Ebook Analysis
This pulls structured knowledge out of non-fiction ebooks with full citation traceability to source chapters. You get two modes: concept extraction for ideas organized by abstraction level (principles down to tactics), and entity extraction for things that recur across books like frameworks, studies, and researchers. The entity mode is designed for building a cross-referenced knowledge base where you can track how the same research or framework gets used in multiple books. Every extraction must be traceable, which means you'll extract less but actually be able to cite it later. Includes tooling for entity resolution and index generation. Best for serious readers building a reference library rather than casual note-taking.
- skills.sh installs
- 397
- GitHub stars
- 182
- last updated
- Aug 21, 2026
Install
$ npx -y skills add jwynia/agent-skills --skill ebook-analysis --agent claude-codeInstalls into .claude/skills of the current project.
Files
Ebook Analysis: Non-Fiction Knowledge Extraction
You analyze ebooks to extract knowledge with full citation traceability. This skill supports two complementary extraction modes:
- Concept Extraction - Extract ideas classified by abstraction (principle → tactic)
- Entity Extraction - Extract named things (studies, researchers, frameworks, anecdotes) that persist across books
Core Principle
Every extraction must be traceable to its exact source. Citation traceability is non-negotiable. Extract less with full provenance rather than more without it.
Two Extraction Modes
Mode 1: Concept Extraction
For extracting IDEAS organized by abstraction level.
Use when: Analyzing a book for transferable ideas, building a concept taxonomy, understanding how abstract principles relate to concrete tactics.
Output: JSON files (analysis.json, concepts.json)
Example: "Spaced repetition improves retention" is a MECHANISM at Layer 2.
Mode 2: Entity Extraction
For extracting NAMED THINGS that can be cross-referenced across books.
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- Repository
- github.com/jwynia/agent-skills
- Category
- AI & Agent Building
- First seen
- Jun 3, 2026
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