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Variant interpretation acmg

Skill BioTender-max/awesome-bio-agent-skills/skills/openclaw/variant-interpretation-acmg

A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.From the repository description

Install
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill variant-interpretation-acmg

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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SKILL.md

1.9 KB, 477 tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

name: 'variant-interpretation-acmg' description: 'Classifies genetic variants according to ACMG (American College of Medical Genetics) guidelines.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

Variant Interpretation (ACMG)

The Variant Interpretation Skill automates the classification of genetic variants (Pathogenic, Benign, VUS) using a rules-based engine derived from ACMG guidelines.

When to Use This Skill

  • When analyzing a VCF file for clinical reporting.
  • To determine the clinical significance of a specific mutation (e.g., BRCA1 c.123A>G).
  • To aggregate evidence (population freq, computational predictions) into a final verdict.

Core Capabilities

  1. Rule Scoring: Applies codes like PVS1 (Null variant), PM2 (Rare), PP3 (In silico).
  2. Classification: Combines scores to reach a verdict (Pathogenic, Likely Pathogenic, VUS, etc.).
  3. Explanation: Provides the logic/evidence used for the classification.

Workflow

  1. Input: Variant details (Gene, HGVS, Consequence) or Evidence codes directly.
  2. Process: Sums weights of applied ACMG criteria.
  3. Output: Final classification and score breakdown.

Example Usage

User: "Classify a variant with evidence PVS1 and PM2."

Agent Action:

python3 Skills/Genomics/Variant_Interpretation/acmg_classifier.py \
    --evidence "PVS1,PM2"
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it: 2 files

7.1 KB alongside SKILL.md, 1 of them executable

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