jwynia/agent-skills/ebook-analysis
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Parse ebooks, extract concepts and entities with citation traceability, classify by type/layer, and synthesize across book collections.
Install
npx vskill@latest install jwynia/agent-skills/ebook-analysisSKILL.md
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.
Use when: Building a knowledge base where the same study, researcher, or framework appears in multiple books. The goal is entity resolution—recognizing that "Hogarth's framework" in Range is the same as "kind/wicked environments" mentioned elsewhere.
Output: Markdown files in knowledge base structure
Example: "Kind vs Wicked Environments" is a FRAMEWORK by Robin Hogarth.
Choosing a Mode
| If you want to... | Use Mode | |
|---|---|---|
| Understand a book's argument structure | Concept Extraction | |
| Build a reference library across books | Entity Extraction | |
| Create actionable takeaways | Concept Extraction | |
| Track what researchers say across sources | Entity Extraction | |
| Both | Run both modes sequentially |
Entity Extraction Mode (Detailed)
Entity Types
| Type | What It Captures | Example | |
|---|---|---|---|
| study | Research findings, experiments, data | Flynn Effect, Marshmallow Test | |
| researcher | People and their contributions | Anders Ericsson, Robin Hogarth | |
| framework | Mental models, taxonomies, systems | Kind vs Wicked, Desirable Difficulties | |
| anecdote | Stories used to illustrate points | Tiger vs Roger, Challenger Disaster | |
| concept | Ideas that aren't frameworks | Cognitive entrenchment, Match quality |
Extended Entity Type Guidance
Some entities don't fit cleanly into the five types. Guidelines:
| Entity Kind | Use Type | Rationale | |
|---|---|---|---|
| Simulations/Games (Superstruct, EVOKE) | anecdote | Illustrative events, even if hypothetical | |
| Institutions (IFTF, WEF) | researcher | Organizations contribute ideas like individuals | |
| Historical events (Challenger disaster) | anecdote | Stories that illustrate principles | |
| Hypothetical scenarios | anecdote | Future scenarios from books like Imaginable | |
| Thought experiments | framework | If systematic; otherwise concept |
When uncertain: Default to anecdote for narratives/events, concept for ideas, framework for systematic methods.
Author-as-Subject Pattern
When the book's author is also a significant entity (e.g., Jane McGonigal in Imaginable):
Create a researcher entity if:
- Author has notable prior work or institutional affiliation
- Author appears in Wikipedia or other reference sources
- Author's background/credentials are relevant to understanding the book
- Other books in your collection might reference them
Skip if:
- Author is primarily known only for this book
- No external sources to verify/enrich the entity
Template addition for author-subjects:
Entity File Template
Knowledge Base Structure
Quotes Extraction
Quotable quotes are a distinct extraction type. For each book, create a quotes file:
File: _[book-slug]-quotes.md
Structure:
What makes a good quote:
- Memorable phrasing that captures a key insight
- Self-contained (understandable without context)
- Surprising or counterintuitive formulation
- Useful for presentations, writing, or reference
Entity Extraction Workflow
- Scan book - Read through identifying named studies, researchers, frameworks, illustrative stories
- Check existing entities - Use
kb-resolve-entity.tsto see if entity already exists - Create or update - New entity → create file; existing → add as source
- Add quotes - Extract memorable quotes to quotes file
- Cross-link - Add Related Entities sections
- Regenerate index - Run
kb-generate-index.ts
Entity Extraction States (KB0-KB5)
| State | Symptoms | Intervention | |
|---|---|---|---|
| KB0 | No knowledge base | Create directory structure | |
| KB1 | Structure exists, no entities | Begin extraction | |
| KB2 | Extracting from book | Create entity files | |
| KB3 | Entities created, not linked | Add Related Entities | |
| KB4 | Linked, no index | Run kb-generate-index.ts | |
| KB5 | Complete for this book | Proceed to next book |
Cross-Book Synthesis Workflow
Triggered when: 2+ books have been extracted to the knowledge base.
