feat(*): Log live goal rate to TensorBoard during training

Game/scripts/ship_ai_controller.gd

@@ -107,6 +107,15 @@ var ball: RigidBody3D
 var opponent: Ship
 var attack_goal_position: Vector3
 
+# Set directly by TrainingMode (_on_goal_scored / the timeout branch in
+# _physics_process) at the same time as `done = true`. Deliberately NOT
+# cleared in reset(): TrainingMode's _reset_episode() (which calls reset())
+# runs synchronously, immediately after done is set, before the Sync node
+# ever reads get_info()/get_done() for that terminal tick — clearing it here
+# would wipe the value that read needs. Both call sites always overwrite
+# (true on goal, false on timeout) rather than toggle, so no reset is needed.
+var goal_scored_this_episode := false
+
 var _ticks_since_ball_touch := 1 << 30  # large so the first touch always pays
 
 
@@ -135,6 +144,14 @@ func get_reward() -> float:
 	return reward
 
 
+# Symmetric across both self-play agents: reports whether this episode ended
+# in a goal at all, not which team scored — a clean "goal rate" signal
+# distinct from rollout/ep_rew_mean, which mixes this with dense shaping
+# (ball chasing/touching). See train.py's GoalRateCallback.
+func get_info() -> Dictionary:
+	return {"goal_scored": goal_scored_this_episode}
+
+
 func get_action_space() -> Dictionary:
 	return {
 		"thrust": {"size": 3, "action_type": "continuous"},

Game/scripts/training_mode.gd

@@ -290,6 +290,7 @@ func _physics_process(_delta):
 			for agent in _agents:
 				agent.reward -= draw_penalty
 				agent.done = true
+				agent.goal_scored_this_episode = false
 		_reset_episode()
 		return
 
@@ -320,6 +321,7 @@ func _on_goal_scored(conceding_team: int) -> void:
 	for agent in _agents:
 		agent.reward += goal_reward if agent.ship.team != conceding_team else -goal_reward
 		agent.done = true
+		agent.goal_scored_this_episode = true
 	_reset_episode()