feat(profiler/behave_shell): emit cognitive.error_resilience.frustration_typing

Compares median within-command IAT for commands following an errored
command vs commands following a successful one. Relative absolute delta
buckets to low / moderate / high. Skips when either group is empty
(no errors, or no clean baseline). v0.1; D.8 re-tunes.
This commit is contained in:
2026-05-04 00:00:36 -04:00
parent b704352783
commit 8183218d29
4 changed files with 172 additions and 0 deletions

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@@ -14,6 +14,7 @@ from decnet.profiler.behave_shell._ctx import SessionContext
from decnet.profiler.behave_shell._features.cognitive import (
cognitive_load,
command_branch_diversity,
error_resilience_frustration_typing,
error_resilience_retry_tactic,
exploration_style,
feedback_loop_engagement,
@@ -55,4 +56,5 @@ FEATURES: tuple[FeatureFn, ...] = (
planning_depth,
tool_vocabulary,
error_resilience_retry_tactic,
error_resilience_frustration_typing,
)

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@@ -25,6 +25,8 @@ from decnet.profiler.behave_shell._thresholds import (
EXPLORATION_TARGETED_REP_MIN,
FEEDBACK_CORRELATION_MIN,
FEEDBACK_MIN_PAIRS,
FRUSTRATION_LOW_MAX,
FRUSTRATION_MODERATE_MAX,
IKI_THINK_MAX_S,
INTER_CMD_DELIBERATE_MAX,
INTER_CMD_INSTANT_MAX,
@@ -186,6 +188,61 @@ def feedback_loop_engagement(ctx: SessionContext) -> Iterator[Observation]:
)
def error_resilience_frustration_typing(ctx: SessionContext) -> Iterator[Observation]:
"""Emit ``cognitive.error_resilience.frustration_typing``.
Compares median within-command IAT for commands *following* an
errored command against the same statistic for commands following
a successful command. A large relative delta indicates the operator
typed differently after a failure — speed-up (rage / fluency) or
slowdown (caution); both are signs of arousal.
Skip emission when either group is empty (no errors, or every
command errored — no clean baseline). Sample-size honesty drops
confidence below the floor.
"""
post_err: list[float] = []
post_ok: list[float] = []
cmds = ctx.commands
intra = ctx.intra_command_iats
if len(cmds) < 2 or len(intra) != len(cmds):
return
for i in range(1, len(cmds)):
cmd_iats = intra[i]
if not cmd_iats:
continue
m = statistics.median(cmd_iats)
if cmds[i - 1].errored:
post_err.append(m)
else:
post_ok.append(m)
if not post_err or not post_ok:
return
median_err = statistics.median(post_err)
median_ok = statistics.median(post_ok)
if median_ok <= 0.0:
return
delta = abs(median_err - median_ok) / median_ok
if delta < FRUSTRATION_LOW_MAX:
value = "low"
elif delta < FRUSTRATION_MODERATE_MAX:
value = "moderate"
else:
value = "high"
if len(post_err) < MIN_COMMANDS_FOR_FULL_CONFIDENCE:
confidence = 0.40
else:
confidence = 0.60
yield make_observation(
ctx,
primitive="cognitive.error_resilience.frustration_typing",
value=value,
confidence=confidence,
)
def error_resilience_retry_tactic(ctx: SessionContext) -> Iterator[Observation]:
"""Emit ``cognitive.error_resilience.retry_tactic``.

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@@ -155,6 +155,21 @@ PLANNING_REACTIVE_MIN: float = 0.50
TOOL_VOCAB_NARROW_MAX: int = 3
TOOL_VOCAB_BROAD_MIN: int = 10
# ── cognitive.error_resilience.frustration_typing (Step D.6) ───────────────
# Compare the median within-command IAT of commands *following* an
# errored command against the same statistic for commands following a
# successful command. The relative absolute delta:
#
# delta = |median_post_error - median_post_success| / median_post_success
#
# delta < FRUSTRATION_LOW_MAX → low
# delta < FRUSTRATION_MODERATE_MAX → moderate
# else → high
#
# v0.1; D.8 re-tunes.
FRUSTRATION_LOW_MAX: float = 0.10
FRUSTRATION_MODERATE_MAX: float = 0.30
# ── motor.keystroke_cadence (Step B.1) ──────────────────────────────────────
# Typing bursts split at gaps > IKI_THINK_MAX_S so think-pauses between
# commands don't inflate the within-burst CV. Mirrors the prototype's

