feat(profiler/behave_shell): emit motor.shell_mastery.shortcut_usage

decnet/profiler/behave_shell/_features/__init__.py

@@ -24,6 +24,7 @@ from decnet.profiler.behave_shell._features.motor import (
     keystroke_cadence,
     motor_stability,
     paste_burst_rate,
+    shortcut_usage,
     tab_completion,
 )
 
@@ -37,6 +38,7 @@ FEATURES: tuple[FeatureFn, ...] = (
     error_correction,
     command_chunking,
     tab_completion,
+    shortcut_usage,
     inter_command_latency_class,
     command_branch_diversity,
     feedback_loop_engagement,

decnet/profiler/behave_shell/_features/motor.py

@@ -28,6 +28,8 @@ from decnet.profiler.behave_shell._thresholds import (
     PASTE_RATE_OCCASIONAL_MIN,
     SHELL_MASTERY_BOUNDARY_BAND,
     SHELL_MASTERY_MIN_COMMANDS,
+    SHORTCUT_USAGE_HEAVY_MIN,
+    SHORTCUT_USAGE_MODERATE_MIN,
     TAB_COMPLETION_HABITUAL_MIN,
     TAB_COMPLETION_OCCASIONAL_MAX,
     TREMOR_FAST_FLOOR_S,
@@ -316,3 +318,51 @@ def tab_completion(ctx: SessionContext) -> Iterator[Observation]:
         value=value,
         confidence=confidence,
     )
+
+
+def shortcut_usage(ctx: SessionContext) -> Iterator[Observation]:
+    """Emit ``motor.shell_mastery.shortcut_usage`` ∈ {none, moderate, heavy}.
+
+    Metric: total readline ctrl-byte keystrokes (the seven in
+    :data:`SHORTCUT_CTRL_BYTES`) divided by command count. Registry
+    buckets are qualitative; v0.1 thresholds are pinned for corpus
+    calibration. Heavy users tend to be tmux/zsh/bash power operators
+    who edit lines in place rather than retyping.
+
+    Confidence:
+    * < ``SHELL_MASTERY_MIN_COMMANDS`` → 0.40.
+    * Within ±10% of either bucket boundary → 0.55.
+    * Otherwise → 0.65 (lower than tab_completion: thresholds are
+      not yet corpus-calibrated, mirrors ``motor_stability`` posture).
+
+    Skips emission when the session has no commands at all.
+    """
+    n = len(ctx.commands)
+    if n == 0:
+        return
+    total_shortcuts = sum(c.shortcut_count for c in ctx.commands)
+    rate = total_shortcuts / n
+
+    if total_shortcuts == 0 or rate < SHORTCUT_USAGE_MODERATE_MIN:
+        value = "none"
+    elif rate < SHORTCUT_USAGE_HEAVY_MIN:
+        value = "moderate"
+    else:
+        value = "heavy"
+
+    if n < SHELL_MASTERY_MIN_COMMANDS:
+        confidence = 0.40
+    elif (
+        _near(rate, SHORTCUT_USAGE_MODERATE_MIN)
+        or _near(rate, SHORTCUT_USAGE_HEAVY_MIN)
+    ):
+        confidence = 0.55
+    else:
+        confidence = 0.65
+
+    yield make_observation(
+        ctx,
+        primitive="motor.shell_mastery.shortcut_usage",
+        value=value,
+        confidence=confidence,
+    )

decnet/profiler/behave_shell/_thresholds.py

@@ -130,6 +130,18 @@ SHORTCUT_CTRL_BYTES: frozenset[str] = frozenset({
 TAB_COMPLETION_OCCASIONAL_MAX: float = 0.30
 TAB_COMPLETION_HABITUAL_MIN: float = 0.50
 
+# motor.shell_mastery.shortcut_usage — total readline ctrl-byte
+# keystrokes per command. Registry buckets are qualitative
+# (``none / moderate / heavy``); v0.1 thresholds are best-guesses
+# pinned for five-class corpus calibration. Re-tune once HUMAN /
+# YOU-sim / LW-sim / CLAUDE-FF / CLAUDE-CL data lands.
+#   0/cmd        → none
+#   <0.05/cmd    → none (counted shortcuts but rare; rounds down)
+#   0.05-0.30    → moderate
+#   ≥0.30/cmd    → heavy
+SHORTCUT_USAGE_MODERATE_MIN: float = 0.05
+SHORTCUT_USAGE_HEAVY_MIN: float = 0.30
+
 # Sample-size floor below which Phase C primitives drop confidence to
 # 0.40 (sample-size honesty). Mirrors MIN_COMMANDS_FOR_FULL_CONFIDENCE
 # but is named separately so a future tune can move them independently.