Can I use this for industry-focused or non-academic topics?

Yes. While it excels at research-heavy fields, it includes a recovery mode for 'practice-origin' concepts that lack formal academic papers, focusing instead on practical evolution.

How does Deep Dive differ from a simple concept search?

Deep Dive connects conceptual definitions with their original academic provenance, building a citation tree to show exactly how a field's ideas evolved over time.

What output formats does the skill provide?

It generates enriched markdown concept cards, summary reports with Mermaid diagrams, and structured folder hierarchies optimized for Obsidian vaults.

How does it decide which papers to focus on?

The skill uses 'Anchor Concept Selection,' prioritizing terms with high interconnectedness, clear seminal origins, and user-specified interest levels.

Deep Dive Research & Domain Explorer

Name: Deep Dive Research & Domain Explorer
Author: devkade

bydevkade

Aprendizaje y Documentación

Explores complex domains by mapping core concepts to their academic research origins and citation genealogy.

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Deep Dive is a specialized capability for Claude Code designed for intensive domain learning and academic mapping. It bridges the gap between conceptual definitions and research literature by identifying 'anchor concepts' and tracing their roots to seminal papers and influential authors. This skill is ideal for practitioners and researchers who need to understand the evolution of a field, providing structured outputs like enriched concept cards, citation trees, and Obsidian-ready knowledge vaults.

Características Principales

Identifies seminal research papers for foundational 'anchor' concepts
Builds multi-generational citation trees (parents, children, and bridge papers)
0 GitHub stars
Supports structured exports for Obsidian vaults including Canvas visualizations
Extracts core domain vocabulary with expert-level token priming
Generates integrated learning paths with difficulty-rated concept tiers

Casos de Uso

Onboarding into a complex technical domain like Reinforcement Learning or Bioinformatics
Creating a structured knowledge base for a new research project or thesis
Mapping the academic evolution and foundational literature of a specific technology

Acerca de

Características Principales

Identifies seminal research papers for foundational 'anchor' concepts
Builds multi-generational citation trees (parents, children, and bridge papers)
0 GitHub stars
Supports structured exports for Obsidian vaults including Canvas visualizations
Extracts core domain vocabulary with expert-level token priming
Generates integrated learning paths with difficulty-rated concept tiers

Casos de Uso

Onboarding into a complex technical domain like Reinforcement Learning or Bioinformatics
Creating a structured knowledge base for a new research project or thesis
Mapping the academic evolution and foundational literature of a specific technology