Non-Fiction Book Curator & Synthesizer (okc-bookSummary) — High-Density Actionable Synthesis (HDAS)

Transforms knowledge from non-fiction books and long documents into rich, actionable, and deeply analytical chapter-by-chapter summaries directly inside the Obsidian Vault (VAULT_ROOT), combining continuous narrative depth with active learning, strategic mental models, and immediate real-world application.

🎯 Primary Execution Rules

1. Default Upload to Obsidian (VAULT_ROOT): All processed content (master book note, individual chapter notes, images in assets/images/, #flashcard cards, glossary, wiki/ concepts, and Master Plan updates) MUST be written exclusively and by default to the Obsidian Vault (VAULT_ROOT).
2. Sequential Chapter-by-Chapter Processing (FastMCP Streamlined):
   • Step 1 (Fetch & Stage): Execute native FastMCP tool fetch_book_data(file_path="<file>", slug="<slug>") on the okc server (or CLI fallback uv run python scripts/fetch_book_data.py --input <file> --slug <slug>).
   • Step 2 (Synthesize Chapters & Master Note): Generate chapter notes (Chapter 00 — <Title>.md, Chapter 01 — <Title>.md, ...), the Executive Master Book Note (<Author> — <Book Title>.md), and relevant wiki/ concepts in memory adhering to HDAS standards.
   • Step 3 (Atomic Batch Commit): Commit all chapter notes, the executive master note, and wiki concepts in a single atomic transaction with incremental sync using FastMCP commit_curated_batch:

     commit_curated_batch(
         raw_notes={
             "dataScienceKnowledgeBase/<Category>/raw/books/<Author> — <Book Title>/Chapter 01 — <Title>.md": "...",
             "dataScienceKnowledgeBase/<Category>/raw/books/<Author> — <Book Title>/Chapter 02 — <Title>.md": "...",
         },
         master_plan_path="dataScienceKnowledgeBase/<Category>/raw/books/<Author> — <Book Title>.md",
         master_plan_content="...",
         wiki_notes={"MentalModelName.md": "..."},
         target_kb="dataScienceKnowledgeBase/<Category>",
         fast_sync=True
     )

   • Step 4 (Clean Staging): Execute native FastMCP tool clean_staging_temp() to safely purge temp/ without terminal commands.
   • Zero-Spam Policy: Perform any vault checks silently using native cortex tools (find_by_name, view_file, find_notes). Never run exploratory terminal commands (python3 -c, ls, etc.).
3. High-Density Actionable Synthesis (HDAS Standard):
   • Dense Narrative Prose: Articulated explanatory paragraphs explaining cause, effect, and dynamics.
   • Front-Loaded Insights: Core mental models named and bolded (e.g. Insight 1: [Mental Model Name]).
   • Actionable Tooling (The "How"): Concrete step-by-step implementation, a 15-minute challenge, and a self-reflection prompt per chapter.
   • Smart Commentary: Cross-domain synthesis connecting the chapter's thesis to other authoritative works and mental models.
   • Common Pitfalls ([!warning]): Explicit warnings about common misapplications or biases.
4. Mandatory Diagrams and Visual Assets:
   • Embed extracted images/figures from the source document using ![[assets/images/<slug>-img-X.png]].
   • Reconstruct conceptual maps, architectures, and decision workflows using native Mermaid.js diagrams.

🎯 File Architecture in Obsidian (VAULT_ROOT)

Each processed book generates the following directory structure inside the Vault:

VAULT_ROOT/dataScienceKnowledgeBase/<Category>/raw/books/
├── <Author> — <Book Title>.md       # Executive Master Note (Synopsis, Architecture Map, Index, Flashcards, Glossary)
└── <Author> — <Book Title>/
    ├── Chapter 00 — <Title>.md      # Individual Chapter Note (HDAS Standard)
    ├── Chapter 01 — <Title>.md
    └── ...

📋 Standard Chapter Architecture (Chapter XX — <Title>.md)

Each chapter note must contain the following 7 structured sections:

# Chapter XX — <Chapter Title>

> **<Author> — <Book Title>**
> Source: Book / Audio Ingestion · Date: YYYY
> Part of: [[<Author> — <Book Title>]]
> Type: book-chapter
> Processed: DD-MM-YYYY
> Tags: #no-read-yet #book-summary #actionable-insights #mental-models

### 1. Central Thesis & One-Sentence Insight
*The major epiphany of the chapter synthesized with immediate impact.*
Narrative context of how this section integrates into the author's overarching thesis.

