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/probe/merge_dupes.py

@@ -0,0 +1,38 @@
+"""Near-duplicate situations among accepted clusters (SELECTION.md protocol step 6).
+
+  python3 merge_dupes.py dev            # list every accepted pair's centroid cosine, with label names
+  python3 merge_dupes.py test 0.93      # merge pairs at or above a threshold chosen on dev
+
+Centroids are the mean unit summary vector of each cluster. On dev the threshold is chosen by
+reading: the lowest cosine that still separates pairs whose names say "same situation" from pairs
+that do not. On test it is applied as given, and each merge is reported with both names so it can
+be checked.
+"""
+import json, pathlib, sys
+
+set_name = sys.argv[1]
+threshold = float(sys.argv[2]) if len(sys.argv) > 2 else None
+
+sys.argv = ['measure.py', 'summary_embeddings.json']
+exec(pathlib.Path('measure.py').read_text(encoding='utf-8').split("print(f'{path.name}")[0])
+sys.argv = ['select_rule.py']
+exec(pathlib.Path('select_rule.py').read_text(encoding='utf-8').split("mode = sys.argv")[0])
+
+candidates = json.loads(pathlib.Path(f'candidates-{set_name}.json').read_text())
+frozen = json.loads(pathlib.Path('rule-frozen.json').read_text())
+terms = [tuple(t) for t in frozen['terms']]
+rows = {r['id']: r for r in load(set_name)}
+accepted = [cid for cid, r in rows.items() if all(passes(r, t) for t in terms)]
+
+cent = {cid: norm([sum(V[i][d] for i in candidates[cid]) / len(candidates[cid]) for d in range(dim)])
+        for cid in accepted}
+pairs = sorted(((dot(cent[a], cent[b]), a, b) for x, a in enumerate(accepted) for b in accepted[x + 1:]),
+               reverse=True)
+
+print(f'{set_name}: {len(accepted)} accepted clusters, {len(pairs)} pairs\n')
+for cos, a, b in pairs[:25]:
+    mark = '  MERGE' if threshold is not None and cos >= threshold else ''
+    print(f"{cos:.4f}  {a}({rows[a]['label']}) {rows[a]['name'] or '-'}\n        {b}({rows[b]['label']}) {rows[b]['name'] or '-'}{mark}")
+if threshold is not None:
+    merged = [(a, b) for cos, a, b in pairs if cos >= threshold]
+    print(f'\nthreshold {threshold}: {len(merged)} merges')