malkhut(wire): 5 risk gate stubs implemented + 3 scenarios behavior-driven

Risk gate (risk/gate.py) — 5 stubs implemented:

1. _kill_switch_active(): operator-controlled emergency stop via set_kill_switch()
2. _cancel_rate_would_exceed(): tracks cancel timestamps per symbol in 60s
   sliding window, blocks if >= MAX_CANCELS_PER_SYMBOL_PER_MINUTE
3. _would_self_trade(): checks open orders for same symbol+side at same price
   (within tick_size), skipping the cancel_order_id for CANCEL_REPLACE
4. _would_exceed_symbol_notional(): sums current open order notional + new
   order notional, blocks if > equity * MAX_SYMBOL_NOTIONAL_FRACTION
5. _violates_venue_minima(): checks tick alignment, lot rounding, min_qty,
   and min_notional — all float-robust comparisons

ScenarioFactory — 3 remaining hardcoded scenarios converted:

1. _spread_tightening: spread_mult=0.3, depth_fraction=1.0 (was hardcoded BTC)
2. _cross_venue_arb: spread_mult=0.5, depth_fraction=0.5 (was hardcoded BTC)
3. _cross_exchange_arb_stress: spread_mult=0.8, depth_fraction=0.3 (was hardcoded BTC)

All 30 scenarios now use _behavior_state() — zero hardcoded prices remain.

675 tests pass. Zero regressions.

MALKHUT/malkhut/risk/gate.py

@@ -1,11 +1,16 @@
 """
 Risk gate — final hard stop before venue execution.
 
-The planner is not trusted. The optimiser is not trusted. The exchange adapter
+The planner is not trusted. The optimiser is not trusted, the exchange adapter
 is not trusted. This gate enforces hard invariants.
 """
 from __future__ import annotations
 
+import time
+from collections import defaultdict
+from typing import Deque
+from collections import deque
+
 from malkhut.actions import FulfilmentAction, PlannedPolicy, RiskDecision
 from malkhut.state import (
     ActionKind,
@@ -13,12 +18,27 @@ from malkhut.state import (
     MarketWorldState,
     MAX_ACCOUNT_LEVERAGE,
     MAX_CANCELS_PER_SYMBOL_PER_MINUTE,
+    MAX_SYMBOL_NOTIONAL_FRACTION,
     Side,
 )
 from malkhut.cwm import materialize_price_from_action
 
 
 class RiskGate:
+    def __init__(self) -> None:
+        self._kill_switch: bool = False
+        self._cancel_timestamps: dict[str, Deque[float]] = defaultdict(
+            lambda: deque(maxlen=MAX_CANCELS_PER_SYMBOL_PER_MINUTE + 10)
+        )
+
+    def set_kill_switch(self, active: bool) -> None:
+        """Operator-controlled emergency stop."""
+        self._kill_switch = active
+
+    def record_cancel(self, symbol: str) -> None:
+        """Record a cancel event for rate-limit tracking."""
+        self._cancel_timestamps[symbol].append(time.time())
+
     def validate(
         self,
         state: MarketWorldState,
@@ -35,7 +55,6 @@ class RiskGate:
         """
         action = planned.selected_action
 
-        # DAAT OOD veto — highest priority
         if daat_verdict == "OUT_OF_DISTRIBUTION":
             return RiskDecision(True, None, "ood_veto_fall_back_to_doctrinal")
 
@@ -66,12 +85,38 @@ class RiskGate:
         return RiskDecision(True, action, "approved")
 
     def _kill_switch_active(self) -> bool:
-        return False
+        return self._kill_switch
 
     def _cancel_rate_would_exceed(self, state: MarketWorldState, action: FulfilmentAction) -> bool:
-        return False
+        if action.kind != ActionKind.CANCEL and action.kind != ActionKind.CANCEL_REPLACE:
+            return False
+        symbol = state.venue.symbol
+        now = time.time()
+        window = self._cancel_timestamps[symbol]
+        cutoff = now - 60.0
+        while window and window[0] < cutoff:
+            window.popleft()
+        return len(window) >= MAX_CANCELS_PER_SYMBOL_PER_MINUTE
 
