repositories, and academic discussions to provide a comprehensive, trustworthy answer.

Quick Start

Use the rabbit-hole skill to investigate how React's concurrent rendering works.

Frequently Asked Questions about rabbit-hole

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

FAQPage Schema
How do I conduct multi-source research with automated citation validation?

Multi-source research with automated citation validation is performed by orchestrating a multi-agent investigation pipeline that manages triage, scouting, parallel investigation, and validation phases to synthesize findings across diverse data sources.

What is the best way to synthesize information across codebases and academic papers?

The best way to synthesize information across codebases and academic papers is through a structured investigation pipeline that searches, analyzes, and cross-validates sources, presenting findings in a clear report highlighting convergence, divergence, and knowledge gaps.

Can I investigate complex technical questions across diverse data sources automatically?

Yes, you can investigate complex technical questions automatically by deploying specialized agents that execute parallel investigation and validation phases across web pages, documentation, and code repositories.

Does multi-agent research synthesis handle knowledge gaps and conflicting sources?

Multi-agent research synthesis handles knowledge gaps and conflicting sources by presenting structured findings that explicitly highlight convergence, divergence, and missing information discovered during the cross-source validation process.

When do I need to use a multi-agent investigation pipeline for research?

You need a multi-agent investigation pipeline when researching complex topics that demand thorough, verifiable information retrieval across diverse data sources, ensuring all extracted citations are rigorously validated and cross-referenced.