CLAUDE: Implement forced outcome feature for terminal client testing

Add ability to force specific play outcomes instead of random dice rolls,
enabling targeted testing of specific game scenarios.

Changes:
- play_resolver.resolve_play(): Add forced_outcome parameter, bypass dice
  rolls when provided, create dummy AbRoll with placeholder values
- game_engine.resolve_play(): Accept and pass through forced_outcome param
- terminal_client/commands.py: Pass forced_outcome to game engine

Testing:
- Verified TRIPLE, HOMERUN, and STRIKEOUT outcomes work correctly
- Dummy AbRoll properly constructed with all required fields
- Game state updates correctly with forced outcomes

Example usage in REPL:
  resolve_with triple
  resolve_with homerun

Fixes terminal client testing workflow to allow controlled scenarios.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

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

backend/app/core/game_engine.py

@@ -324,7 +324,7 @@ class GameEngine:
             logger.warning(f"Offensive decision timeout for game {state.game_id}, using default")
             return OffensiveDecision()  # All defaults
 
-    async def resolve_play(self, game_id: UUID) -> PlayResult:
+    async def resolve_play(self, game_id: UUID, forced_outcome: Optional[PlayOutcome] = None) -> PlayResult:
         """
         Resolve the current play with dice roll
 
@@ -335,6 +335,13 @@ class GameEngine:
         4. Update game state in DB
         5. Check for inning change (outs >= 3)
         6. Prepare next play (always last step)
+
+        Args:
+            game_id: Game to resolve
+            forced_outcome: If provided, use this outcome instead of rolling dice (for testing)
+
+        Returns:
+            PlayResult with complete outcome
         """
         state = state_manager.get_state(game_id)
         if not state:
@@ -347,7 +354,7 @@ class GameEngine:
         offensive_decision = OffensiveDecision(**state.decisions_this_play.get('offensive', {}))
 
         # STEP 1: Resolve play (this internally calls dice_system.roll_ab)
-        result = play_resolver.resolve_play(state, defensive_decision, offensive_decision)
+        result = play_resolver.resolve_play(state, defensive_decision, offensive_decision, forced_outcome)
 
         # Track roll for batch saving at end of inning
         if game_id not in self._rolls_this_inning:

backend/app/core/play_resolver.py

@@ -11,9 +11,10 @@ Updated: 2025-10-29 - Integrated universal PlayOutcome enum
 import logging
 from dataclasses import dataclass
 from typing import Optional, List
+import pendulum
 
 from app.core.dice import dice_system
-from app.core.roll_types import AbRoll
+from app.core.roll_types import AbRoll, RollType
 from app.models.game_models import GameState, DefensiveDecision, OffensiveDecision
 from app.config import PlayOutcome
 
@@ -135,7 +136,8 @@ class PlayResolver:
         self,
         state: GameState,
         defensive_decision: DefensiveDecision,
-        offensive_decision: OffensiveDecision
+        offensive_decision: OffensiveDecision,
+        forced_outcome: Optional[PlayOutcome] = None
     ) -> PlayResult:
         """
         Resolve a complete play
@@ -144,22 +146,41 @@ class PlayResolver:
             state: Current game state
             defensive_decision: Defensive team's choices
             offensive_decision: Offensive team's choices
+            forced_outcome: If provided, use this outcome instead of rolling dice (for testing)
 
         Returns:
             PlayResult with complete outcome
         """
         logger.info(f"Resolving play - Inning {state.inning} {state.half}, {state.outs} outs")
 
-        # Roll dice using our advanced AbRoll system
-        ab_roll = dice_system.roll_ab(
-            league_id=state.league_id,
-            game_id=state.game_id
-        )
-        logger.info(f"AB Roll: {ab_roll}")
+        if forced_outcome:
+            # Use forced outcome for testing (no dice roll)
+            logger.info(f"Using forced outcome: {forced_outcome.value}")
+            outcome = forced_outcome
+            # Create a dummy AbRoll for the forced outcome
+            ab_roll = AbRoll(
+                roll_id=f"forced_{state.game_id}_{state.play_count}",
+                roll_type=RollType.AB,
+                league_id=state.league_id,
+                timestamp=pendulum.now('UTC'),
+                game_id=state.game_id,
+                d6_one=1,  # Dummy values - not used for forced outcomes
+                d6_two_a=3,
+                d6_two_b=4,
+                chaos_d20=10,
+                resolution_d20=10
+            )
+        else:
+            # Roll dice using our advanced AbRoll system
+            ab_roll = dice_system.roll_ab(
+                league_id=state.league_id,
+                game_id=state.game_id
+            )
+            logger.info(f"AB Roll: {ab_roll}")
 
-        # Get base outcome from chart
-        outcome = self.result_chart.get_outcome(ab_roll)
-        logger.info(f"Base outcome: {outcome}")
+            # Get base outcome from chart
+            outcome = self.result_chart.get_outcome(ab_roll)
+            logger.info(f"Base outcome: {outcome}")
 
         # Apply decisions (simplified for Phase 2)
         # TODO: Implement full decision logic in Phase 3

backend/terminal_client/commands.py

@@ -211,11 +211,8 @@ class GameCommands:
         try:
             if forced_outcome:
                 display.print_info(f"🎯 Forcing outcome: {forced_outcome.value}")
-                # TODO: Integrate with game_engine to properly apply forced outcomes
-                display.print_warning("⚠️  Manual outcome selection is experimental")
-                display.print_warning("    Using regular resolution for now (forced outcome noted)")
 
-            result = await game_engine.resolve_play(game_id)
+            result = await game_engine.resolve_play(game_id, forced_outcome)
             state = await game_engine.get_game_state(game_id)
 
             if state: