deep-learning

Name: deep-learning
Availability: InStock
Author: mikonos

Structure long-form texts into connected Zettelkasten notes with templates.

2|1|Updated Mar 10, 2026

Search Tags:#atomic-notes #deep-reading #zettelkasten #structure-notes #method-notes #index-notes #luhmann-scan

Ready to run

npx skills add https://github.com/mikonos/zk-steward-companion --skill deep-learning-mikonos

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: deep-learning
Source: https://github.com/mikonos/zk-steward-companion/tree/main/skills/deep-learning
Command: npx skills add https://github.com/mikonos/zk-steward-companion --skill deep-learning-mikonos

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill helps turn books, long articles, and reports into a connected Zettelkasten-style knowledge network, producing structure notes, atomic notes, method notes, and index notes to support deep reading and knowledge management.

Core Features & Use Cases

Structure notes: extract core arguments, reading order, and argument maps.
Atomic notes: capture concepts with definitions, mechanisms, and context.
Method notes: compose SOPs, templates, checklists for actionable use.
Index notes: create entry points and multi-entry pathways to navigate the network.
Luhmann Scan & Reading Order: generate and link notes during reading to form a networked reading sequence.

Quick Start

Provide a book or long-form text to digest and I will generate the full deep-reading workflow (structure notes, index notes, atomic notes, and method notes) ready to mount into your knowledge network.

Frequently Asked Questions about deep-learning

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

FAQPage Schema

How do I turn a long book or report into a Zettelkasten knowledge network?▼

To build a Zettelkasten knowledge network from long texts, you structure content into connected atomic, structure, method, and index notes. This skill processes books and reports end-to-end using the Luhmann Scan to generate a navigable, linked reading sequence.

What is the Luhmann Scan and how does it help with deep reading?▼

The Luhmann Scan is a deep reading technique that generates and links notes sequentially during reading to form a networked reading order. It helps extract core arguments and concepts, transforming linear texts into a connected knowledge network of structure and atomic notes.

How do I create atomic notes and structure notes from long-form articles?▼

Creating atomic notes captures single concepts with definitions and context, while structure notes extract core arguments and argument maps. This skill automates that extraction from long-form articles, linking them together to support comprehensive digestion and knowledge grafting.

Can I use this Zettelkasten method for books and reports without any extra dependencies?▼

Yes, you can use this Zettelkasten method for books and reports without extra dependencies. It requires only frontmatter in SKILL.md with a name and description, using built-in templates and references to generate the full deep-reading workflow.

What is the best way to generate index notes for navigating a knowledge network?▼

The best way to generate index notes is to create multi-entry pathways that serve as navigation points for your knowledge network. This skill automatically produces these entry points alongside method notes and structure notes, ensuring all connected concepts remain easily accessible.

When should I use method notes instead of atomic notes in my knowledge management system?▼

Use method notes when you need actionable outputs like SOPs, templates, and checklists, whereas atomic notes capture static concepts, definitions, and mechanisms. This skill generates both types to support comprehensive digestion and practical application of your readings.