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deep-research

Search academic papers, web, and social media to generate cited research reports.

1|Updated Feb 8, 2026
Search Tags:#fact-checking#report generation#content extraction#academic papers#multi-source research
One-click install
npx skills add https://github.com/framerslab/agentos-skills --skill deep-research-framerslab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/framerslab/agentos-skills/tree/main/registry/curated/deep-research
Command: npx skills add https://github.com/framerslab/agentos-skills --skill deep-research-framerslab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires serper, tavily, firecrawl, cohere, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of conducting thorough and accurate multi-source investigations, ensuring that users can trust the veracity and completeness of their research findings.

Core Features & Use Cases

  • Multi-source Investigation: Cross-reference claims across web, academic, and social sources.
  • Academic Search: Find papers on arXiv, Google Scholar, Semantic Scholar.
  • Content Extraction: Pull full text from URLs, YouTube transcripts, Wikipedia.
  • Search Aggregation: Query multiple search engines simultaneously.
  • Deep Crawling: Crawl entire domains for comprehensive coverage.
  • Multi-stage Reranking: High-precision results through configurable reranker chain.
  • Trend Discovery: Identify emerging topics across platforms.
  • Report Generation: Synthesize findings into structured reports with citations.
  • Use Case: A researcher investigating a topic needs to gather diverse sources and verify the accuracy of the information across them.

Quick Start

Utilize the deep-research skill to conduct a thorough investigation on the impact of climate change.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I conduct multi-source research across academic papers and the web?▼

Multi-source research cross-references claims across academic papers, web, and social media by querying platforms like arXiv and Google Scholar, extracting full text, and synthesizing findings into a structured report.

Can I crawl entire domains and extract content from YouTube transcripts?▼

Yes, content extraction pulls full text from URLs, YouTube transcripts, and Wikipedia, while deep crawling scans entire domains for comprehensive coverage to ensure no source is missed.

What is multi-stage reranking for search aggregation?▼

Multi-stage reranking is a configurable chain that filters search aggregation results from multiple engines simultaneously, ensuring high-precision outcomes by prioritizing the most relevant and accurate sources.

Do I need API access to Serper, Tavily, Firecrawl, and Cohere for fact-checking?▼

Yes, fact-checking and report generation require access to APIs including Serper, Tavily, Firecrawl, and Cohere to perform academic search, content extraction, crawling, and multi-source verification.

How do I identify emerging topics and generate trend discovery reports?▼

Trend discovery identifies emerging topics across platforms by aggregating search results and social media sources, then synthesizing those findings into structured reports with citations.

What is the best way to verify the accuracy of information found across multiple sources?▼

The best way to verify information accuracy is cross-referencing claims across web, academic, and social sources, applying multi-stage reranking to filter results, and generating a synthesized report with citations.

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