"""Numeric thresholds for BEHAVE-SHELL primitive classification.

Each constant cites its calibration source. When the registry's
``notes:`` field disagrees with a constant here, the registry is
authoritative — fix the constant, re-run the calibration grid.

Empirical thresholds inherited from the BEHAVE prototype extractor
(``BEHAVE/prototype_extractors/shell/extract.py``); see lines 40-90 of
that file for the calibration history. Any change here must keep the
five-class grid green.
"""
from __future__ import annotations

# ── paste-burst detection (Step 1) ──────────────────────────────────────────
# A single input event with ≥ PASTE_MIN_CHARS_PER_EVENT chars is the
# paste-class proxy used by the prototype; xterm-kitty / iTerm / VS Code
# pastes arrive as one bulk write.
PASTE_MIN_CHARS_PER_EVENT: int = 4

# Consecutive paste-class events arriving within this IAT collapse into
# one PasteBurst record. 200ms is the prototype's IKI burst cap.
PASTE_BURST_MAX_IAT_S: float = 0.20

# ── motor.input_modality (Step 2) ───────────────────────────────────────────
# Paste-event ratio thresholds. ≥ 40% paste events → "pasted" (LLM-driven);
# ≤ 5% → "typed" (human at the keyboard); in between → "mixed".
# Lowered from 0.5 after the 47.6% case in sessions-2026-05-02-with-llm.jsonl
# was clearly LLM-driven but missed the 0.5 floor.
MODALITY_PASTED_MIN: float = 0.40
MODALITY_TYPED_MAX: float = 0.05

# ── motor.paste_burst_rate (Step 3) ─────────────────────────────────────────
# Same paste-event ratio re-bucketed for the "how often does the operator
# paste" axis. Coarser than input_modality on purpose: this primitive is the
# habit signal, input_modality is the dominant-channel signal.
PASTE_RATE_HABITUAL_MIN: float = 0.50
PASTE_RATE_OCCASIONAL_MIN: float = 0.10

# ── cognitive.inter_command_latency_class (Step 5) ──────────────────────────
# Bucket edges (seconds) for the median inter-command IAT. Prototype
# values; v0.2 splits the original llm_roundtrip 2-8s band into
# llm_lightweight (orchestrated agents w/ small models / terse prompts) and
# llm_heavyweight (reasoning-class agents in tool loops with text
# generation between calls). Empirical anchor: Claude Opus driving recon
# via tmux send-keys produced a median of 15.5s.
INTER_CMD_INSTANT_MAX: float = 0.30
INTER_CMD_TYPING_MAX: float = 1.50
INTER_CMD_DELIBERATE_MAX: float = 2.00
INTER_CMD_LLM_LIGHTWEIGHT_MAX: float = 8.00
INTER_CMD_LLM_HEAVYWEIGHT_MAX: float = 30.00

# Sample-size floor for inter-command IAT primitives. Below this we
# halve the confidence per BEHAVE-EXTRACTOR.md "sample-size honesty".
MIN_COMMANDS_FOR_FULL_CONFIDENCE: int = 5

# ── cognitive.command_branch_diversity (Step 6) ─────────────────────────────
# unique_first_tokens / total_commands ratio. Prototype's empirical
# split (sessions-2026-05-02-* corpus): CLAUDE-CL chasing one finding
# ≈ 0.55-0.60 (adaptive), HUMAN exploring filesystem ≈ 0.65-0.70
# (adaptive), YOU-sim / CLAUDE-FF scripted recon ≈ 0.75+ (linear).
BRANCH_DIVERSITY_LINEAR_MIN: float = 0.70   # >= → linear_playbook

# ── cognitive.feedback_loop_engagement (Step 7) ─────────────────────────────
# Pearson r threshold for "the operator's pause grew with the volume of
# preceding output". |r| > this → significant; sign carries direction.
FEEDBACK_CORRELATION_MIN: float = 0.30
# Need at least this many (output_bytes, next_pause) pairs to even
# attempt a correlation. Below this the answer is "unknown".
FEEDBACK_MIN_PAIRS: int = 5

# ── cognitive.inter_command_consistency (Step 8) ────────────────────────────
# CV (stdev / mean) of inter-command IATs. Empirical (this corpus):
# human session CV=0.94 → variable; LLM-simulated CV=0.24 → metronomic;
# anything beyond 1.5 is heuristically "bimodal" (real bimodal detection
# via Hartigan dip is filed for v0.2).
PAUSE_CV_METRONOMIC_MAX: float = 0.40
PAUSE_CV_BIMODAL_MIN: float = 1.50

