writing-intelligence

name

writing-intelligence

description

Writing Intelligence v3.0 — Sovereign Writing Operating System. 11-pass governed compiler, 12 engines, 12 specialist agents, 11 machine-readable schemas, epistemic ledger, voice fingerprinting, genre stacking, storyworld memory, arena delivery, benchmark regression. 27 domain packs (fiction, dialogue, thriller, transmedia, grant/NOFO, sermon, technical docs, social media, YouTube, newsletter, real estate, loan officer, church leadership, small business, journalism, resume, academic, sales, email, speech, pitch, government brief, medical, legal, patent, cinematic). Trigger on: write, rewrite, edit, draft, revise, ghostwrite, compile, audit, score, grade, redline, voice fingerprint, voice drift, genre stack, epistemic ledger, architecture graph, scene graph, delivery bundle, benchmark, prose, chapter, sermon, speech, pitch, memo, narrative, dialogue, scene, thriller, anti-slop, AI detection, grant writing, NOFO, resume, journalism, novel, screenplay, fiction writing.

Writing Intelligence v3.0 — Sovereign Writing Operating System

Author: Antonio T. Smith Jr. — Founder & CEO, Density6 LLC License: MIT Version: 3.0.0 (Sovereign Writing OS) Lineage: v1.0 (7-pass compiler, 52 files) → v2.0 (Fiction Intelligence Engine, 58 files) → v3.0 (11-pass governed kernel, 12 engines, 12 agents, schemas, benchmarks, governance)

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0. What v3.0 Is

v1.0 proved AI-sounding prose can be defeated by compilation instead of cosmetic cleanup. v2.0 proved fiction can be engineered as living architecture — scene, chapter, role, dialogue, power, tension, transmedia.

v3.0 proves something larger: authorship can be governed without being flattened.

Writing Intelligence v3.0 is no longer only a writing skill. It is an operating system for producing, auditing, scoring, preserving, and deploying high-integrity writing across genres, voices, teams, products, and longform worlds. It runs as one skill or as a coordinated multi-agent writing board. It emits human-readable scorecards and machine-readable JSON. It governs intent, voice, evidence, structure, and delivery — and it remembers what worked so the next release is provably better than the last.

The v3.0 Law: If a rule cannot be applied, audited, scored, tested, or explained — it is not a v3.0 rule yet.

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1. The v3.0 Formula

Intent → Corpus → Voice → Genre → Architecture → Evidence → Prose → Scene/Argument → Stress → Score → Delivery → Memory → Benchmark

Stage	Meaning	Required Output
Intent	What the writing must cause	Mission contract
Corpus	What source material governs it	Source map / input manifest
Voice	Who the writing must sound like	Voiceprint or fingerprint
Genre	Which domain rules apply	Genre pack stack
Architecture	How the piece is structured	Section / scene blueprint
Evidence	Which claims need support	Epistemic ledger
Prose	Actual language production	Draft output
Scene/Argument	Narrative or persuasive engine	Scene or argument graph
Stress	Weakness interrogation	Adversarial audit
Score	Quality measurement	Scorecard (human + JSON)
Delivery	Format-specific packaging	Output mode bundle
Memory	What persists across sessions	Continuity + project memory update
Benchmark	Whether quality improved	Regression results

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2. Architecture: 11-Pass Compilation Kernel

Every piece of writing processed by v3.0 runs through eleven sequential passes. Passes may be skipped only by explicit reason. Each pass leaves an audit artifact. Each rewrite preserves an original-to-new trace when redline mode is active.

Pass	Name	Purpose	Core Artifact
0	Intake Contract	Lock task, source, constraints, audience, output mode	IntakeContractV3
1	Mission Lock	Define what the text must do	MissionLockV3
2	Corpus & Context Ingestion	Map source material, user inputs, prior docs	CorpusMapV3
3	Diagnostic Scan	Identify residue, gaps, drift, slop, weak claims	DiagnosticReportV3
4	Architecture Compile	Build section, paragraph, scene, or argument structure	ArchitecturePlanV3
5	Evidence & Epistemic Ledger	Classify claims, sources, inferences, recommendations	EpistemicLedgerV3
6	Sentence Surgery	Remove slop, inject variance, sharpen language	SentenceSurgeryLogV3
7	Voice Restoration	Restore author fingerprint and voice integrity	VoiceMatchReportV3
8	Genre & Arena Alignment	Fit output to channel, profession, platform, reader	ArenaAlignmentV3
9	Adversarial Stress Battery	Attack the draft as reader, editor, skeptic, detector	StressBatteryV3
10	Score & Delivery Packaging	Produce final draft, scorecard, notes, formats	DeliveryBundleV3
11	Memory & Benchmark Update	Save learnings and regression data	MemoryBenchmarkUpdateV3

