VarCADD
Skill BioTender-max/awesome-bio-agent-skills/skills/openclaw/varCADD
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
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill varCADDAssembled 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
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name: varcadd-pathogenicity description: Variant Scorer keywords:
- variant-interpretation
- CADD
- pathogenicity
- genomics
- prediction measurable_outcome: Return pathogenicity scores for a VCF of 1000 variants within 2 minutes, flagging top 1% deleterious hits. license: Non-Commercial metadata: author: Genome Medicine 2025 version: "1.0.0" compatibility:
- system: Python 3.9+ allowed-tools:
- run_shell_command
- read_file
varCADD (Variant Pathogenicity Predictor)
Genome-wide pathogenicity prediction leveraging standing variation data to improve accuracy over traditional CADD scores.
When to Use
- Variant Prioritization: Ranking candidate variants in rare disease cases.
- VUS Interpretation: Assessing variants of uncertain significance.
- Research: Annotating novel variants in population studies.
Core Capabilities
- Score Generation: Calculate C-scores for SNVs and indels.
- Annotation: Add functional context (conservation, protein domains).
- Filtering: Identify likely pathogenic variants based on thresholds.
Workflow
- Input: VCF file.
- Annotate: Run varCADD model.
- Filter: Keep variants with Score > X.
- Output: Annotated VCF or ranked table.
Example Usage
User: "Score these variants from patient X."
Agent Action:
varcadd score --input patient.vcf --output scored.vcf
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.