feat: introduce identity-backed goat

simulation/actions/ActionTargetResolver.gd

@@ -17,6 +17,8 @@ func resolve(
 			)
 		SimulationIds.TARGET_ACTIVITY:
 			return _resolve_activity(npc, origin, simulation_manager, active_world_adapter)
+		SimulationIds.TARGET_ANIMAL:
+			return _resolve_animal(npc, origin, simulation_manager, active_world_adapter)
 		SimulationIds.TARGET_FREE:
 			return {
 				"target_id": "", "position": origin + simulation_manager.get_wander_offset(npc.id)
@@ -202,6 +204,32 @@ func _resolve_activity(
 	return active_world_adapter.get_activity_target(npc.current_task, origin)
 
 
+func _resolve_animal(
+	npc: SimNPC, origin: Vector3, simulation_manager: Node, active_world_adapter: Node
+) -> Dictionary:
+	if not active_world_adapter.has_method("get_animal_candidates"):
+		return {}
+	var best: Dictionary = {}
+	var best_distance := INF
+	var candidates: Array[Dictionary] = active_world_adapter.get_animal_candidates(npc.current_task)
+	for candidate in candidates:
+		var animal_id := StringName(candidate["target_id"])
+		var state: AnimalStateRecord = simulation_manager.animal_care.get_state(animal_id)
+		if state == null or not state.can_npc_feed() or not state.is_available_for(npc.id):
+			continue
+		var position: Vector3 = candidate["position"]
+		var distance := origin.distance_squared_to(position)
+		if distance < best_distance:
+			best_distance = distance
+			best = candidate
+	if best.is_empty():
+		return {}
+	var target_id := StringName(best["target_id"])
+	if not simulation_manager.animal_care.reserve(target_id, npc.id):
+		return {}
+	return best
+
+
 func score_resource_candidate(
 	npc: SimNPC, origin: Vector3, position: Vector3, state: ResourceStateRecord
 ) -> float: