book-thesis

name	book-thesis
description	Metabook reasoning layer for the book-* skill suite. Owns the intent substrate: a thesis tree, paragraph back-pointers to thesis nodes, per-paragraph entailment checks, and a Datalog pass over claim triples for transitive cross-chapter contradictions. Use when a book needs to enforce three properties simultaneously: factual accuracy, cross-chapter consistency, and preservation of the core point across revisions. Composes with book-knowledge (facts), russellian-style (prose), book-compose (orchestrator), book-review (qualitative), book-qa (mechanical gate). Do NOT use for chapter drafting (use book-compose), claim ingestion (use book-knowledge), or sentence-grain prose discipline (use russellian-style).
license	MIT

book-thesis

The metabook reasoning layer. Owns the intent substrate of a book — the thesis statement, the sub-arguments that decompose it, and the requirement that every paragraph in the manuscript trace back to some node in that tree. Sibling to book-knowledge (which owns the fact substrate).

What it owns

• The thesis tree: a YAML/RDF graph rooted at :Thesis, with sub-arguments and required-evidence slots.
• Paragraph back-pointers: every paragraph in a draft carries a supports: field naming a tree node.
• The entailment loop: a per-paragraph LLM-critic dispatch that asks "does this paragraph actually advance its declared supports node?"
• The Datalog consistency pass: a small rule set that derives transitive contradictions across chapter-level claim triples.
• The exemplar pack: synthetic (supports-node, claim, paragraph) triples injected into the drafting prompt.

What it does NOT own

• Claim ingestion or claim-ledger maintenance. That is book-knowledge.
• Sentence-grain prose linting (hedges, passive voice, modifier budget). That is russellian-style.
• Chapter orchestration, bundling, and book release. That is book-compose.
• Qualitative editorial review by personas. That is book-review.
• Mechanical D1–D8 defect gating. That is book-qa. (book-thesis contributes D9–D12.)

Architecture (4 layers)

book-thesis sits as Layer 2–4 on top of book-knowledge's Layer 1:

┌─────────────────────────────────────────────────────────────┐
│ Layer 4  Datalog consistency pass                            │
│          rules/consistency.dl over claim triples             │
└────────────────────────┬────────────────────────────────────┘
┌────────────────────────▼────────────────────────────────────┐
│ Layer 3  Verifier-generator entailment loop                  │
│          per-paragraph LLM critic, grounded against the KG   │
└────────────────────────┬────────────────────────────────────┘
┌────────────────────────▼────────────────────────────────────┐
│ Layer 2  Thesis spine                                        │
│          YAML / RDF tree + paragraph back-pointers           │
└────────────────────────┬────────────────────────────────────┘
┌────────────────────────▼────────────────────────────────────┐
│ Layer 1  Claim ledger + RDF + SHACL (book-knowledge)         │
└─────────────────────────────────────────────────────────────┘

Components

• scripts/compile_thesis.py — read thesis/<book-id>.yaml, emit RDF triples into the book-knowledge graph.
• scripts/lint_supports.py — walk every paragraph in the manuscript; flag orphans (no supports:), broken supports (node doesn't exist), and chains that don't transitively reach :Thesis.
• scripts/dispatch_entailment.py — prepare per-paragraph payloads for an LLM entailment critic. Returns entailed | weakly-entailed | unrelated | contradicts.
• scripts/datalog_consistency.py — load claim triples + thesis tree into pyDatalog, run rules/consistency.dl, emit derived contradictions.
• scripts/synthesize_exemplars.py — Symbolic→LLM exemplar pack generator. Given the thesis tree + claim slice for a chapter, writes a few-shot exemplar bundle used by the drafting agent.
• rules/consistency.dl — the initial Datalog rule set (~15 rules) covering transitive contradiction, orphan paragraphs, thesis-reachability.

Composes with

• book-knowledge — fact substrate. book-thesis reads claim triples from book-knowledge's RDF graph and writes thesis triples back into it.
• book-compose — the chapter contract gains a thesis_advances: field naming sub-arguments. compile_thesis.py runs at the start of build_book.
• book-qa — defines four new defect classes (D9 orphan-paragraph, D10 transitive-contradiction, D11 failed-entailment, D12 unadvanced-sub-argument). lint_supports.py and datalog_consistency.py feed those gates.
• book-review — orthogonal. book-review's personas do qualitative review; book-thesis does formal-structural check.
• russellian-style — orthogonal. russellian-style polices sentence-grain; book-thesis polices argument-level.

Usage

# Compile a thesis spec into RDF triples
python scripts/compile_thesis.py <workspace> <book-id>

# Lint paragraph back-pointers against the thesis tree
python scripts/lint_supports.py <workspace> <release-version>

# Run the Datalog consistency pass
python scripts/datalog_consistency.py <workspace>

# Generate an exemplar pack for a chapter
python scripts/synthesize_exemplars.py <workspace> <chapter-id>

# Prepare entailment payloads (one per paragraph) for an LLM critic
python scripts/dispatch_entailment.py <workspace> <release-version>

Tests

Fixture-based pytest cases under tests/. Run with:

python -m pytest tests/ -v

Coverage:

• compile_thesis: round-trip YAML → triples → SPARQL query
• lint_supports: known-orphan paragraph fixture; known-good paragraph fixture
• datalog_consistency: contradicting-claim fixture (A→B in ch-1, B→¬A in ch-2)
• dispatch_entailment: payload-shape contract
• synthesize_exemplars: exemplar pack shape contract