2.1 Pass-Level Execution Rules

• Every pass must be skippable only by explicit reason.
• Every pass must leave an audit artifact.
• Every score must identify the rule it came from.
• Every rewrite must preserve an original-to-new trace when redline mode is active.
• Every output must declare whether it is final, draft, audit-only, or benchmark-only.
• Every claim must be classified before it is strengthened.
• Every voice change must explain whether it increased or decreased authorial fidelity.

2.2 Pass 0 — Intake Contract

Read references/compiler/intake_contract.md and emit schemas/intake_contract.schema.json-shaped object. Lock task mode (draft / rewrite / score / redline / compress / expand / audit / convert / certify), word-count constraints, citation requirements, output formats, forbidden changes, audience, voice target. User-provided constraints override auto-detection.

2.3 Pass 1 — Mission Lock

Declare:

• Intent: inform / convert / warn / teach / dignify / dominate / comfort / reveal / mobilize / persuade / entertain / defend / terrify / disorient
• Audience: vocabulary, abstraction, evidence expectations
• Voice: voiceprint from references/voiceprints/
• Genre stack: one or more packs from references/genre_packs/
• Scale: sentence / paragraph / scene / chapter / arc / series
• Success condition: one sentence describing what "worked" looks like

2.4 Pass 2 — Corpus & Context Ingestion

Read references/compiler/corpus_governance.md. Separate: user-provided text, repo knowledge, source documents, prior project memory, examples, generated ideas. Mark source priority. Flag stale, contradictory, unsupported claims. Block invented source attribution. Emit CorpusMapV3.

2.5 Pass 3 — Diagnostic Scan

Read references/anti_patterns/phrases.md, structures.md, cadence.md, fake_depth.md. Identify:

• AI residue (phrases, structures, cadence patterns)
• Contradictions within the text
• Vagueness (claims without actors, actions, stakes, specifics)
• Cadence repetition (sentence-length uniformity, transition homogeneity)
• Argument gaps (unsupported claims, missing premises)
• Evidence gaps (assertions without backing)
• Tone drift (sections that shift register without cause)
• Perplexity flatness (vocabulary predictability across paragraphs)
• Burstiness deficit (lack of sentence-length variance)

2.6 Pass 4 — Architecture Compile

Read references/compiler/architecture_graph.md (sections, paragraphs, claims). For narrative work, also read references/compiler/scene_graph.md. For persuasive work, also read references/compiler/argument_graph.md. Build the graph. Detect orphan sections, unsupported claims, dead scenes, repeated beats. Emit ArchitecturePlanV3.

2.7 Pass 5 — Evidence & Epistemic Ledger

Read references/compiler/epistemic_ledger.md. Classify each major sentence as observed fact / sourced fact / inference / synthesis / recommendation / rhetoric. Mark source status: verified / user-provided / assumed / inferred / missing / unsafe. Cap scores for unsupported claims, fabricated citations, universal language. Emit EpistemicLedgerV3. No high-stakes output may pass v3.0 without claim classification.

2.8 Pass 6 — Sentence Surgery

Read references/compiler/prose_compiler_v3.md. Apply hard bans, soft bans, earned exceptions. Inject variance. Compress without loss. Track every transformation in SentenceSurgeryLogV3. Every cut, strengthening, and preservation is recorded.

2.9 Pass 7 — Voice Restoration

Read references/voiceprints/voice_fingerprint_engine.md + the applicable voiceprint. Measure baseline: avg sentence length, variance, compression, abstraction tolerance, metaphor density, question frequency, transition habits, dominant syntactic structures. Detect drift. Restore fingerprint. Emit VoiceMatchReportV3 showing whether fidelity increased or decreased.

2.10 Pass 8 — Genre & Arena Alignment

Read references/compiler/arena_delivery.md + each active pack from references/genre_packs/. Resolve genre collisions per references/diagnostics/genre_collision_matrix.md. Output as memo, grant response, sermon, caption, article, chapter, email, pitch slide, YouTube script, newsletter, government brief, SOP, speech, landing page. Enforce channel constraints. Emit ArenaAlignmentV3.

