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>
Mike Wichers
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