Add story-to-pack research and a structured situation review

Research toward building a content pack from a story corpus, kept on its own
branch and independent of the game. Records the selection experiments against
blind labels, and settles selection as gate G2 followed by a human review:
review.py writes REVIEW.md and a review.json form, apply_review.py checks the
filled form and writes situations.json for the next stage.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01C6UDQ9o6L6Ey173U7XVou6

tools/story-to-pack/recovered/chunk.py

@@ -0,0 +1,26 @@
+"""Cut stories into scene-sized chunks on paragraph boundaries."""
+import json, pathlib, re
+
+TARGET = 320   # words; a scene is a situation with people in it
+
+stories = json.loads(pathlib.Path('stories.json').read_text(encoding='utf-8'))
+chunks = []
+for si, s in enumerate(stories):
+    paras = [p.strip() for p in re.split(r'\n\s*\n', s['text']) if p.strip()]
+    buf, n = [], 0
+    for p in paras:
+        w = len(p.split())
+        if n + w > TARGET and buf:
+            chunks.append({'story': si, 'title': s['title'], 'volume': s['volume'],
+                           'text': ' '.join(buf), 'words': n})
+            buf, n = [], 0
+        buf.append(p); n += w
+    if buf and n >= 80:
+        chunks.append({'story': si, 'title': s['title'], 'volume': s['volume'],
+                       'text': ' '.join(buf), 'words': n})
+
+pathlib.Path('chunks.json').write_text(json.dumps(chunks), encoding='utf-8')
+ws = sorted(c['words'] for c in chunks)
+print(f'chunks: {len(chunks)}  from {len(stories)} stories')
+print(f'words/chunk  min {ws[0]}  median {ws[len(ws)//2]}  max {ws[-1]}')
+print(f'total words: {sum(ws):,}')