Files
DECNET/decnet/profiler/behave_shell/_features/__init__.py
anti cd7c7ea5a2 feat(profiler/behave_shell): emit environmental.keyboard_layout
ANTI authorised dropping the PII boundary for this primitive. ctx
gains typed_unigram_counts / typed_bigram_counts / typed_letter_count
populated during the existing single-pass input walk (paste-class
events excluded).

Two-axis classifier:
* layout-artefact unigrams take priority — q rate above floor with
  low English saturation → azerty; z above floor with y below → qwertz
* fallback to English-bigram saturation: ≥ floor → qwerty, else other

Sample-size floor 200 typed letters; bigram histogram capped at
top-64 to bound memory. Confidence cap stays moderate (0.40-0.55) —
heuristic discriminator.
2026-05-04 00:38:24 -04:00

81 lines
2.0 KiB
Python

"""Registered feature functions.
Each entry takes a ``SessionContext`` and yields zero or more
``Observation`` instances. Adding a primitive = adding a function in a
sibling module and appending it to ``FEATURES``.
"""
from __future__ import annotations
from typing import Callable, Iterable
from decnet_behave_core.spec.envelope import Observation
from decnet.profiler.behave_shell._ctx import SessionContext
from decnet.profiler.behave_shell._features.cognitive import (
cognitive_load,
command_branch_diversity,
error_resilience_fallback_to_man,
error_resilience_frustration_typing,
error_resilience_retry_tactic,
exploration_style,
feedback_loop_engagement,
planning_depth,
tool_vocabulary,
inter_command_consistency,
inter_command_latency_class,
)
from decnet.profiler.behave_shell._features.environmental import (
keyboard_layout,
locale,
shell_type,
terminal_multiplexer,
)
from decnet.profiler.behave_shell._features.temporal import (
escalation_pattern,
landing_ritual,
session_duration,
)
from decnet.profiler.behave_shell._features.motor import (
command_chunking,
error_correction,
input_modality,
keystroke_cadence,
motor_stability,
paste_burst_rate,
pipe_chaining_depth,
shortcut_usage,
tab_completion,
)
FeatureFn = Callable[[SessionContext], Iterable[Observation]]
FEATURES: tuple[FeatureFn, ...] = (
input_modality,
paste_burst_rate,
keystroke_cadence,
motor_stability,
error_correction,
command_chunking,
tab_completion,
shortcut_usage,
pipe_chaining_depth,
inter_command_latency_class,
command_branch_diversity,
feedback_loop_engagement,
inter_command_consistency,
cognitive_load,
exploration_style,
planning_depth,
tool_vocabulary,
error_resilience_retry_tactic,
error_resilience_frustration_typing,
error_resilience_fallback_to_man,
session_duration,
escalation_pattern,
landing_ritual,
shell_type,
terminal_multiplexer,
locale,
keyboard_layout,
)