diff --git a/src/lerobot/robots/unitree_g1/controllers/sonic_whole_body.py b/src/lerobot/robots/unitree_g1/controllers/sonic_whole_body.py
index 95fa58f09..d1429d2b2 100644
--- a/src/lerobot/robots/unitree_g1/controllers/sonic_whole_body.py
+++ b/src/lerobot/robots/unitree_g1/controllers/sonic_whole_body.py
@@ -57,11 +57,35 @@ TOKEN_DIM = 64  # decoder latent size
 # added on top of this.
 DEFAULT_ANGLES = np.array(
     [
-        -0.312, 0.0, 0.0, 0.669, -0.363, 0.0,
-        -0.312, 0.0, 0.0, 0.669, -0.363, 0.0,
-        0.0, 0.0, 0.0,
-        0.2, 0.2, 0.0, 0.6, 0.0, 0.0, 0.0,
-        0.2, -0.2, 0.0, 0.6, 0.0, 0.0, 0.0,
+        -0.312,
+        0.0,
+        0.0,
+        0.669,
+        -0.363,
+        0.0,
+        -0.312,
+        0.0,
+        0.0,
+        0.669,
+        -0.363,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.2,
+        0.2,
+        0.0,
+        0.6,
+        0.0,
+        0.0,
+        0.0,
+        0.2,
+        -0.2,
+        0.0,
+        0.6,
+        0.0,
+        0.0,
+        0.0,
     ],
     dtype=np.float32,
 )
@@ -110,10 +134,10 @@ def compute_kp_kd():
 
 
 # Action-feature prefix for the latent-token interface (see _extract_token_from_action).
-TOKEN_ACTION_PREFIX = "motion_token"
+TOKEN_ACTION_PREFIX = "motion_token"  # nosec B105 - feature-key prefix, not a secret
 # Proprio-state prefix for the token interface: the robot echoes the last commanded token
 # here so ``lerobot-rollout`` aggregates it into a 64-D ``observation.state``.
-TOKEN_STATE_PREFIX = "motion_token_state"
+TOKEN_STATE_PREFIX = "motion_token_state"  # nosec B105 - feature-key prefix, not a secret
 
 
 def token_action_key(i: int) -> str:
@@ -142,10 +166,72 @@ INIT_RAMP_S = 3.0
 # all-zero token, which is off the learned manifold and decodes to a slightly goofy stance.
 # This one decodes to a stable, natural standing pose.
 _NEUTRAL_TOKEN_CODES = np.array(
-    [-1, 3, 1, -1, 1, -3, 6, 1, 1, 1, -2, -4, -2, 0, -3, -1,
-     2, -1, -3, -5, 3, 1, 1, -4, -1, -1, 1, -7, 0, 1, 2, -2,
-     5, -2, -2, -4, 0, -1, 3, -1, 0, -5, -1, 0, -4, 0, 0, -1,
-     -1, 2, -2, 1, 3, 3, 1, 0, 0, 6, 0, -7, 3, 0, 2, -2],
+    [
+        -1,
+        3,
+        1,
+        -1,
+        1,
+        -3,
+        6,
+        1,
+        1,
+        1,
+        -2,
+        -4,
+        -2,
+        0,
+        -3,
+        -1,
+        2,
+        -1,
+        -3,
+        -5,
+        3,
+        1,
+        1,
+        -4,
+        -1,
+        -1,
+        1,
+        -7,
+        0,
+        1,
+        2,
+        -2,
+        5,
+        -2,
+        -2,
+        -4,
+        0,
+        -1,
+        3,
+        -1,
+        0,
+        -5,
+        -1,
+        0,
+        -4,
+        0,
+        0,
+        -1,
+        -1,
+        2,
+        -2,
+        1,
+        3,
+        3,
+        1,
+        0,
+        0,
+        6,
+        0,
+        -7,
+        3,
+        0,
+        2,
+        -2,
+    ],
     dtype=np.float32,
 )
 NEUTRAL_TOKEN = _NEUTRAL_TOKEN_CODES / 16.0  # FSQ Div(16): integer codes -> on-grid token