- bench.py now generates every README table row (ANSI CI, pip/tqdm, pytest,
pretty JSON added) and refuses to print chars/4 estimates — reproduced
numbers can no longer silently diverge from the claims
- eval.py: the receipt ratios can't give — 8 seeded failure logs with
planted root causes and red herrings, asked raw vs compressed, graded by
deterministic keyword check. First run (haiku 4.5): raw 6/8, compressed
8/8 at 3.1x fewer tokens; both raw misses were lost-in-the-middle
- README: eval section, related-work section (rtk, Headroom, Drain3,
LLMLingua-2, arXiv 2604.13066), prompt-cache claim sharpened to the
rebuilt-prompt scenario, agent-harness integration (--run, --hook),
re-measured receipts table
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- LICENSE (MIT) and pyproject.toml: pip install . gives lessismore + lm
commands; [tokens] and [ml] extras
- budget(): middle-out hard cap, the only guaranteed-bounded pass; --budget N
runs after compression as the backstop; char-slicing fallback for single
giant lines
- serve(): stdlib paste-in demo page, localhost only; lm --serve
- Scrubbed internal hostnames/IPs from samples and README; benchmarks
re-measured after scrub (interleaved now 54,999 -> 4,585, 12.0x; dedupe
alone 1.6x on same input)
- 30-assert suite, green on system python and tiktoken venv
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
