feat: Improve revision pipeline quality — 6 targeted enhancements (v3.1)

1. editor.py — Fix rewrite_chapter_content to use model_writer (was model_logic).
   Chapter rewrites now use the creative writing model, not the cheaper analysis model.

2. editor.py — evaluate_chapter_quality now uses keep_head=True so the evaluator
   sees the chapter opening (engagement hook, sensory anchoring) as well as the
   ending; long chapters no longer scored on tail only.

3. editor.py — Consistency analysis sampling upgraded to head+middle+tail (was
   head+tail), giving the LLM a complete view of each chapter's events.

4. writer.py — max_attempts is now adaptive: climax/resolution chapters
   (position >= 0.75) receive 3 refinement attempts; others keep 2.

5. writer.py — Polish-skip threshold tightened from 0.012 to 0.008 (1 filter
   word per 125 words vs. 1 per 83 words), so more borderline drafts are cleaned.

6. style_persona.py — Persona validation sample increased from 200 to 400 words
   for more reliable voice quality assessment.

Version bumped: 3.0 → 3.1

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

story/editor.py

@@ -67,7 +67,7 @@ def evaluate_chapter_quality(text, chapter_title, genre, model, folder, series_c
     }}
     """
     try:
-        response = model.generate_content([prompt, utils.truncate_to_tokens(text, 7500)])
+        response = model.generate_content([prompt, utils.truncate_to_tokens(text, 7500, keep_head=True)])
         model_name = getattr(model, 'name', ai_models.logic_model_name)
         utils.log_usage(folder, model_name, response.usage_metadata)
         data = json.loads(utils.clean_json(response.text))
@@ -129,7 +129,13 @@ def analyze_consistency(bp, manuscript, folder):
     chapter_summaries = []
     for ch in manuscript:
         text = ch.get('content', '')
-        excerpt = text[:1000] + "\n...\n" + text[-1000:] if len(text) > 2000 else text
+        if len(text) > 3000:
+            mid = len(text) // 2
+            excerpt = text[:800] + "\n...\n" + text[mid - 200:mid + 200] + "\n...\n" + text[-800:]
+        elif len(text) > 1600:
+            excerpt = text[:800] + "\n...\n" + text[-800:]
+        else:
+            excerpt = text
         chapter_summaries.append(f"Ch {ch.get('num')}: {excerpt}")
 
     context = "\n".join(chapter_summaries)
@@ -236,8 +242,8 @@ def rewrite_chapter_content(bp, manuscript, chapter_num, instruction, folder):
     """
 
     try:
-        response = ai_models.model_logic.generate_content(prompt)
-        utils.log_usage(folder, ai_models.model_logic.name, response.usage_metadata)
+        response = ai_models.model_writer.generate_content(prompt)
+        utils.log_usage(folder, ai_models.model_writer.name, response.usage_metadata)
         try:
             data = json.loads(utils.clean_json(response.text))
             return data.get('content'), data.get('summary')

story/style_persona.py

@@ -121,7 +121,7 @@ def validate_persona(bp, persona_details, folder):
 
     sample_prompt = f"""
     ROLE: Fiction Writer
-    TASK: Write a 200-word opening scene that perfectly demonstrates this author's voice.
+    TASK: Write a 400-word opening scene that perfectly demonstrates this author's voice.
 
     AUTHOR_PERSONA:
     Name: {name}
@@ -131,7 +131,7 @@ def validate_persona(bp, persona_details, folder):
     TONE: {tone}
 
     RULES:
-    - Exactly ~200 words of prose (no chapter header, no commentary)
+    - Exactly ~400 words of prose (no chapter header, no commentary)
     - Must reflect the persona's stated sentence structure, vocabulary, and voice
     - Show, don't tell — no filter words (felt, saw, heard, realized, noticed)
     - Deep POV: immerse the reader in a character's immediate experience

story/writer.py

@@ -380,7 +380,7 @@ def write_chapter(chap, bp, folder, prev_sum, tracking=None, prev_content=None,
     _draft_word_list = current_text.lower().split() if current_text else []
     _fw_hit_count = sum(1 for w in _draft_word_list if w in _fw_set)
     _fw_density = _fw_hit_count / max(len(_draft_word_list), 1)
-    _skip_polish = _fw_density < 0.012  # < ~1 filter word per 83 words → draft already clean
+    _skip_polish = _fw_density < 0.008  # < ~1 filter word per 125 words → draft already clean
 
     if current_text and not _skip_polish:
         utils.log("WRITER", f"  -> Two-pass polish (Pro model, FW density {_fw_density:.3f})...")
@@ -427,8 +427,12 @@ def write_chapter(chap, bp, folder, prev_sum, tracking=None, prev_content=None,
     elif current_text:
         utils.log("WRITER", f"  -> Draft clean (FW density {_fw_density:.3f}). Skipping polish pass.")
 
-    # Reduced from 3 → 2 attempts since polish pass already refines prose before evaluation
-    max_attempts = 2
+    # Adaptive attempts: climax/resolution chapters (position >= 0.75) get 3 passes;
+    # earlier chapters keep 2 (polish pass already refines prose before evaluation).
+    if chapter_position is not None and chapter_position >= 0.75:
+        max_attempts = 3
+    else:
+        max_attempts = 2
     SCORE_AUTO_ACCEPT = 8
     # Adaptive passing threshold: lenient for early setup chapters, strict for climax/resolution.
     # chapter_position=0.0 → setup (SCORE_PASSING=6.5), chapter_position=1.0 → climax (7.5)