Switch compare to discrete verdicts + granular pose axes + per-axis definitions

The 4B's 0-1 scores were unreliable (identical ref/gen scored ~0.6), so the
judge now returns verdict match/partial/mismatch per axis; overall_score and a
new mismatch_count are computed from verdicts on our side (reliable, monotonic).
Expanded the action/pose cluster into position_name, body_orientation,
limb_arrangement, penetration, contact_points, genital_visibility (+ breast_size)
so explicit poses carry detail. Each axis now ships a one-line definition in the
prompt so gender_mix/subject_count stop absorbing positional text. 24 axes total.
Example workflows use the node default (axes=''). Docs realigned; stop condition
is now mismatch_count==0.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

docs/AGENT_LOOP.md

@@ -59,9 +59,10 @@ Stdout (captured by the agent) is the report:
 {
   "run_tag": "iter003",
   "overall_score": 0.62,
+  "mismatch_count": 1,
   "axes": {
-    "position":       {"score": 0.40, "ref": "doggy style", "gen": "missionary"},
-    "clothing_state": {"score": 0.85, "ref": "red lace lingerie", "gen": "plain bra"}
+    "position_name":  {"verdict": "mismatch", "ref": "doggy style", "gen": "cowgirl"},
+    "clothing_state": {"verdict": "partial",  "ref": "red lace lingerie", "gen": "plain bra"}
   },
   "prompt_used": "...",
   "_prompt_id": "…", "_report_path": "…/calib_iter003.json"