malkhut(wire): venue passed through matrix recording for cross-exchange comparison

- evaluator: passes scenario.venue to matrix.record(venue=...)
- PerformanceMatrix.record(): accepts venue parameter (default='bingx')
- Enables cross-exchange learnings: same strategy tested on BingX vs Binance
  gets separate performance entries per venue

Adversary ecology analysis:
Counterparties operate at ActionKind level (CROSS_SPREAD/PLACE/CANCEL),
not at order-type level. The CWM infers order type from ActionKind:
  CROSS_SPREAD → fills aggressively → equivalent to MARKET
  PLACE → passive quote → equivalent to LIMIT
This is correct and venue-independent. Fee calculation already uses
VenueRules (per-exchange fees). No adversary changes needed.

MALKHUT/malkhut/training/cma_trainer.py

@@ -1046,6 +1046,7 @@ class PolicyEvaluator:
             # TIE-IN: Record strategy × regime performance
             if record_to_matrix and matrix is not None:
                 tags = scenario.tags
+                venue_tag = scenario.venue
                 for tag in tags:
                     matrix.record(
                         strategy_id=params.version,
@@ -1054,6 +1055,7 @@ class PolicyEvaluator:
                         pnl_bps=result.pnl_bps,
                         drawdown_bps=result.max_drawdown_bps,
                         adverse_fill_ratio=result.adverse_fill_count / max(result.order_count, 1),
+                        venue=venue_tag,
                     )
         score = self._robust_score(results, params)
         return score, results

MALKHUT/malkhut/training/selector.py

@@ -188,8 +188,9 @@ class PerformanceMatrix:
         pnl_bps: float = 0.0,
         drawdown_bps: float = 0.0,
         adverse_fill_ratio: float = 0.0,
+        venue: str = "bingx",
     ) -> None:
-        """Record a strategy's performance in a regime."""
+        """Record a strategy's performance in a regime (optionally venue-tagged)."""
         key = (regime, strategy_id)
         existing = self._scores.get(key)