sc-research

Conduct deep research via Rube MCP web search and PAL MCP multi-model consensus.

19|2|Updated Aug 26, 2025
One-click install
npx skills add https://github.com/Tony363/SuperClaude --skill sc-research
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sc-research
Source: https://github.com/Tony363/SuperClaude/tree/main/.claude/skills/sc-research
Command: npx skills add https://github.com/Tony363/SuperClaude --skill sc-research

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of conducting in-depth research on any topic, overcoming information gaps and biases by leveraging real-time web search and multi-model AI consensus.

Core Features & Use Cases

  • Comprehensive Web Research: Gathers information from the web using sophisticated search queries.
  • Multi-Model Analysis: Utilizes multiple AI models to analyze findings, identify contradictions, and reach a consensus.
  • Structured Reporting: Generates detailed, well-sourced research reports with confidence assessments.
  • Use Case: A product manager needs to understand the competitive landscape for a new feature. This Skill can research existing solutions, analyze their strengths and weaknesses, and synthesize findings into a concise report.

Quick Start

Use the sc-research skill to perform a deep dive into the latest advancements in renewable energy technologies.

Frequently Asked Questions about sc-research

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

FAQPage Schema
How do I conduct deep research and generate structured reports with confidence assessments?▼

Conduct deep research by specifying a topic to trigger automated web searches and multi-model AI consensus analysis. This generates a structured report containing sourced findings and confidence assessments for complex information gathering.

What is multi-model AI consensus analysis for information gathering?▼

Multi-model AI consensus analysis utilizes multiple AI models to evaluate web search findings, identify contradictions, and reach a consensus. This overcomes individual model biases and ensures the final research output is balanced.

Can I use this for competitive landscape research and data analysis?▼

Yes, you can use this for competitive landscape research and data analysis. It gathers information on existing solutions, analyzes strengths and weaknesses, and synthesizes findings into a concise, well-sourced report.

Does this web search research tool require any external dependencies?▼

No external dependencies are required to use the tool. It integrates real-time web search via Rube MCP and multi-model consensus analysis via PAL MCP internally to automate the research process.

How do I automate reporting for complex information gathering needs?▼

Automate reporting by inputting a research topic; the system handles sophisticated web search queries and multi-model analysis to output detailed reports with sourced findings and confidence assessments automatically.

What are the limitations of using AI consensus for web research?▼

AI consensus research relies on real-time web search results, meaning quality depends on available online data. It synthesizes findings and assesses confidence but may still encounter information gaps or contradictory sources.