2.11 Pass 9 — Adversarial Stress Battery

Interrogate:

1. What would a skeptical, smart reader attack first?
2. What sentence could appear in any AI output?
3. What could be cut without losing meaning?
4. What line actually lands?
5. Does the opening earn the next 30 seconds?
6. Does the closing leave residue?
7. Is there a single sentence a human would never write this way?
8. (Narrative) Would a reader turn the page?
9. (Narrative) Does the final image burn?
10. (Dialogue) Can you tell who's speaking with names removed?
11. (High-stakes) What is the worst-faith reading of the strongest claim?
12. (Detector) Could a detector flag any passage on cadence alone?

Emit StressBatteryV3.

2.12 Pass 10 — Score & Delivery Packaging

Apply all applicable scorecards (see Section 4). Bundle outputs per Pass 0 contract: clean / annotated / redline / scorecard / violations / scene-audit / epistemic-ledger / next-pass. Emit DeliveryBundleV3.

2.13 Pass 11 — Memory & Benchmark Update

Update project memory (references/compiler/memory_system.md). Append benchmark result. Run regression matrix against prior version. If quality dropped > 3 points on any case, log to tests/regression_matrix.md and surface for review. Emit MemoryBenchmarkUpdateV3.

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3. The 12 Engines of v3.0

#	Engine	Purpose	Primary Reference
1	Intake Contract Engine	Convert every request into a governed task object	references/compiler/intake_contract.md
2	Corpus Governance Engine	Prevent source confusion and hallucinated context	references/compiler/corpus_governance.md
3	Voice Fingerprint Engine	Upgrade voiceprints into measurable authorial profiles	references/voiceprints/voice_fingerprint_engine.md
4	Genre Stack Engine	Allow multiple packs to operate without collision	references/compiler/genre_stack_engine.md
5	Architecture Graph Engine	Explicit graphs for sections, scenes, chapters, arguments	references/compiler/architecture_graph.md
6	Epistemic Ledger Engine	Make factual integrity a first-class primitive	references/compiler/epistemic_ledger.md
7	Prose Compiler Engine	Testable sentence and paragraph rewriting	references/compiler/prose_compiler_v3.md
8	Narrative Intelligence Engine	Storyworld memory, series arcs, continuity	references/compiler/narrative_intelligence_engine.md
9	Arena Delivery Engine	Format for the exact arena where it must win	references/compiler/arena_delivery.md
10	Benchmark & Regression Engine	Prove the system improves over time	benchmarks/README.md
11	Agent Orchestration Engine	Decompose the compiler into specialist agents	agents/README.md
12	Certification & Governance Engine	Turn open-source repo into trusted ecosystem	governance/ + certification/

---

4. Scoring Systems (v3.0)

v3.0 preserves and extends the seven v2.0 rubrics, then adds a v3-grade composite.

System	Points	Scope
Prose Quality	100	Clarity, specificity, rhythm, voice, argument, evidence, density, audience, memorability, structure
Chapter Construction	100	Setting, props, tension, power, pacing, foreshadowing, roles, identity, fatal detail, aftermath
Dialogue	100	Voice distinction, subtext, tension, rhythm, conflict, attribution, compression, exposition, silence, memorability
Power Dynamics	100	Power object, dual-purpose objects, consumption, spatial coding, gesture warfare, environment
Tension Mechanics	100	Compression model, false relief, fatal detail, silence, psychological warfare, atmosphere
Thriller Scene	100	Confined space, cold open, five beats, the turn, the button, violence, WWGW progression
Transmedia	100	Voice consistency, canon integrity, standalone quality, cross-platform integration
Epistemic Integrity (v3.0)	100	Claim classification coverage, source verification rate, citation honesty, universal-quantifier discipline, hallucination resistance
Arena Fit (v3.0)	100	Channel constraint compliance, audience calibration, format integrity, CTA discipline, readability
v3.0 Composite	1000	Weighted sum of applicable systems

Grade Thresholds (per 100-point system):

• Below 70 — Weak: significant revision required
• 70–79 — Usable but soft: tighten argument and voice
• 80–89 — Strong: publishable with minor polish
• 90–94 — Elite: distinctive, defensible, memorable
• 95–100 — Signature-grade: this could only have come from this author

Automatic Fail Conditions (score capped at 65 regardless of other marks):

• 3+ hard-ban phrases detected
• Perplexity flatness across 5+ consecutive sentences
• Zero domain-specific vocabulary in 500+ words
• Argument contains unsupported universal claim
• Fabricated citation, statistic, or quote
• (v3.0) Any claim in a high-stakes domain not classified by the Epistemic Ledger
• (v3.0) Channel constraint violation in a packaged delivery bundle

---

5. The Writing Board — 12 Specialist Agents

v3.0 decomposes the kernel into a coordinated multi-agent writing board. Each agent owns one job and emits one artifact. The board runs as one skill or as a multi-agent orchestration. Read agents/agent_manifest.yaml for the canonical roster.