# ── 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
# _split_into_bursts (BEHAVE/prototype_extractors/shell/extract.py:275-286).
IKI_THINK_MAX_S: float = 1.50
# Sub-human floor for the "machine" classification — only paired with a
# pathologically uniform CV, since real humans never produce sub-5ms IATs
# in a sustained burst.
IKI_MACHINE_MAX_S: float = 0.005
CV_MACHINE_MAX: float = 0.05
CV_STEADY_MAX: float = 0.50
CV_BURSTY_MAX: float = 1.50
# Need this many input events before we'll claim a cadence at all.
MIN_INPUTS_FOR_CADENCE: int = 5

# ── motor.motor_stability (Step B.2) ────────────────────────────────────────
# Tremor proxy: fraction of within-burst IATs below TREMOR_FAST_FLOOR_S
# (30 ms — physiologically implausible double-press floor; humans can't
# reliably produce IATs below ~50 ms in sustained typing). High rate
# of sub-floor IATs flags double-press / motor twitch / stuck-key.
TREMOR_FAST_FLOOR_S: float = 0.030
TREMOR_RATE_MIN: float = 0.10  # ≥10% sub-floor → tremor

# ── motor.error_correction (Step B.3) ───────────────────────────────────────
# Backspace within this many seconds of the preceding key = "caught the
# typo mid-keystroke" (immediate). Beyond this = the operator paused,
# noticed, then went back (deferred).
BACKSPACE_IMMEDIATE_MAX_S: float = 0.50

# ── motor.command_chunking (Step B.4) ───────────────────────────────────────
# Median CV of within-command IATs. Below this → fluent (steady within
# each command); above → fragmented (operator pauses mid-command).
CMD_CHUNKING_FLUENT_CV_MAX: float = 0.50

# ── motor.shell_mastery.* (Phase C) ─────────────────────────────────────────
# Readline control bytes counted toward ``shortcut_usage``. The seven
# pinned by BEHAVE-EXTRACTOR.md §Phase C (line 472):
#   ^A start-of-line  ^E end-of-line  ^W kill-prev-word
#   ^U kill-line      ^R reverse-i-search  ^B back-char  ^F forward-char
# v0.2 may extend to ^K/^Y/^L/^D/^P/^N once corpus calibration justifies it.
# Note: ^U / ^W also feed ``motor.error_correction`` (Step B.3) via the
# ``kill_line_count`` channel — these are independent measurements over
# the same byte stream, not double-counting.
SHORTCUT_CTRL_BYTES: frozenset[str] = frozenset({
    "\x01", "\x05", "\x17", "\x15", "\x12", "\x02", "\x06",
})

# motor.shell_mastery.tab_completion — fraction of commands containing
# at least one ``\t`` keystroke. Registry buckets per BEHAVE-EXTRACTOR.md
# line 471: ``none`` (0%), ``occasional`` (<30%), ``habitual`` (≥50%).
# The 30%-50% gap rounds down to ``occasional`` — the registry's own gap.
TAB_COMPLETION_OCCASIONAL_MAX: float = 0.30
TAB_COMPLETION_HABITUAL_MIN: float = 0.50

# motor.shell_mastery.shortcut_usage — total readline ctrl-byte
# keystrokes per command. Registry buckets are qualitative
# (``none / moderate / heavy``); v0.1 thresholds are best-guesses
# pinned for five-class corpus calibration. Re-tune once HUMAN /
# YOU-sim / LW-sim / CLAUDE-FF / CLAUDE-CL data lands.
#   0/cmd        → none
#   <0.05/cmd    → none (counted shortcuts but rare; rounds down)
#   0.05-0.30    → moderate
#   ≥0.30/cmd    → heavy
SHORTCUT_USAGE_MODERATE_MIN: float = 0.05
SHORTCUT_USAGE_HEAVY_MIN: float = 0.30

# Sample-size floor below which Phase C primitives drop confidence to
# 0.40 (sample-size honesty). Mirrors MIN_COMMANDS_FOR_FULL_CONFIDENCE
# but is named separately so a future tune can move them independently.
SHELL_MASTERY_MIN_COMMANDS: int = 5

# Width of the "near a bucket boundary" band (relative to the boundary)
# used by Phase C primitives. ±10% of the boundary value drops
# confidence by 0.20 per BEHAVE-EXTRACTOR.md §"Threshold proximity".
SHELL_MASTERY_BOUNDARY_BAND: float = 0.10