BEHAVE-EXTRACTOR.md Phase B Step B.1.
* SessionContext gains typing_bursts: tuple[tuple[float, ...], ...]
built by _split_typing_bursts(iats) — splits at gaps > IKI_THINK_MAX_S
(1.5s) and drops bursts of fewer than 3 IATs. Mirrors prototype's
_split_into_bursts at BEHAVE/prototype_extractors/shell/extract.py:275.
* _features/motor.py:keystroke_cadence(ctx) emits one Observation
in {steady, bursty, hunt_and_peck, machine}. Median CV across
typing bursts; mean IKI < IKI_MACHINE_MAX_S paired with CV <
CV_MACHINE_MAX → machine. Confidence 0.85/0.70/0.65/0.60 per the
prototype's calibration history.
* < MIN_INPUTS_FOR_CADENCE inputs or zero typing bursts → skip
emission. v0.1 emits only the burst-CV variant; the prototype's
NAIVE session-CV variant is parked for v0.2.
* Calibration grid widened (PHASE_A_PRIMITIVES → PHASE_AB_PRIMITIVES)
to include motor.keystroke_cadence. Grid green across all five
shards.
Tests: too-few-inputs → no emit, all-think-pauses → no burst → no
emit, uniform IATs → steady, sub-5ms → machine, mixed-pace → bursty,
extreme bimodal → hunt_and_peck.
BEHAVE-EXTRACTOR.md Phase A Step 4. Pure refactor inside _ctx.py —
no new feature emits. Lays the shared utility for the three
cognitive primitives next in line (Steps 5-7).
* Command dataclass (frozen): start_ts, end_ts, first_token_hash.
PII-safe by construction — only the first whitespace-delimited
token of the command is retained, and only as a sha256 hash
(decnet/profiler/behave_shell/_parse.py:hash_token).
* _segment_commands walks input events char-by-char, splits on
\r / \n, hashes the first token, drops the rest.
* SessionContext gains commands, inter_cmd_iats, output_per_cmd.
output_per_cmd[i] counts bytes between commands[i].end_ts and
commands[i+1].start_ts — the natural pairing for Step 7
(feedback_loop_engagement).
Tests: empty / unterminated streams, single command (CR + LF
terminators), paste-with-newline, multi-command IAT pairing,
output-byte counting between boundaries, blank-line skip,
first-token-only PII discipline.
BEHAVE-EXTRACTOR.md Phase A Step 1. Lays the shared primitives that
Steps 2-3 (motor.input_modality, motor.paste_burst_rate) will
consume:
* parse_shard_line / parse_shard turn a shard JSONL line/file into
AsciinemaEvents, skipping headers and malformed records.
* PasteBurst dataclass + _detect_paste_bursts group consecutive
paste-class input events (len(d) >= 4 chars per the prototype's
empirical floor) into contiguous bursts, splitting on IAT gaps
larger than PASTE_BURST_MAX_IAT_S (200ms).
* SessionContext now carries iats and paste_bursts derivations.
* Threshold constants harvested from
BEHAVE/prototype_extractors/shell/extract.py — calibrated against
the five 2026-05-02 shards.
Tests cover pure-typed, pure-pasted, mixed streams; close vs far
paste events; typed events breaking a burst; PasteBurst immutability;
and the JSON parser's junk handling.
BEHAVE-EXTRACTOR.md Phase A Step 0. Lays the package skeleton
(__init__/extract/_parse/_ctx/_thresholds/_features) with empty
FEATURES = (), so the worker plumbing in BEHAVE-INTEGRATION Phase 4
has a stable import path before any primitive lands.
extract_session() builds a SessionContext once and fans the
registered feature functions across it; at Step 0 that fan-out is
empty and the function yields nothing. Step 1 (asciinema parser +
paste-burst detector) and Step 2 (motor.input_modality) land next.
Smoke suite asserts the empty contract: empty stream → no
observations, single event → t_start == t_end, multi-event → events
routed into input_events / output_events by kind, evidence_ref
defaults to "session:<sid>" or honours an explicit override.
