story.py — create_chapter_plan():
- TARGET_CHAPTERS is now a guideline (±15%) not a hard constraint; the AI
can produce a count that fits the story rather than forcing a specific number
- Word scaling is now pacing-aware instead of uniform: Very Fast ≈ 60% of avg,
Fast ≈ 80%, Standard ≈ 100%, Slow ≈ 125%, Very Slow ≈ 150%
- Two-pass normalisation: pacing weights applied first, then the total is
nudged to the word target — natural variation preserved throughout
- Variance range tightened to ±8% (was ±10%) for more predictable totals
- Prompt now tells the AI that estimated_words should reflect pacing rhythm
story.py — expand():
- Added event ceiling (target_chapters × 1.5): if the outline already has
enough beats, the pass switches from "add events" to "enrich descriptions"
— prevents over-dense outlines for short stories and flash fiction
- Task instruction is dynamically chosen: add-events vs deepen-descriptions
- Clarified that original user beats must be preserved but new events must
each be distinct and spread evenly (not front-loaded)
story.py — refinement loop:
- Word count constraint softened from hard "do not condense" to
"~N words ±20% acceptable if the scene demands it" so action chapters
can run short and introspective chapters can run long naturally
main.py — bridge chapter insertion:
- Removed hardcoded 1500-word estimate for dynamically inserted bridge
chapters; now computes the average estimated_words from the current
chapter plan so bridge chapters match the book's natural chapter length
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
story.py — write_chapter():
- Added POSITION context ("Chapter N of Total") so the AI calibrates narrative
tension correctly (setup vs escalation vs climax/payoff)
- Moved PACING_GUIDE to sit directly after PACING metadata instead of being
buried after 13 quality criteria items where the AI rarely reads it
- Removed duplicate pacing descriptions that appeared after QUALITY_CRITERIA
story.py — refinement loop:
- Capped critique history to last 2 entries (was accumulating all previous
attempts, wasting tokens and confusing the model on attempt 4-5)
- Added TARGET_WORDS and BEATS constraints to the refinement prompt to prevent
chapters from shrinking or losing plot beats during editing passes
- Restructured refinement prompt with explicit HARD_CONSTRAINTS section
story.py — check_and_propagate():
- Increased chapter context from 5000 to 12000 chars for continuity rewrites
(was asking for a full chapter rewrite but only providing a fragment)
- Added explicit word count target to rewrite so chapters are not truncated
- Added conservative decision bias: only rewrite on genuine contradictions
story.py — plan_structure():
- Now passes TARGET_CHAPTERS, TARGET_WORDS, GENRE, and CHARACTERS to the
structure AI — it was planning blindly without knowing the book's scale
marketing.py — generate_blurb():
- Rewrote prompt with 4-part structure: Hook → Stakes → Tension → Close
- Formats plot beats as a readable list instead of raw JSON array
- Extracts protagonist automatically for personalised blurb copy
- Added genre-tone matching, present-tense voice, and no-spoiler rule
marketing.py — generate_cover():
- Added genre-to-visual-style mapping (thriller → cinematic, fantasy → epic
digital painting, romance → painterly, etc.)
- Art prompt instructions now enforce: no text/letters/watermarks, rule-of-thirds
composition, explicit focal point, lighting description, colour palette
- Replaced generic image evaluation with a 5-criteria book-cover rubric:
visual impact, genre fit, composition, quality, and clean image (no text)
- Score penalties: -3 for visible text/watermarks, -2 for blur/deformed anatomy
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