     def _would_self_trade(self, state: MarketWorldState, action: FulfilmentAction) -> bool:
+        if action.kind not in (ActionKind.PLACE, ActionKind.CANCEL_REPLACE, ActionKind.CROSS_SPREAD):
+            return False
+        if action.side is None:
+            return False
+        for oo in state.open_orders:
+            if oo.symbol != state.venue.symbol:
+                continue
+            if oo.side != action.side:
+                continue
+            if oo.client_order_id == action.cancel_order_id:
+                continue
+            if oo.price is None or action.price_ticks_from_best is None:
+                continue
+            our_price = materialize_price_from_action(state, action)
+            if our_price is None:
+                continue
+            if abs(our_price - oo.price) < state.venue.tick_size:
+                return True
         return False
 
     def _would_exceed_leverage(
@@ -82,7 +127,19 @@ class RiskGate:
     def _would_exceed_symbol_notional(
         self, state: MarketWorldState, action: FulfilmentAction, params: FulfilmentPolicyParams,
     ) -> bool:
-        return False
+        if action.kind not in (ActionKind.PLACE, ActionKind.CANCEL_REPLACE, ActionKind.CROSS_SPREAD):
+            return False
+        price = materialize_price_from_action(state, action)
+        if price is None:
+            return False
+        qty = action.qty_fraction * state.account.available_balance / max(price, 1e-12)
+        order_notional = price * qty
+        max_notional = state.account.equity * MAX_SYMBOL_NOTIONAL_FRACTION
+        current_notional = 0.0
+        for oo in state.open_orders:
+            if oo.symbol == state.venue.symbol and oo.price is not None:
+                current_notional += oo.price * oo.remaining_qty
+        return (current_notional + order_notional) > max_notional
 
     def _post_only_would_cross(self, state: MarketWorldState, action: FulfilmentAction) -> bool:
         if not action.post_only:
@@ -97,4 +154,25 @@ class RiskGate:
         return False
 
     def _violates_venue_minima(self, state: MarketWorldState, action: FulfilmentAction) -> bool:
+        if action.kind not in (ActionKind.PLACE, ActionKind.CANCEL_REPLACE):
+            return False
+        price = materialize_price_from_action(state, action)
+        if price is None:
+            return False
+        if price <= 0:
+            return True
+        tick = state.venue.tick_size
+        if tick > 0:
+            remainder = price % tick
+            if remainder > 1e-9 and tick - remainder > 1e-9:
+                return True
+        qty = action.qty_fraction * state.account.available_balance / max(price, 1e-12)
+        lot = state.venue.lot_size
+        if lot > 0 and qty > 0:
+            rounded = round(qty / lot) * lot
+            if rounded < state.venue.min_qty:
+                return True
+        notional = price * qty
+        if notional < state.venue.min_notional:
+            return True
         return False

MALKHUT/malkhut/training/cma_trainer.py

@@ -645,7 +645,7 @@ class ScenarioFactory:
         return Scenario(
             scenario_id=f"tighten_{symbol}_{seed}",
             symbol=symbol,
-            initial_state=self._make_state(symbol, bid=49950.0, ask=50050.0, bid_qty=2.0, ask_qty=2.0, exchange_id=self.exchange_id),
+            initial_state=self._behavior_state(symbol, spread_mult=0.3, depth_fraction=1.0, exchange_id=self.exchange_id),
             counterparties=self.counterparties,
             max_steps=steps,
             tags=("spread_tightening", "competition"),
@@ -726,7 +726,7 @@ class ScenarioFactory:
         return Scenario(
             scenario_id=f"arb_{symbol}_{seed}",
             symbol=symbol,
-            initial_state=self._make_state(symbol, bid=49990.0, ask=50010.0, bid_qty=0.5, ask_qty=0.5, exchange_id=self.exchange_id),
+            initial_state=self._behavior_state(symbol, spread_mult=0.5, depth_fraction=0.5, exchange_id=self.exchange_id),
             counterparties=(LatencyArbPolicy(lead_threshold=0.3), ToxicTakerPolicy(sensitivity=0.4)),
             max_steps=steps,
             tags=("arbitrage", "cross_venue", "price_discovery"),
@@ -834,7 +834,7 @@ class ScenarioFactory:
         return Scenario(
             scenario_id=f"arb_stress_{symbol}_{seed}",
             symbol=symbol,
-            initial_state=self._make_state(symbol, bid=49980.0, ask=50020.0, bid_qty=0.3, ask_qty=0.3, exchange_id=self.exchange_id),
+            initial_state=self._behavior_state(symbol, spread_mult=0.8, depth_fraction=0.3, exchange_id=self.exchange_id),
             counterparties=(LatencyArbPolicy(lead_threshold=0.2), ToxicTakerPolicy(sensitivity=0.4)),
             max_steps=steps,
             tags=("cross_exchange", "arb_stress", "price_discovery"),