deep-research

Conduct multi-source research and produce cited findings with confidence levels.

Updated Apr 10, 2026
One-click install
npx skills add https://github.com/LuizEduPP/skills --skill deep-research-luizedupp
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/LuizEduPP/skills/tree/main/deep-research
Command: npx skills add https://github.com/LuizEduPP/skills --skill deep-research-luizedupp

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Deep research requests often return superficial summaries, so this skill replaces guesswork with evidence-backed investigations that capture the full context of complex topics.

Core Features & Use Cases

  • Structured planning: Break down broad questions into focused objectives, scope, and success criteria before starting research.
  • Multi-source gathering: Combine web search, documentation, academic papers, and community signals to cover every facet of the subject.
  • Critical synthesis: Produce executive summaries, detailed findings, practical implications, and metadata that cite sources and state confidence.
  • Use Case: Use the skill to compare AI agent evaluation methodologies, analyze emerging technology trends, or review the latest academic literature with clear citations.

Quick Start

Ask the deep-research skill to investigate AI agent evaluation metrics using multiple credible sources and synthesize actionable findings with citations.

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 for complex topics with validated evidence?

Multi-source research combines web search, documentation, academic papers, and community signals to capture full context. It breaks broad questions into focused objectives and scope, then delivers structured outputs with detailed findings, critical analysis, and source attribution.

What's the best way to synthesize academic literature with clear citations?

Synthesizing academic literature requires combining web search and documentation with critical analysis. It produces executive summaries, detailed findings, practical implications, and research metadata that cite sources and state confidence levels for the reviewed literature.

Can I use web search to compare AI agent evaluation methodologies?

Yes, web search can investigate AI agent evaluation metrics by gathering signals from multiple credible sources. It synthesizes actionable findings with citations, comparing methodologies through structured planning and evidence-backed analysis.

Does multi-source research work for analyzing emerging technology trends and business strategies?

Multi-source research works across AI systems, technology trends, academic subjects, business strategies, and current events. It conducts comprehensive investigations requiring validated evidence, delivering structured outputs with practical implications and confidence levels.

What is included in structured research outputs for evidence-based analysis?

Structured research outputs include executive summaries, detailed findings, critical analysis, practical implications, source attribution, and research metadata. They flag confidence levels to ensure evidence-based analysis replaces superficial summaries with validated investigations.

When should I avoid using automated research for academic reviews?

Automated research should be avoided when topics require peer-reviewed validation beyond web search and community signals. It flags confidence levels, but may lack access to paywalled academic databases, limiting critical synthesis for strictly formal academic reviews.