Vet the concrete third-party model a study will be built on — this repository, this revision, this checkpoint — not the architecture family. Records a model dossier (source and version pin, licence and the file it was read from, intended use, pretrained-weight provenance, model task vs study task, reported validation, what the model was developed on, your evaluation arms) and gates it deterministically. Catches what a licence check and a citation count cannot: an evaluation arm sitting on the benchmark the model was developed or tuned on, so the arm reads like validation while being closer to a training-set score. Also an evaluation set inside a pretraining corpus, an unstated or use-incompatible licence, an unpinned revision, and a hardware claim never executed. It vets an artifact; it never downloads or runs one.
$npx -y skills add aperivue/medsci-skills --skill model-sourcingInstalls into the current project.
Run `npx skills use "https://github.com/aperivue/medsci-skills" --skill "aperivue/medsci-skills/model-sourcing"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/aperivue/medsci-skills" that are relevant to the current task. Run `npx skills add "https://github.com/aperivue/medsci-skills"` and select the relevant skills, then follow their instructions.