Goals:
- Find entities that appear in multiple books
- Identify conceptual connections between books
- Surface contradictions or complementary perspectives
- Update entity files with multi-source synthesis
Process:
- Entity overlap detection
``bash # Find entities with 2+ sources grep -l "Sources in Collection" knowledge/nonfiction/**/*.md | \ xargs grep -l "| .* | .* |" | head -20 `` Or manually review entities updated with new source.
- Conceptual connection mapping
- Compare frameworks across books (e.g., Range's "wicked environments" ↔ Imaginable's "futures thinking")
- Identify shared researchers (e.g., Tetlock appears in both Range and Imaginable)
- Look for complementary themes (prediction failure → preparation despite uncertainty)
- Synthesis documentation
For entities appearing in 2+ books, update the Summary section: ``markdown ## Summary [Synthesized understanding from BOTH sources, noting agreements and differences] ``
- Cross-book insights
Document thematic connections in context/insights/cross-book-{theme}.md: ```markdown # Cross-Book Insight: [Theme]
## Books Contributing
- Range (Epstein) - [perspective]
- Imaginable (McGonigal) - [perspective]
## Synthesis [How the books complement or contradict each other] ```
Concept Extraction Mode (Detailed)
Concept Types (Abstract → Concrete)
| Type | Definition | Example | |
|---|---|---|---|
| Principle | Foundational truth or axiom | "Communities form around shared identity" | |
| Mechanism | How something works | "Reciprocity creates social bonds" | |
| Pattern | Recurring structure or approach | "The community lifecycle pattern" | |
| Strategy | High-level approach to achieve goals | "Build trust before asking for contribution" | |
| Tactic | Specific actionable technique | "Send welcome emails within 24 hours" |
Abstraction Layers
| Layer | Name | Abstraction | Example | |
|---|---|---|---|---|
| 0 | Foundational | Universal principles | "Humans seek belonging" | |
| 1 | Theoretical | Domain-specific theory | "Community requires shared purpose" | |
| 2 | Strategic | Approaches and frameworks | "The funnel model of engagement" | |
| 3 | Tactical | Specific methods | "Onboarding sequences" | |
| 4 | Specific | Concrete implementations | "Use Discourse for forums" |
Relationship Types
| Relationship | Meaning | When to Use | |
|---|---|---|---|
| INFLUENCES | A affects B | Causal or correlational connection | |
| SUPPORTS | A provides evidence for B | Citation, example, validation | |
| CONTRADICTS | A conflicts with B | Opposing claims | |
| COMPOSED_OF | A contains B | Part-whole relationships | |
| DERIVES_FROM | A is derived from B | Logical conclusions |
Concept Extraction States (EA0-EA7)
| State | Symptoms | Intervention | |
|---|---|---|---|
| EA0 | No input file | Guide file preparation | |
| EA1 | Raw file, not parsed | Run ea-parse.ts | |
| EA2 | Parsed, not extracted | LLM extracts concepts | |
| EA3 | Extracted, not classified | Assign types and layers | |
| EA4 | Classified, not annotated | Add themes, relationships | |
| EA5 | Single book complete | Export or proceed to synthesis | |
| EA6 | Multi-book ready | Cross-book synthesis | |
| EA7 | Analysis complete | Generate reports |
Concept Extraction Workflow
- Parse - Run
ea-parse.tsto chunk book with position tracking - Extract - Present chunks to LLM for concept identification with exact quotes
- Classify - Assign type (principle→tactic) and layer (0-4)
- Annotate - Add themes and functional analysis
- Link - Connect related concepts
- Export - Generate analysis.json, concepts.json, report.md
Available Tools
Parsing Tools
ea-parse.ts
Parse ebook files into chunks with metadata and position tracking.
Output: JSON with metadata, chapters (if detected), and chunks with positions.
Knowledge Base Tools
kb-generate-index.ts
Scan knowledge base and generate searchable entity index.
Output: Creates _entities.json with all entities, aliases, and metadata.
This is the start of the file. Read the full SKILL.md on GitHub.
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Source
- SKILL.md in the repositoryCheckingskills/general/document-processing/analysis/ebook-analysis/SKILL.md
Popularity
- Repository stars
- 33
- Repository forks
- 7
- 7-day trend score
- 18
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 18 Mar 2026, 7 months ago.
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