malkhut: 3.5H instrumented E2E + calibrated slippage + conditional slippage

MALKHUT/malkhut/cwm/hft_cwm.py

@@ -503,7 +503,13 @@ class HftBacktestCWM:
                 if cumulative_usd >= new_fill_price * new_fill_qty:
                     break
             if cumulative_levels > 0:
-                expected_slippage_bps = cumulative_levels * 0.1  # ~0.1 bps per level consumed
+                # Calibrated slippage: per-asset model from VST data
+                from malkhut.training.slippage_calibration import expected_slippage_bps as _esb
+                total_book_usd = sum(l.price * l.qty for l in (book_depth or ()))
+                expected_slippage_bps = _esb(
+                    prev_state.venue.symbol, cumulative_levels,
+                    new_fill_price * new_fill_qty, total_book_usd,
+                )
 
         # Price improvement: how much better than best bid/ask?
         price_improvement_bps = 0.0