This walks you through the full antibody engineering pipeline from preclinical lead to clinical candidate. It handles humanization by searching IMGT for germline matches, designs CDR grafting strategies with backmutation analysis, pulls structures from AlphaFold and SAbDab, scores developability across aggregation and stability metrics, and searches IEDB for immunogenicity risks. The workflow is structured around creating a progressive optimization report that documents every variant with citations. It leans heavily on database lookups rather than model reasoning, which makes sense for this domain where you want evidence-graded decisions. The phase-by-phase structure keeps complex antibody optimization organized, though you'll need access to the external APIs it calls.
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-antibody-engineering