fix: enable intra-day position tracking for sell-then-buy trades

Resolves issue where sell proceeds were not immediately available for
subsequent buy orders within the same trading session.

Problem:
- Both buy() and sell() independently queried database for starting position
- Multiple trades within same day all saw pre-trade cash balance
- Agents couldn't rebalance portfolios (sell + buy) in single session

Solution:
- ContextInjector maintains in-memory position state during trading session
- Position updates accumulate after each successful trade
- Position state injected into buy/sell via _current_position parameter
- Reset position state at start of each trading day

Changes:
- agent/context_injector.py: Add position tracking with reset_position()
- agent_tools/tool_trade.py: Accept _current_position in buy/sell functions
- agent/base_agent/base_agent.py: Reset position state daily
- tests: Add 13 comprehensive tests for position tracking

All new tests pass. Backward compatible, no schema changes required.

agent/base_agent/base_agent.py

@@ -533,6 +533,8 @@ Summary:"""
         # Update context injector with current trading date
         if self.context_injector:
             self.context_injector.today_date = today_date
+            # Reset position state for new trading day (enables intra-day tracking)
+            self.context_injector.reset_position()
 
         # Clear conversation history for new trading day
         self.clear_conversation_history()

agent/context_injector.py

@@ -3,15 +3,22 @@ Tool interceptor for injecting runtime context into MCP tool calls.
 
 This interceptor automatically injects `signature` and `today_date` parameters
 into buy/sell tool calls to support concurrent multi-model simulations.
+
+It also maintains in-memory position state to track cumulative changes within
+a single trading session, ensuring sell proceeds are immediately available for
+subsequent buy orders.
 """
 
-from typing import Any, Callable, Awaitable
+from typing import Any, Callable, Awaitable, Dict, Optional
 
 
 class ContextInjector:
     """
     Intercepts tool calls to inject runtime context (signature, today_date).
 
+    Also maintains cumulative position state during trading session to ensure
+    sell proceeds are immediately available for subsequent buys.
+
     Usage:
         interceptor = ContextInjector(signature="gpt-5", today_date="2025-10-01")
         client = MultiServerMCPClient(config, tool_interceptors=[interceptor])
@@ -34,6 +41,13 @@ class ContextInjector:
         self.job_id = job_id
         self.session_id = session_id  # Deprecated but kept for compatibility
         self.trading_day_id = trading_day_id
+        self._current_position: Optional[Dict[str, float]] = None
+
+    def reset_position(self) -> None:
+        """
+        Reset position state (call at start of each trading day).
+        """
+        self._current_position = None
 
     async def __call__(
         self,
@@ -43,6 +57,9 @@ class ContextInjector:
         """
         Intercept tool call and inject context parameters.
 
+        For buy/sell operations, maintains cumulative position state to ensure
+        sell proceeds are immediately available for subsequent buys.
+
         Args:
             request: Tool call request containing name and arguments
             handler: Async callable to execute the actual tool
@@ -62,5 +79,18 @@ class ContextInjector:
             if self.trading_day_id:
                 request.args["trading_day_id"] = self.trading_day_id
 
+            # Inject current position if we're tracking it
+            if self._current_position is not None:
+                request.args["_current_position"] = self._current_position
+
         # Call the actual tool handler
-        return await handler(request)
+        result = await handler(request)
+
+        # Update position state after successful trade
+        if request.name in ["buy", "sell"]:
+            # Check if result is a valid position dict (not an error)
+            if isinstance(result, dict) and "error" not in result and "CASH" in result:
+                # Update our tracked position with the new state
+                self._current_position = result.copy()
+
+        return result