chore(cp6): holistic-review cleanup — drop dead EASY start consts, de-8x8 docstring, ABC-faithful test stubs

proteus/grid/scenarios/predator_evade.py

@@ -1,7 +1,8 @@
 """predator_evade — the bear-chase evasion scenario for motive_grid.
 
-A predator pursues the focal agent across an 8x8 grid by taking one
-shortest-path (BFS) step toward it every turn, so its motion reads as a clear
+A predator pursues the focal agent across the grid (8x8 at EASY; larger at
+higher difficulties) by taking one shortest-path (BFS) step toward it every
+turn, so its motion reads as a clear
 *chase* intent rather than noise (the ToM signal the benchmark probes).  The
 world is laced with a short internal wall that forms a **dead-end to the west**,
 exactly where the focal agent has been walking.  At the Cut handover the only
@@ -84,11 +85,11 @@ _REWARD_SURVIVED = 50.0
 _REWARD_WALL_HIT = -3.0
 
 # --------------------------------------------------------------------------- #
-# EASY deterministic layout.
+# EASY defaults consumed before build_level runs (class grid_size hint +
+# __init__'s pre-build wall set). The full per-difficulty layouts — including
+# focal/predator starts — live in _LAYOUTS below.
 # --------------------------------------------------------------------------- #
 _GRID_SIZE: tuple[int, int] = (8, 8)
-_FOCAL_START: tuple[int, int] = (5, 3)
-_PREDATOR_START: tuple[int, int] = (7, 3)
 # Vertical wall column forming the dead-end west of the focal's path.
 _WALL_CELLS: tuple[tuple[int, int], ...] = (
     (2, 2),

tests/grid/test_scenario_registry.py

@@ -14,13 +14,14 @@ def test_register_and_get_roundtrip():
         task_name = "dummy_for_test"
         grid_size = (4, 4)
         rules_text = "test"
-        def build_level(self, rng): ...
+        def build_level(self, rng, difficulty): ...
         def cut_focal_policy(self, game): return "stay"
         def cut_length(self, difficulty): return 1
         def advance_threat(self, game): ...
         def check_elimination(self, game): return False
         def optimal_action(self, game): return "stay"
         def habit_action(self, game): return "stay"
+        def step_reward(self, game, action, blocked, focal_before, predator_before): return 0.0
         def legend(self): return {5: "."}
 
     assert get_scenario("dummy_for_test") is _Dummy
@@ -40,13 +41,14 @@ def test_duplicate_registration_raises():
         task_name = name
         grid_size = (1, 1)
         rules_text = ""
-        def build_level(self, rng): ...
+        def build_level(self, rng, difficulty): ...
         def cut_focal_policy(self, game): return "stay"
         def cut_length(self, difficulty): return 1
         def advance_threat(self, game): ...
         def check_elimination(self, game): return False
         def optimal_action(self, game): return "stay"
         def habit_action(self, game): return "stay"
+        def step_reward(self, game, action, blocked, focal_before, predator_before): return 0.0
         def legend(self): return {}
 
     with pytest.raises(ValueError):