tooluniverse-variant-interpretation

Problem This Skill Solves

Clinical labs and researchers face critical challenges in variant interpretation:

1. Variant classification uncertainty - VUS (Variants of Uncertain Significance) comprise 40-60% of clinical variants
2. Evidence aggregation burden - Must integrate data from 10+ databases per variant
3. Structural context missing - Traditional annotation ignores 3D protein impact
4. Clinical actionability unclear - How does classification translate to patient care?

This skill provides: A systematic workflow that combines population databases, functional predictions, structural analysis (via AlphaFold2), and literature evidence into ACMG-compliant interpretations with clear clinical recommendations.

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Key Principles

1. ACMG-Guided Classification - Follow ACMG/AMP 2015 guidelines with explicit evidence codes
2. Structural Evidence Integration - Use AlphaFold2 for novel structural impact analysis
3. Population Context - gnomAD frequencies with ancestry-specific data
4. Gene-Disease Validity - ClinGen curation status for clinical relevance
5. Actionable Output - Clear recommendations, not just classifications
6. English-first queries - Always use English terms in tool calls (gene names, variant descriptions, disease names), even if the user writes in another language. Only try original-language terms as a fallback. Respond in the user's language

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Triggers

Use this skill when users:

• Ask about variant interpretation or classification
• Have VCF data needing clinical annotation
• Ask "what does this variant mean clinically?"
• Need ACMG classification for variants
• Want structural impact analysis for missense variants
• Ask about pathogenicity of specific variants

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