Record original-alignment implementation and traceability checkpoint

Capture current source, content data, tests, asset licenses, and original-specification traceability. Original implementation remains incomplete. The accepted matching UI generation passed 154 suites and 12,253 checks, with eight rendered staff-contract screens reviewed. Latest native Windows and full-original acceptance remain outstanding.

tests/performance/fixtures/linear_path_reference.gd

@@ -0,0 +1,65 @@
+extends PathService
+
+# Pre-optimization algorithm, retained as an exact route-order oracle.
+func _run_a_star(
+	start: Vector3i,
+	goal: Vector3i,
+	allowed_layers: Array[int],
+	allowed_access_ids: Array[StringName]
+) -> Array[Vector3i]:
+	if start == goal:
+		return [start]
+
+	var open_set: Dictionary = {start: true}
+	var closed_set: Dictionary = {}
+	var came_from: Dictionary = {}
+	var g_score: Dictionary = {start: 0}
+
+	while not open_set.is_empty():
+		var current := _select_best_open_node(open_set, g_score, goal)
+		if current == goal:
+			return _reconstruct_path(came_from, current)
+
+		open_set.erase(current)
+		closed_set[current] = true
+		var edges: Array = _adjacency.get(current, [])
+		for edge_value: Variant in edges:
+			var edge: Dictionary = edge_value
+			var neighbor: Vector3i = edge[&"to"]
+			if neighbor.z not in allowed_layers \
+				or _cell_is_temporarily_blocked(neighbor) \
+				or not _edge_meets_vertical_policy(current, edge) \
+				or not _edge_is_accessible(edge, allowed_access_ids):
+				continue
+			var tentative_cost: int = int(g_score[current]) + _edge_total_cost(edge)
+			var known_cost: int = int(g_score.get(neighbor, _INFINITE_COST))
+			var better_parent := false
+			if tentative_cost == known_cost and came_from.has(neighbor):
+				better_parent = _coordinate_less(current, came_from[neighbor])
+			if tentative_cost > known_cost or (tentative_cost == known_cost and not better_parent):
+				continue
+
+			came_from[neighbor] = current
+			g_score[neighbor] = tentative_cost
+			if closed_set.has(neighbor):
+				closed_set.erase(neighbor)
+			open_set[neighbor] = true
+
+	return []
+
+
+func _select_best_open_node(open_set: Dictionary, g_score: Dictionary, goal: Vector3i) -> Vector3i:
+	var best := Vector3i.ZERO
+	var has_best := false
+	var best_score := _INFINITE_COST
+	for candidate_value: Variant in open_set:
+		var candidate: Vector3i = candidate_value
+		var score: int = int(g_score[candidate]) + _heuristic(candidate, goal)
+		if not has_best or score < best_score:
+			best = candidate
+			best_score = score
+			has_best = true
+		elif score == best_score and _coordinate_less(candidate, best):
+			best = candidate
+	return best
+