anti
e52a0e0381
BEHAVE-EXTRACTOR.md Phase A Step 5. Classifies the operator's
thinking pace between commands. Splits LW-sim / CLAUDE-FF /
CLAUDE-CL.
* _features/cognitive.py:inter_command_latency_class(ctx) emits one
Observation in {instant, typing_speed, deliberate,
llm_lightweight, llm_heavyweight, long}, computed as the median
of ctx.inter_cmd_iats bucketed against the prototype thresholds
(v0.2 split: lightweight 2-8s, heavyweight 8-30s).
* Sample-size honesty: < 5 commands halves confidence (0.40 vs
0.80) per BEHAVE-EXTRACTOR.md.
* Threshold consts (INTER_CMD_*_MAX, MIN_COMMANDS_FOR_FULL_CONFIDENCE,
plus parked Step 6/7/8 thresholds for the next three commits)
added to _thresholds.py.
Tests cover all six buckets at empirically-anchored IATs (15s ≈
Claude Opus driving recon via tmux send-keys), plus the
single-command no-IAT and low-sample-count paths.
62 lines
2.0 KiB
Python
62 lines
2.0 KiB
Python
"""``cognitive.*`` feature functions.
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Step 5: ``cognitive.inter_command_latency_class``.
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Step 6: ``cognitive.command_branch_diversity``.
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Step 7: ``cognitive.feedback_loop_engagement``.
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Step 8: ``cognitive.inter_command_consistency``.
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"""
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from __future__ import annotations
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import statistics
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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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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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INTER_CMD_LLM_LIGHTWEIGHT_MAX,
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INTER_CMD_TYPING_MAX,
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MIN_COMMANDS_FOR_FULL_CONFIDENCE,
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)
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def _bucket_inter_cmd_latency(median_iat: float) -> str:
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if median_iat <= INTER_CMD_INSTANT_MAX:
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return "instant"
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if median_iat <= INTER_CMD_TYPING_MAX:
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return "typing_speed"
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if median_iat <= INTER_CMD_DELIBERATE_MAX:
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return "deliberate"
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if median_iat <= INTER_CMD_LLM_LIGHTWEIGHT_MAX:
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return "llm_lightweight"
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if median_iat <= INTER_CMD_LLM_HEAVYWEIGHT_MAX:
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return "llm_heavyweight"
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return "long"
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def inter_command_latency_class(ctx: SessionContext) -> Iterator[Observation]:
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"""Emit ``cognitive.inter_command_latency_class``.
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Operator's *thinking pace* between commands, bucketed against
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calibrated thresholds. Splits LW-sim / CLAUDE-FF / CLAUDE-CL.
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"""
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if not ctx.inter_cmd_iats:
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return
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median_iat = statistics.median(ctx.inter_cmd_iats)
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bucket = _bucket_inter_cmd_latency(median_iat)
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# Sample-size honesty: < 5 commands → halve confidence
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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 = 0.80
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yield make_observation(
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ctx,
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primitive="cognitive.inter_command_latency_class",
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value=bucket,
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confidence=confidence,
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)
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