feat(profiler/behave_shell): emit cognitive.planning_depth
Distribution of inter-command IATs bucketed against IKI_THINK_MAX_S (deep) and INTER_CMD_INSTANT_MAX (reactive); fall-through is shallow. v0.1 thresholds; D.8 re-tunes.
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@@ -16,6 +16,7 @@ from decnet.profiler.behave_shell._features.cognitive import (
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command_branch_diversity,
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exploration_style,
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feedback_loop_engagement,
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planning_depth,
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inter_command_consistency,
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inter_command_latency_class,
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)
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@@ -49,4 +50,5 @@ FEATURES: tuple[FeatureFn, ...] = (
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inter_command_consistency,
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cognitive_load,
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exploration_style,
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planning_depth,
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)
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@@ -25,6 +25,7 @@ from decnet.profiler.behave_shell._thresholds import (
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EXPLORATION_TARGETED_REP_MIN,
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FEEDBACK_CORRELATION_MIN,
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FEEDBACK_MIN_PAIRS,
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IKI_THINK_MAX_S,
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INTER_CMD_DELIBERATE_MAX,
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INTER_CMD_INSTANT_MAX,
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INTER_CMD_LLM_HEAVYWEIGHT_MAX,
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@@ -33,6 +34,8 @@ from decnet.profiler.behave_shell._thresholds import (
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MIN_COMMANDS_FOR_FULL_CONFIDENCE,
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PAUSE_CV_BIMODAL_MIN,
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PAUSE_CV_METRONOMIC_MAX,
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PLANNING_DEEP_MIN,
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PLANNING_REACTIVE_MIN,
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)
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@@ -181,6 +184,50 @@ def feedback_loop_engagement(ctx: SessionContext) -> Iterator[Observation]:
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)
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def planning_depth(ctx: SessionContext) -> Iterator[Observation]:
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"""Emit ``cognitive.planning_depth`` ∈ {deep, shallow, reactive}.
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Read off the distribution of inter-command IATs:
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* **deep** — many think-pauses (> ``IKI_THINK_MAX_S``). The
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operator stops to think between commands.
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* **reactive** — most pauses are sub-instant
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(≤ ``INTER_CMD_INSTANT_MAX``). Knee-jerk pacing — automated
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runner, prepared playbook, or an LLM with no internal latency.
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* **shallow** — neither: mostly typing-speed pauses, no extended
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contemplation.
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Skip emission when no inter-command IATs exist (one or zero
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commands); the registry has no ``unknown`` for this primitive.
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"""
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iats = ctx.inter_cmd_iats
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if not iats:
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return
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n = len(iats)
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deep_count = sum(1 for x in iats if x > IKI_THINK_MAX_S)
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reactive_count = sum(1 for x in iats if x <= INTER_CMD_INSTANT_MAX)
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deep_frac = deep_count / n
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reactive_frac = reactive_count / n
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if deep_frac >= PLANNING_DEEP_MIN:
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value = "deep"
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elif reactive_frac >= PLANNING_REACTIVE_MIN:
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value = "reactive"
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else:
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value = "shallow"
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if len(ctx.commands) < MIN_COMMANDS_FOR_FULL_CONFIDENCE:
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confidence = 0.40
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else:
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confidence = 0.65
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yield make_observation(
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ctx,
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primitive="cognitive.planning_depth",
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value=value,
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confidence=confidence,
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)
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def exploration_style(ctx: SessionContext) -> Iterator[Observation]:
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"""Emit ``cognitive.exploration_style`` ∈ {methodical, chaotic, targeted}.
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@@ -128,6 +128,19 @@ COGNITIVE_LOAD_MEDIUM_MAX: float = 0.67
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EXPLORATION_TARGETED_REP_MIN: float = 0.50
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EXPLORATION_CHAOTIC_BACKTRACK_MIN: float = 0.30
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# ── cognitive.planning_depth (Step D.3) ────────────────────────────────────
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# Distribution of inter-command IATs.
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# deep_pause_fraction = (count of inter_cmd_iats > IKI_THINK_MAX_S) / N
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# reactive_pause_fraction = (count of inter_cmd_iats <= INTER_CMD_INSTANT_MAX) / N
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#
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# deep_pause_fraction >= PLANNING_DEEP_MIN → deep
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# reactive_pause_fraction >= PLANNING_REACTIVE_MIN → reactive
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# otherwise → shallow
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#
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# v0.1; D.8 re-tunes once D.1-D.7 are stable.
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PLANNING_DEEP_MIN: float = 0.40
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PLANNING_REACTIVE_MIN: float = 0.50
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# ── motor.keystroke_cadence (Step B.1) ──────────────────────────────────────
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# Typing bursts split at gaps > IKI_THINK_MAX_S so think-pauses between
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# commands don't inflate the within-burst CV. Mirrors the prototype's
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61
tests/profiler/behave_shell/test_cognitive_planning_depth.py
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61
tests/profiler/behave_shell/test_cognitive_planning_depth.py
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@@ -0,0 +1,61 @@
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"""Step D.3: ``cognitive.planning_depth``."""
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from __future__ import annotations
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from decnet.profiler.behave_shell import extract_session
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from decnet.profiler.behave_shell._parse import AsciinemaEvent
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def _of(observations: list, primitive: str):
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obs = [o for o in observations if o.primitive == primitive]
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assert len(obs) == 1, f"expected exactly one {primitive}, got {len(obs)}"
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return obs[0]
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def _commands_at(starts: list[float]) -> list[AsciinemaEvent]:
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events: list[AsciinemaEvent] = []
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for s in starts:
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events.append((s, "i", "x\r"))
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return events
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def test_no_inter_cmd_iats_no_emission() -> None:
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out = list(extract_session(_commands_at([0.0]), sid="pd-empty"))
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assert [o for o in out if o.primitive == "cognitive.planning_depth"] == []
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def test_long_pauses_emit_deep() -> None:
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"""Most pauses > 1.5s → deep."""
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out = list(extract_session(
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_commands_at([0.0, 3.0, 6.0, 9.0, 12.0, 15.0, 18.0, 21.0]),
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sid="pd-deep",
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))
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obs = _of(out, "cognitive.planning_depth")
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assert obs.value == "deep"
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def test_sub_instant_pauses_emit_reactive() -> None:
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"""Most pauses ≤ INTER_CMD_INSTANT_MAX (0.30s) → reactive."""
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out = list(extract_session(
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_commands_at([i * 0.10 for i in range(8)]),
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sid="pd-react",
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))
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obs = _of(out, "cognitive.planning_depth")
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assert obs.value == "reactive"
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def test_typing_speed_pauses_emit_shallow() -> None:
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"""Pauses around 1s — neither deep nor reactive → shallow."""
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out = list(extract_session(
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_commands_at([i * 1.0 for i in range(8)]),
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sid="pd-shallow",
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))
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obs = _of(out, "cognitive.planning_depth")
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assert obs.value == "shallow"
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def test_low_sample_count_reduces_confidence() -> None:
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short = list(extract_session(_commands_at([0.0, 1.0, 2.0]), sid="pd-short"))
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full = list(extract_session(_commands_at([i * 1.0 for i in range(8)]), sid="pd-full"))
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s = _of(short, "cognitive.planning_depth")
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f = _of(full, "cognitive.planning_depth")
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assert s.confidence < f.confidence
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