Add a new ML *system* to the TabArena benchmark. Use this skill whenever the user wants to integrate a whole pipeline rather than a single model — AutoML frameworks (AutoGluon, LightAutoML, FLAML, auto-sklearn), LLM-driven agents, hosted prediction APIs…
Run one already-integrated model on the TabArena benchmark, from a local smoke fit to the cluster run and the evaluated leaderboard. Use this skill whenever a maintainer wants to benchmark a model that is already in the registry, e.g. "benchmark TabM", "run…
Process, upload, and register one benchmarked method's results in TabArena. Use this skill whenever a maintainer points at a benchmark run's output directory and wants to turn its raw `results.pkl` files into cached + hosted + registered TabArena artifacts —…
Adapt TabArena/bencheval as the tasks/models/metrics/splitting layer for a new, domain-specific benchmark that lives in its own repository (not a contribution to this repo). Use this skill whenever the user wants to build a benchmark for a different data…
Add a new ML model to the TabArena benchmark system. Use this skill whenever the user wants to integrate a new tabular ML model into TabArena — even if they just say "add X model", "integrate X", "support X", or "wrap X for the benchmark". Creates all…
Regenerate the TabArena website artifacts and refresh a leaderboard Space's `data/` with them. Use this skill whenever a maintainer wants to publish the latest results to the leaderboard — e.g. "update the leaderboard", "regenerate the website artifacts and…