Phase G shared infrastructure (no primitive yet emitted):
* New `_intent.py` — five precomputed first-token-hash sets (recon /
exfil / persistence / lateral / destructive) with documented
precedence, plus opsec-history and three lexeme sets (positive /
negative / obscenity) for the typed-text counter pass. Stop words
that collide with registry value vocabulary (`no`, `hell`, `ok`)
are deliberately excluded — the PII regression test catches such
collisions.
* `_typed_char_histograms()` extended with five integer counters
populated in the same single-pass walk: `obscenity_hits`,
`positive_lex_hits`, `negative_lex_hits`, `caps_run_max`,
`bang_run_max`. Longest-suffix match against bounded lexicon
(`LEXEME_MAX_LEN`); paste-class events excluded.
* `SessionContext` widened by the same five fields. Drives G.5
(valence), G.6 (arousal), G.8 (frustration_venting) without retaining
raw operator text.
* Bump twisted >= 26.4.0rc2 to clear CVE-2026-42304 (pre-existing,
caught by pre-commit pip-audit). Adjust ftp template type-ignore
code from attr-defined to misc to match the new Twisted typing.
PII discipline: same shape as F.4 — fixed-vocabulary integer counters
on ctx, never on observations.
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.
Adds PromptLine dataclass + extract_prompt_lines() helper. PromptLine
carries ts, suffix_char ($/#/%/>), raw_line (ANSI-stripped, capped),
is_root flag. Populated during the existing single-pass output-window
walk; SessionContext gains prompt_lines, Command gains
followed_by_prompt.
PII trade-off (ANTI-authorised at Phase F): PS1 text retained on ctx
so F.1 / F.3 / E.4 can read it. Capped at PROMPT_LINE_MAX_CHARS=256.
Observations still only carry derived primitive values.
D.0's regex error helpers stay alongside (NOT subsumed) — they fire
even when PS1 echo is suppressed. F.0 enriches D.0 rather than
replacing it.
Lifts the error-signal slice of F.0 forward as a D.0 prelude. ANSI
strip + canonical bash/sh error fingerprints classify each command's
post-execution output window; Command gains errored / output_bytes
fields. PII discipline preserved — only a bool and an int leave the
helper, the stripped output text is dropped on return.
Drives D.1 (cognitive_load error_rate term) and D.5–D.7 (error_resilience
family). Phase F.0 will subsume this with PS1 + exit-code parsing.
BEHAVE-EXTRACTOR.md Phase B Step B.3. Replaces the prototype's
two-line "0 vs >0 backspaces" placeholder with a backspace-timing
classifier that honours the registry's full vocabulary.
* SessionContext gains backspace_count, backspace_iats (IAT from
each backspace back to the preceding non-backspace input event),
and kill_line_count (^U / ^W). Built by _scan_correction_signals,
which retains only counts and timing aggregates — no character
data leaves the helper, in line with the BEHAVE PII discipline.
* _features/motor.py:error_correction(ctx) emits one Observation
in {immediate, deferred, absent, route_around}.
- 0 backspaces + ≥1 ^U/^W → route_around (rewrite, not correct)
- 0 backspaces + 0 kill-lines → absent
- backspaces with median IAT ≤ 500 ms → immediate
- slower → deferred
Confidence 0.65 / 0.65 / 0.55 / 0.55.
* < 3 inputs → skip emit.
* Calibration grid widened to include motor.error_correction;
green across all five shards.
Tests cover all four buckets, the < 3 inputs skip, and the PII
regression (raw command body never appears in the serialised
observation).
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.
