feat(profiler/behave_shell): emit motor.keystroke_cadence

BEHAVE-EXTRACTOR.md Phase B Step B.1.

* SessionContext gains typing_bursts: tuple[tuple[float, ...], ...]
  built by _split_typing_bursts(iats) — splits at gaps > IKI_THINK_MAX_S
  (1.5s) and drops bursts of fewer than 3 IATs. Mirrors prototype's
  _split_into_bursts at BEHAVE/prototype_extractors/shell/extract.py:275.
* _features/motor.py:keystroke_cadence(ctx) emits one Observation
  in {steady, bursty, hunt_and_peck, machine}. Median CV across
  typing bursts; mean IKI < IKI_MACHINE_MAX_S paired with CV <
  CV_MACHINE_MAX → machine. Confidence 0.85/0.70/0.65/0.60 per the
  prototype's calibration history.
* < MIN_INPUTS_FOR_CADENCE inputs or zero typing bursts → skip
  emission. v0.1 emits only the burst-CV variant; the prototype's
  NAIVE session-CV variant is parked for v0.2.
* Calibration grid widened (PHASE_A_PRIMITIVES → PHASE_AB_PRIMITIVES)
  to include motor.keystroke_cadence. Grid green across all five
  shards.

Tests: too-few-inputs → no emit, all-think-pauses → no burst → no
emit, uniform IATs → steady, sub-5ms → machine, mixed-pace → bursty,
extreme bimodal → hunt_and_peck.

decnet/profiler/behave_shell/_features/__init__.py

@@ -19,6 +19,7 @@ from decnet.profiler.behave_shell._features.cognitive import (
 )
 from decnet.profiler.behave_shell._features.motor import (
     input_modality,
+    keystroke_cadence,
     paste_burst_rate,
 )
 
@@ -27,6 +28,7 @@ FeatureFn = Callable[[SessionContext], Iterable[Observation]]
 FEATURES: tuple[FeatureFn, ...] = (
     input_modality,
     paste_burst_rate,
+    keystroke_cadence,
     inter_command_latency_class,
     command_branch_diversity,
     feedback_loop_engagement,

decnet/profiler/behave_shell/_features/motor.py

@@ -2,9 +2,12 @@
 
 Step 2: ``motor.input_modality`` — typed / pasted / mixed.
 Step 3: ``motor.paste_burst_rate`` — none / occasional / habitual.
+Step B.1: ``motor.keystroke_cadence`` — steady / bursty / hunt_and_peck / machine.
 """
 from __future__ import annotations
 
+import statistics
+from itertools import chain
 from typing import Iterator
 
 from decnet_behave_core.spec.envelope import Observation
@@ -12,6 +15,11 @@ from decnet_behave_core.spec.envelope import Observation
 from decnet.profiler.behave_shell._ctx import SessionContext
 from decnet.profiler.behave_shell._features._emit import make_observation
 from decnet.profiler.behave_shell._thresholds import (
+    CV_BURSTY_MAX,
+    CV_MACHINE_MAX,
+    CV_STEADY_MAX,
+    IKI_MACHINE_MAX_S,
+    MIN_INPUTS_FOR_CADENCE,
     MODALITY_PASTED_MIN,
     MODALITY_TYPED_MAX,
     PASTE_RATE_HABITUAL_MIN,
@@ -76,3 +84,45 @@ def paste_burst_rate(ctx: SessionContext) -> Iterator[Observation]:
         value=level,
         confidence=confidence,
     )
+
+
+def keystroke_cadence(ctx: SessionContext) -> Iterator[Observation]:
+    """Emit ``motor.keystroke_cadence`` ∈ {steady, bursty, hunt_and_peck, machine}.
+
+    Median CV of within-typing-burst IATs (bursts split at gaps >
+    ``IKI_THINK_MAX_S`` so think-pauses between commands don't
+    inflate the variance). Pasted-only sessions and sessions below
+    ``MIN_INPUTS_FOR_CADENCE`` skip emission — no honest cadence
+    available.
+
+    v0.1 emits only the burst-CV variant. The prototype's NAIVE
+    session-CV variant (lower confidence, second emission per
+    primitive) is parked for v0.2.
+    """
+    if len(ctx.input_events) < MIN_INPUTS_FOR_CADENCE:
+        return
+    if not ctx.typing_bursts:
+        return
+    burst_cvs: list[float] = []
+    for b in ctx.typing_bursts:
+        m = statistics.fmean(b)
+        if m > 0:
+            burst_cvs.append(statistics.pstdev(b) / m)
+    if not burst_cvs:
+        return
+    cv = statistics.median(burst_cvs)
+    mean_iki = statistics.fmean(chain.from_iterable(ctx.typing_bursts))
+    if mean_iki < IKI_MACHINE_MAX_S and cv < CV_MACHINE_MAX:
+        value, confidence = "machine", 0.85
+    elif cv < CV_STEADY_MAX:
+        value, confidence = "steady", 0.70
+    elif cv < CV_BURSTY_MAX:
+        value, confidence = "bursty", 0.65
+    else:
+        value, confidence = "hunt_and_peck", 0.60
+    yield make_observation(
+        ctx,
+        primitive="motor.keystroke_cadence",
+        value=value,
+        confidence=confidence,
+    )