REPRODUCE

Every script and artifact behind this Space

All links point at branch feat/system-one-benchmarks of cisco-ai-defense/defenseclaw. The corpora and the prediction files are held in private data repositories; the scoring artifacts this Space reads are vendored into the public repository at the paths below.

Ledger and corpus

Running an arm

benchmark_run_system_one.py defaults to --max-input-tokens 200_000_000. A full 100,001-request s3 pass needs about 282M, and the cap is enforced after every request has completed, so the driver raises and writes no metadata. The budget is per driver, so sharding avoids the cap. A run that hit it is recoverable in place with --resume --resume-retry-errors, because the error rows still pass the prediction schema and carry a valid recomputed request_sha256.

The cohort harness

Scoring the cohort

The three scripts carry the dev host's absolute paths as they ran. Their arithmetic is imported verbatim from the board's re-mining module, which is what makes cohort numbers and board numbers comparable; that module is reached through a path on the dev host rather than through this directory. They are published in the form that produced the artifacts.

The arithmetic both programmes run

Artifacts this Space reads

Building this Space

Gates before an upload

Repository visibility

This Space is public. The four data repositories that hold the corpora, the prediction files and the serving records stay private. Nothing in the publish path moves a repository between visibilities in either direction, and the post-upload check aborts if one moved.

Corpus cases_sha256 39f2c1df2369952a0525cc4c5575f4bdb590fb3ca8c1bc6805cf4f376c1adbf7, grid cell C7/I3/Q2, --instruction-format structured.