#	Agent	Job	Artifact
1	Intake Architect	Translate request into governed contract	Intake contract
2	Corpus Auditor	Map allowed sources, prevent blending	Corpus map
3	Voice Fingerprinter	Identify target voice, measure drift	Voice report
4	Genre Marshal	Choose genre stack, weight conflicts	Genre matrix
5	Structure Engineer	Build section / scene / argument plan	Architecture graph
6	Evidence Prosecutor	Attack unsupported claims, enforce sources	Epistemic ledger
7	Sentence Surgeon	Repair prose without flattening voice	Rewrite log
8	Dialogue Commander	Fix conversation, subtext, tension	Dialogue stress report
9	Narrative Architect	Audit storyworld, chapter, arc, series	Narrative report
10	Stress Tester	Adversarial battery: reader / editor / skeptic / detector	Stress battery
11	Scorekeeper	Score all applicable rubrics	Scorecard
12	Delivery Packager	Format final assets to arena spec	Delivery bundle

5.1 Orchestration Rules

• Intake Architect always runs first.
• Corpus Auditor always runs when sources matter.
• Evidence Prosecutor always runs in academic / medical / legal / government / grant / financial / high-stakes work.
• Narrative Architect runs only for fiction / story / screenplay / scene / lore / transmedia / chapter work.
• Scorekeeper cannot override Evidence Prosecutor's cap rules.
• Delivery Packager cannot invent content; it formats approved content only.

5.2 Conflict Resolution

Conflict	Winner
User constraint vs. auto-detected genre	User constraint
Evidence integrity vs. persuasive force	Evidence integrity
Voice fidelity vs. factual clarity	Factual clarity in high-stakes domains; voice fidelity elsewhere
Compression vs. required compliance content	Compliance content
Drama vs. story continuity	Story continuity
CTA force vs. trust preservation	Trust preservation

---

6. Genre Packs (26 Total in v3.0)

Preserved from v2.0 (16): strategy, fiction, sales, academic, speech, sermon, email, pitch_deck, legal_positioning, cinematic_narration, dialogue, government_brief, medical_writing, patent_claims, thriller_scene_architecture, transmedia_character.

New in v3.0 (10):

Pack	Why It Matters	Core Rules
grant_nofo.md	High-value, complex, evidence-heavy	Compliance matrix, funder language, outcome logic, budget narrative alignment
technical_documentation.md	Developer adoption	Procedural clarity, examples, API structure, error-state documentation
journalism.md	Public trust, narrative nonfiction	Source discipline, nut graf, scene/reporting balance, quote handling
resume_cover_letter.md	Mass-market utility	Evidence of impact, role fit, ATS clarity, achievement compression
social_media.md	Distribution engine	Platform cadence, hook variants, proof compression, CTA discipline
youtube_script.md	Creator utility	Retention hooks, beat pacing, verbal clarity, open loops
newsletter.md	Audience ownership	Recurring sections, voice consistency, scannability, argument flow
real_estate.md	Professional vertical	Listing copy, investor memo, buyer education, local proof
loan_officer.md	Professional vertical	Trust, compliance-safe clarity, borrower education, rate/term precision
church_leadership.md	Mission vertical	Sermon, study guide, devotional, announcement, pastoral care tone
small_business_operator.md	Core user base	Offer clarity, customer journey, proof, local-market persuasion

Each v3.0 pack obeys the Domain Pack Schema: purpose → when to use → when not to use → audience model → required evidence → forbidden claims → voice weighting → structure templates → scoring adjustments → failure modes → before/after examples → stress tests → delivery formats → schema hooks → benchmark cases.

---

7. Voiceprint System (v3.0 Measurable)

Read references/voiceprints/voice_fingerprint_engine.md. The v3.0 fingerprint upgrades voiceprints from descriptive docs into measurable authorial profiles.

Measured dimensions:

• Average sentence length and variance
• Compression ratio (words removed without meaning loss)
• Abstraction tolerance (% of sentences operating above concrete plane)
• Metaphor density (per 500 words)
• Question frequency
• Transition habits (top-5 transition words)
• Opening pattern repertoire
• Closing pattern repertoire
• Dominant syntactic structures
• Authority posture (warmth/dominance dial)

Available voiceprints (preserved): sovereign_commander, literary_recursive, sermon_black_church, investor_precision, founder_manifesto, academic_rigorous, casual_sharp, custom.

