anti
6763fceb0b
BEHAVE-EXTRACTOR.md Phase A Step 3. Same paste-event ratio as
motor.input_modality but coarser-bucketed: this is the *habit*
signal (does the operator reach for paste at all?), where
input_modality is the dominant-channel signal.
* _features/motor.py:paste_burst_rate(ctx) emits one Observation
per session in {none, occasional, habitual} with confidence
0.70 / 0.70 / 0.80.
* Thresholds: PASTE_RATE_OCCASIONAL_MIN=0.10,
PASTE_RATE_HABITUAL_MIN=0.50.
Splits YOU-sim from LW/CLAUDE-FF/CLAUDE-CL — LLM-driven sessions
paste habitually, real humans rarely paste.
Tests: pure-typed → none; 1-paste-in-10 → occasional;
paste-majority → habitual; output-only → no observation; habitual
confidence > occasional confidence.
79 lines
2.4 KiB
Python
79 lines
2.4 KiB
Python
"""``motor.*`` feature functions.
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Step 2: ``motor.input_modality`` — typed / pasted / mixed.
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Step 3: ``motor.paste_burst_rate`` — none / occasional / habitual.
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"""
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from __future__ import annotations
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from typing import Iterator
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from decnet_behave_core.spec.envelope import Observation
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from decnet.profiler.behave_shell._ctx import SessionContext
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from decnet.profiler.behave_shell._features._emit import make_observation
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from decnet.profiler.behave_shell._thresholds import (
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MODALITY_PASTED_MIN,
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MODALITY_TYPED_MAX,
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PASTE_RATE_HABITUAL_MIN,
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PASTE_RATE_OCCASIONAL_MIN,
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)
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def input_modality(ctx: SessionContext) -> Iterator[Observation]:
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"""Emit ``motor.input_modality`` ∈ {typed, pasted, mixed}.
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Ratio of paste-class events to total inputs. Empty input → skip
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emission entirely (the registry doesn't admit ``unknown`` here
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and fabricating ``typed`` for a zero-input session is dishonest).
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"""
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n = len(ctx.input_events)
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if n == 0:
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return
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ratio = ctx.paste_event_count / n
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if ratio >= MODALITY_PASTED_MIN:
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modality = "pasted"
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confidence = 0.75
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elif ratio <= MODALITY_TYPED_MAX:
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modality = "typed"
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confidence = 0.75
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else:
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modality = "mixed"
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confidence = 0.70
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yield make_observation(
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ctx,
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primitive="motor.input_modality",
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value=modality,
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confidence=confidence,
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)
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def paste_burst_rate(ctx: SessionContext) -> Iterator[Observation]:
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"""Emit ``motor.paste_burst_rate`` ∈ {none, occasional, habitual}.
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Same paste-event ratio as ``input_modality`` but coarser-bucketed:
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this primitive is the *habit* signal (does the operator reach for
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paste at all?), where input_modality is the dominant-channel
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signal (is the session paste-driven overall?). Splits YOU-sim from
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LW/CLAUDE-FF/CLAUDE-CL — LLM-driven sessions paste habitually,
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real humans don't.
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"""
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n = len(ctx.input_events)
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if n == 0:
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return
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ratio = ctx.paste_event_count / n
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if ratio >= PASTE_RATE_HABITUAL_MIN:
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level = "habitual"
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confidence = 0.80
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elif ratio >= PASTE_RATE_OCCASIONAL_MIN:
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level = "occasional"
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confidence = 0.70
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else:
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level = "none"
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confidence = 0.70
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yield make_observation(
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ctx,
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primitive="motor.paste_burst_rate",
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value=level,
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confidence=confidence,
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)
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