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deep-research

Produce multi-source web research reports with inline citations in Markdown.

3|3|Updated Apr 5, 2026
Search Tags:#research#benchmarking#firecrawl#citations#synthesis#web-search#due-diligence
One-click install
npx skills add https://github.com/diegocamara89/ai-skills-hub --skill deep-research-diegocamara89
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/diegocamara89/ai-skills-hub/tree/main/all-skills/deep-research
Command: npx skills add https://github.com/diegocamara89/ai-skills-hub --skill deep-research-diegocamara89

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates time-consuming manual web investigation by orchestrating multi-source searches, deep-reading key documents, and producing a single, evidence-backed report with precise source attribution.

Core Features & Use Cases

  • Multi-source search orchestration: combines web search and semantic tools to gather 15-30 relevant sources across news, papers, forums, and benchmarks.
  • Deep-read synthesis with citations: reads full pages, extracts facts, cross-references claims, and produces structured Markdown reports with inline citations and a sources list.
  • Parallelized subagents for scale: splits broad topics into focused agents (benchmarks, reviews, news) and merges findings into a coherent executive summary.
  • Use Case: perform due diligence on a technology vendor, produce a competitive landscape report, or compile benchmark comparisons with verifiable citations.

Quick Start

Use the deep-research skill to produce a cited research report on "State of AI coding assistants in 2025" covering key tools, benchmarks, pricing, and developer sentiment.

Frequently Asked Questions about deep-research

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

FAQPage Schema
How do I generate multi-source web research reports with inline citations?▼

Multi-source web research reports with inline citations are generated by orchestrating parallelized subagents to search the web, deep-read full pages, cross-reference claims, and synthesize findings into a structured Markdown document with verifiable source attribution.

What's the best way to automate due diligence research on a technology vendor?▼

Automated due diligence is best handled by splitting broad topics into focused agents that gather 15-30 sources across news and benchmarks, cross-reference facts, and merge findings into a coherent executive summary with precise citations.

Do I need a web search tool to produce cited competitive benchmarking reports?▼

Yes, producing cited competitive benchmarking reports requires at least one configured web search or fetch tool, along with the ability to deep-read full pages and extract facts for cross-referencing.

How does deep-read synthesis work for technical literature reviews?▼

Deep-read synthesis for technical literature reviews works by reading full pages, extracting factual claims, cross-referencing them across multiple sources, and producing a structured Markdown report with inline citations and a sources list.

Can I compile market analysis reports by merging findings from parallelized research agents?▼

Yes, you can compile market analysis reports by splitting broad topics into focused parallelized subagents that gather benchmarks, reviews, and news, then merging their findings into a coherent executive summary.

What are the limitations of using automated web research for evidence-backed synthesis?▼

Automated web research for evidence-backed synthesis is limited by the configured search tool's reach and the ability to deep-read full pages, meaning heavily paywalled or dynamically rendered sources may restrict cross-referencing accuracy.

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