Clinical variant interpretation from raw variant calls to ACMG-classified recommendations with structural impact analysis. Use for VUS classification, pathogenicity assessment with cited criteria, structure-based variant impact (AlphaFold/PDB), non-coding/regulatory variant effect prediction with sequence deep-learning models (AlphaGenome, Enformer, Borzoi, ChromBPNet, Evo 2), and producing clinical-grade variant reports for return of results or molecular tumor boards. Use this whenever a user asks about a variant's significance, an intronic/promoter/enhancer/UTR non-coding variant's functional impact, or needs ACMG classification — even if they don't say "ACMG".
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The canonical home for this skill is tooluniverse-variant-interpretation in mims-harvard/ToolUniverse
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The required workflow queries various biomedical literature and preprint databases (PubMed, EuropePMC, BioRxiv, MedRxiv, SemanticScholar, OpenAlex) which contain outsider-authored papers, preprints, and abstracts.
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
The skill references an external repository locator (`https://github.com/evolutionaryscale/esm@ee891c52`) to install a runtime dependency via `pip install` during setup or execution instructions, constituting an unverifiable external runtime dependency under the dependency gate rules.
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