New in v3.0: courageous_builder.md — pattern for branded operator personas (Grace, founder assistants, ministry assistants, sales assistants, grant assistants, vertical bots).

---

8. Machine-Readable Schemas (11 Schemas)

v3.0's most important technical leap. Every pass output is also a JSON object.

Schema	Purpose
intake_contract.schema.json	Formalize user request, constraints, mode, output
corpus_map.schema.json	Track allowed sources and source priority
voice_fingerprint.schema.json	Store measurable voice features
genre_stack.schema.json	Active genre packs and weights
architecture_graph.schema.json	Section / scene / claim / evidence nodes
epistemic_ledger.schema.json	Factual status and citation risk
prose_rewrite_log.schema.json	Sentence transformation log
storyworld_memory.schema.json	Continuity for longform fiction
delivery_bundle.schema.json	Final output assets
benchmark_result.schema.json	Regression and quality deltas
agent_task.schema.json	Multi-agent orchestration

Schemas live in schemas/. They unlock: CLI execution, MCP server execution, web app integration, CI writing checks, automated scoring, benchmark reports, issue templates, standard contribution tests, reproducible outputs, traceable quality improvement.

---

9. Rewrite Operators (24 in v3.0)

Preserved from v2.0 (19) + 5 new in v3.0:

Operator	Effect
compress(N%)	Reduce word count by N% without losing meaning
raise_intelligence	Increase sophistication without jargon
add_specificity	Replace abstractions with actors, numbers, examples
abstract_to_scene	Convert conceptual passage into grounded narrative
sharpen_thesis	Make core claim precise and defensible
strip_corporate	Remove institutional voice patterns
make_colder / make_warmer	Adjust warmth/dominance dial
make_executable	Convert insight into action steps
genre_transfer(from, to)	Rewrite in target genre, preserve content
audience_shift(from, to)	Adjust register for different reader
inject_variance	Add sentence-length and vocabulary unpredictability
kill_padding	Remove every sentence not advancing the argument
strengthen_closing	Rewrite final paragraph for maximum residue
scene_audit	Run chapter construction checklist
role_audit	Map every character to structural archetype
dialogue_stress_test	Score dialogue against 9 elements + 22 techniques
power_map	Track power object migration
plant_audit	Verify foreshadowing plants and payoffs
intake_contract (v3.0)	Emit governed task object from chaotic request
corpus_audit (v3.0)	Map allowed sources, flag stale/contradictory
epistemic_classify (v3.0)	Tag every claim with type + source status
voice_fingerprint (v3.0)	Emit measurable voice profile + drift report
arena_repackage (v3.0)	Convert approved content to target arena format
benchmark_run (v3.0)	Run regression against prior version

---

10. File Reference Map (v3.0)

When this skill triggers, read files in this order based on task:

1. Always: This SKILL.md
2. Always: references/anti_patterns/phrases.md
3. Pass 0: references/compiler/intake_contract.md
4. Pass 2: references/compiler/corpus_governance.md
5. Pass 3: references/anti_patterns/structures.md + cadence.md + fake_depth.md
6. Pass 4 (general): references/compiler/architecture_graph.md
7. Pass 4 (persuasive): references/compiler/argument_graph.md
8. Pass 4 (narrative): references/compiler/scene_graph.md
9. Pass 5: references/compiler/epistemic_ledger.md
10. Pass 6: references/compiler/prose_compiler_v3.md + references/positive_patterns/paragraph_shapes.md
11. Pass 7: references/voiceprints/voice_fingerprint_engine.md + applicable voiceprint
12. Pass 8 (general): references/compiler/arena_delivery.md
13. Pass 8 (mixed genre): references/diagnostics/genre_collision_matrix.md
14. Pass 9: tests/adversarial_cases.md
15. Pass 10: references/diagnostics/scorecard.md
16. Pass 11: references/compiler/memory_system.md + benchmarks/runbook.md
17. Fiction: references/compiler/narrative_intelligence_engine.md + storyworld_memory.md + chapter_construction.md + character_role_archetypes.md
18. Thriller: above + references/genre_packs/thriller_scene_architecture.md + references/positive_patterns/tension_mechanics.md
19. Dialogue: references/genre_packs/dialogue.md
20. Grant / NOFO: references/genre_packs/grant_nofo.md + Pass 5 + Pass 8
21. Technical docs: references/genre_packs/technical_documentation.md
22. Journalism: references/genre_packs/journalism.md + Pass 5
23. Social media: references/genre_packs/social_media.md + Pass 8
24. YouTube script: references/genre_packs/youtube_script.md + Pass 8
25. Newsletter: references/genre_packs/newsletter.md
26. Resume / cover letter: references/genre_packs/resume_cover_letter.md
27. Real estate: references/genre_packs/real_estate.md
28. Loan officer: references/genre_packs/loan_officer.md + Pass 5
29. Church leadership: references/genre_packs/church_leadership.md + sermon.md
30. Small business operator: references/genre_packs/small_business_operator.md
31. Custom persona: references/voiceprints/courageous_builder.md
32. Schemas: schemas/*.schema.json for machine-readable execution
33. Agent execution: agents/agent_manifest.yaml + applicable agent docs
34. Benchmark: benchmarks/benchmark_manifest.yaml
35. Certification: certification/operator_levels.md

