Files
DECNET/tests/profiler/behave_shell/test_cognitive_tool_vocabulary.py
anti f2b3393669 chore: relicense to AGPL-3.0-or-later and add SPDX headers
Replaces LICENSE (GPLv3 -> AGPLv3) and prepends
`SPDX-License-Identifier: AGPL-3.0-or-later` to every source file
across decnet/, decnet_web/, tests/, scripts/, and tools/.

Rationale: closes the GPLv3 ASP loophole so any party operating a
modified DECNET as a network service must offer their modified
source. Personal copyright (Samuel Paschuan) + inbound=outbound
contributions make a future unilateral relicense infeasible.

- LICENSE: full AGPL-3.0 text (gnu.org/licenses/agpl-3.0.txt)
- COPYRIGHT: project copyright notice
- tools/add_spdx_headers.py: idempotent header injector
  (shebang- and PEP 263-aware)

Touches 1565 source files (.py, .ts, .tsx, .js, .jsx, .css, .sh).
No behavior change; comments only.
2026-05-22 21:04:16 -04:00

63 lines
2.0 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-or-later
"""Step D.4: ``cognitive.tool_vocabulary``."""
from __future__ import annotations
from decnet.profiler.behave_shell import extract_session
from decnet.profiler.behave_shell._parse import AsciinemaEvent
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 _cmds(tokens: list[str]) -> list[AsciinemaEvent]:
events: list[AsciinemaEvent] = []
for i, tok in enumerate(tokens):
t0 = i * 1.0
for j, c in enumerate(tok):
events.append((t0 + j * 0.05, "i", c))
events.append((t0 + len(tok) * 0.05, "i", "\r"))
return events
def test_no_commands_no_emission() -> None:
out = list(extract_session([(0.0, "i", "x")], sid="tv-empty"))
assert [o for o in out if o.primitive == "cognitive.tool_vocabulary"] == []
def test_few_distinct_tools_emit_narrow() -> None:
out = list(extract_session(
_cmds(["ls", "ls", "ps", "ps", "ls", "ps", "ls", "ps"]),
sid="tv-narrow",
))
obs = _of(out, "cognitive.tool_vocabulary")
assert obs.value == "narrow"
def test_mid_distinct_emit_moderate() -> None:
out = list(extract_session(
_cmds(["ls", "ps", "id", "uname", "whoami", "pwd"]),
sid="tv-mod",
))
obs = _of(out, "cognitive.tool_vocabulary")
assert obs.value == "moderate"
def test_many_distinct_tools_emit_broad() -> None:
out = list(extract_session(
_cmds(["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k"]),
sid="tv-broad",
))
obs = _of(out, "cognitive.tool_vocabulary")
assert obs.value == "broad"
def test_low_sample_count_reduces_confidence() -> None:
short = list(extract_session(_cmds(["a", "b"]), sid="tv-short"))
full = list(extract_session(_cmds(["a", "b", "c", "d", "e", "f"]), sid="tv-full"))
s = _of(short, "cognitive.tool_vocabulary")
f = _of(full, "cognitive.tool_vocabulary")
assert s.confidence < f.confidence