The corpus had an append-only manifest, a reviewer tool, and an evaluation harness, but nothing a
stranger could read: what is in the corpus, what a label means, and how leakage is prevented lived in
code and in reviewers' heads.
scripts/dataset_card.py generates docs/DATASET_CARD.md from manifest.jsonl. Every count is read back
from real records — active samples, contributors, per-split contributor and sample counts, class
balance over active samples only — and every fact the pipeline does not collect (devices, contexts,
licenses) is printed as pending rather than estimated. The generator refuses to render a card for a
corpus where one contributor straddles two splits or where a recorded split is not the one the
subject key derives, and it never publishes a subject key or a withdrawn sample's labels. --check
fails when the committed page is not the generator's own output, so the card cannot drift into a
hand-written document.
docs/LABELING_GUIDE.md is the reviewer's rulebook: visible form, broad visible color, and photo
quality; visible color is not blood; nothing is diagnosed; a model suggestion is provisional input to
a human decision. Exclusions are named, and the split policy is stated where it is enforced.
The demo's new DATASET CARD scene builds a throwaway corpus with the real ingest command from
committed synthetic fixtures, publishes the card, and shows the refusal a planted contributor earns,
then re-checks the committed page. Its captions are release gates in build_release.py, which also runs
tests/dataset-card.test.py before a release exists.
tests/dataset-card.test.py covers the counts, the pending facts, the withdrawal receipt, both
refusals, determinism, the empty-corpus case, the committed-page identity, and both documents'
prohibitions. Every fixture is synthetic.
Closes#27