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@@ -0,0 +1,98 @@
"""Step D.6: ``cognitive.error_resilience.frustration_typing``."""
from __future__ import annotations
from decnet.profiler.behave_shell import extract_session
from decnet.profiler.behave_shell._parse import AsciinemaEvent
PRIMITIVE = "cognitive.error_resilience.frustration_typing"
def _of(observations: list, primitive: str):
obs = [o for o in observations if o.primitive == primitive]
assert len(obs) == 1, f"expected exactly one {primitive}, got {len(obs)}"
return obs[0]
def _typed(text: str, t0: float, dt: float) -> list[AsciinemaEvent]:
return [(t0 + i * dt, "i", c) for i, c in enumerate(text)]
def _build(blocks: list[tuple[str, bool, float]]) -> list[AsciinemaEvent]:
"""Synthesise a session.
``blocks`` is a list of (token, errored, dt) tuples. Each command
gets its own time slot 2s apart; ``dt`` is the within-command IAT.
"""
events: list[AsciinemaEvent] = []
for i, (tok, errored, dt) in enumerate(blocks):
t0 = i * 2.0
events.extend(_typed(f"{tok}\r", t0=t0, dt=dt))
if errored:
cmd_end = t0 + len(tok) * dt
events.append((cmd_end + 0.10, "o", f"bash: {tok}: command not found\n"))
else:
cmd_end = t0 + len(tok) * dt
events.append((cmd_end + 0.10, "o", "ok\n"))
return events
def test_no_errors_no_emission() -> None:
out = list(extract_session(_build([("ls", False, 0.05)] * 5), sid="ft-clean"))
assert [o for o in out if o.primitive == PRIMITIVE] == []
def test_no_baseline_no_emission() -> None:
"""Every command errored — no clean baseline → skip emission."""
out = list(extract_session(_build([("foo", True, 0.05)] * 5), sid="ft-allerr"))
assert [o for o in out if o.primitive == PRIMITIVE] == []
def test_matching_speeds_emit_low() -> None:
"""Same dt for post-error and post-success commands → delta ≈ 0 → low."""
blocks = [
("ok", False, 0.05),
("ok", False, 0.05),
("foo", True, 0.05),
("ok", False, 0.05), # post-err: dt=0.05
("ok", False, 0.05), # post-ok: dt=0.05
("foo", True, 0.05),
("ok", False, 0.05), # post-err: dt=0.05
("ok", False, 0.05),
]
out = list(extract_session(_build(blocks), sid="ft-low"))
obs = _of(out, PRIMITIVE)
assert obs.value == "low"
def test_huge_speed_change_emits_high() -> None:
"""Post-error commands typed 4x slower than post-success → delta=3 → high."""
blocks = [
("ok", False, 0.05),
("ok", False, 0.05), # post-ok: dt=0.05
("foo", True, 0.05),
("ok", False, 0.20), # post-err: dt=0.20 (4x slower)
("ok", False, 0.05), # post-ok: dt=0.05
("foo", True, 0.05),
("ok", False, 0.20),
("ok", False, 0.05),
]
out = list(extract_session(_build(blocks), sid="ft-high"))
obs = _of(out, PRIMITIVE)
assert obs.value == "high"
def test_low_post_error_count_reduces_confidence() -> None:
short = [
("ok", False, 0.05),
("foo", True, 0.05),
("ok", False, 0.05),
("ok", False, 0.05),
]
full_blocks = [("ok", False, 0.05)]
for _ in range(6):
full_blocks.append(("foo", True, 0.05))
full_blocks.append(("ok", False, 0.05))
s = _of(list(extract_session(_build(short), sid="ft-short")), PRIMITIVE)
f = _of(list(extract_session(_build(full_blocks), sid="ft-full")), PRIMITIVE)
assert s.confidence < f.confidence