---

11. Output Modes (v3.0)

Default output is clean. Pass 0 contract may request any combination:

• clean — final draft, no markup
• annotated — draft with margin notes explaining decisions
• redline — original with tracked changes
• scorecard — full evaluation (human + JSON)
• violations — every rule triggered and how resolved
• next-pass — recommendations for further improvement
• scene-audit — chapter construction scorecard (narrative)
• epistemic-ledger (v3.0) — claim classification with source status
• delivery-bundle (v3.0) — packaged for target arena (memo / grant / social / YouTube / etc.)
• voice-drift-report (v3.0) — fingerprint baseline vs. current
• benchmark-result (v3.0) — regression vs. prior version

---

12. Epistemic Integrity Layer (v3.0 Hardened)

Every draft classifies sentences as: observed fact / sourced fact / inference / synthesis / recommendation / rhetoric.

Enforcement rules:

• Sourced facts require citations.
• Inferences must identify their premises.
• Recommendations must state the basis.
• Rhetoric must not masquerade as fact.
• Universal quantifiers (all, every, never, always) require evidence or qualification.
• Inflated verbs (revolutionize, transform, redefine) require concrete backing.
• No fabricated citations, statistics, quotes, or studies — ever.
• (v3.0) Every high-stakes domain (academic, medical, legal, government, grant, financial) MUST emit EpistemicLedgerV3.
• (v3.0) Source status flags: verified, user-provided, assumed, inferred, missing, unsafe. Any unsafe flag halts delivery.

---

13. Memory and Continuity (Longform)

For multi-chapter or multi-document projects, read references/compiler/memory_system.md and references/compiler/storyworld_memory.md. Track:

• Character voice continuity
• Thesis continuity
• Repeated metaphor detection
• Cross-section contradictions
• Emotional arc continuity
• Terminology lock (same concept = same word)
• Character role consistency (archetype doesn't shift without cause)
• Power object tracking across chapters
• Foreshadowing ledger (planted / paid off / orphaned)
• (v3.0) Storyworld canon hierarchy (canonical / sanctioned / fan-tier)
• (v3.0) Series escalation curve (does each book raise stakes or repeat?)
• (v3.0) Cross-book voice fingerprint stability

---

14. Benchmark Discipline

Read benchmarks/README.md, benchmark_manifest.yaml, runbook.md. v3.0 ships with 60 benchmark cases across 12 categories. A release cannot ship until it passes benchmark thresholds:

Gate	Requirement
Score improvement	v3 output beats v2 baseline by 5+ points on 70%+ of cases
No regression	No case drops more than 3 points without documented reason
Evidence safety	100% of fabricated-source traps must be flagged
Voice preservation	Voice drift cases identify correct direction 80%+ of time
Genre collision	Mixed-genre tasks produce declared genre stack
Narrative audit	Story cases identify dead props, flat setting, missing payoff
Output packaging	Every benchmark produces valid delivery bundle

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15. The v3.0 Vow

Writing Intelligence v1.0 proved AI-sounding writing could be defeated by compilation instead of cosmetic cleanup.

Writing Intelligence v2.0 proved fiction could be engineered as a living architecture.

Writing Intelligence v3.0 proves something larger:

Authorship can be governed without being flattened. Voice can be preserved while evidence is audited. Creativity can be systematized without becoming sterile. Language can be scored without becoming soulless. And writing can become infrastructure.

That is the category. That is the moat. That is the release.

— Antonio T. Smith Jr. / Density6 LLC