### 2. Inquiry Questions
1. Critical question 1...?
2. Critical question 2...?
3. Critical question 3...?
4. Critical question 4...?
5. Critical question 5...?

### 3. Enriched Summary Development (Narrative Depth & Mental Models)
Dense and articulated paragraphs (avoid dry bullet lists) explaining root causes, dynamics, and consequences:
- **Insight 1: [Name of Mental Model / Core Mechanism]**
  In-depth explanation of logic, empirical evidence, and historical nuances.
- **Insight 2: [Name of Mental Model / Core Mechanism]**
  Operational mechanics and determining factors.
- **Insight 3: [Name of Mental Model / Core Mechanism]**
  Strategic implications and industry transformations.

> [!example] Visual Metaphor / Analogy: <Title>
> The author's signature analogy or illustrative story to anchor the concept in memory.

> [!quote] Key Quote & Real-World Case: <Title>
> Real-world case study with its foundational lesson.

> [!warning] Common Pitfall & Bias to Avoid: <Title>
> The typical mistake or trap encountered when erroneously interpreting or applying this principle.

```mermaid
flowchart TD
    A[Trigger / Mental Model] --> B[Decision Dynamics]
    B --> C[Outcome / Strategic Impact]

4. Smart Commentary (Cross-Domain Connections & Extended Context)

High-level analysis connecting the chapter's thesis to other authors, foundational books (e.g., The Second Machine Age, Superintelligence, Homo Deus, Blitzscaling, Lean Startup), or contemporary technological developments.

5. Practical Application Guide (The "How")

• Actionable Step-by-Step: 3 to 4 specific steps to implement the concept at work, in engineering projects, or in decision-making.
• Immediate 15-Minute Challenge: Practical hands-on exercise to execute today.
• Self-Reflection Prompt: Introspective inquiry to audit your current workflow or architecture.

6. Critical Analysis & Model Boundaries

Honest evaluation of author biases, edge-case exceptions where the model fails, and counterarguments from the field.

7. Executive One-Sentence Takeaway

The definitive actionable conclusion to remember always.

---

## 📖 Executive Master Note Structure (`<Author> — <Book Title>.md`)

The Master Note serves as the central hub for the book at the root of `raw/books/`:

```markdown
# <Book Title>

> **<Author> — <Book Title>**
> Type: book | non-fiction
> Processed: DD-MM-YYYY
> Status: [[Chapter 00 — <Title>]], [[Chapter 01 — <Title>]] ...
> Tags: #no-read-yet #book-summary #master-note

## 📌 Executive Synopsis
(Fluid summary of 300-500 words covering the core thesis of the book, the problems it addresses, and the value of reading it).

## 🗺️ Book Architecture Map
```mermaid
mindmap
  root((<Book Title>))
    Part 1: Foundations
      [[Chapter 00 — <Title>]]
      [[Chapter 01 — <Title>]]
    Part 2: Mechanics and Dynamics
      [[Chapter 02 — <Title>]]

📚 Chapter Index & Mental Models

🎴 Study Flashcards (#flashcard)

#flashcard Q: What is the central thesis advocated by the author in the book? A: Concise and precise answer.

Q: How does concept X connect to principle Y? A: Dynamics explanation.

📖 Specialized Glossary

Term: Detailed definition in the context of the book.

🔗 Related Wiki Concepts

• [[ConceptA]]
• [[ConceptB]]

---

## 🚀 Execution & Integration Workflow

1. **Ingest and Segment**: Begin with `uv run python scripts/fetch_book_data.py --input <file> --slug <slug>`.
2. **Sequential Chapter Generation**: Create each `Chapter XX — <Title>.md` note sequentially in `raw/books/<Author> — <Book Title>/` using the 7-section HDAS standard.
3. **Master Note Creation**: Create `<Author> — <Book Title>.md` in the root of `raw/books/`.
4. **Wiki Enrichment**: Create or update concept pages in `wiki/` with bidirectional wikilinks.
5. **Staging Cleanup**: Run `uv run python scripts/fetch_book_data.py --clean`.
6. **Vault Sync**: Run `uv run python scripts/sync_vault.py`.