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.