vep-variant-annotator
Variant Effect Predictor skill for comprehensive variant annotation with clinical database integration
Best use case
vep-variant-annotator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Variant Effect Predictor skill for comprehensive variant annotation with clinical database integration
Teams using vep-variant-annotator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/vep-variant-annotator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How vep-variant-annotator Compares
| Feature / Agent | vep-variant-annotator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Variant Effect Predictor skill for comprehensive variant annotation with clinical database integration
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# VEP Variant Annotator Skill ## Purpose Provide comprehensive variant annotation using Variant Effect Predictor with clinical database integration. ## Capabilities - Functional consequence prediction - Population frequency annotation (gnomAD) - Clinical database integration (ClinVar, COSMIC) - Custom annotation plugins - Pathogenicity score integration (CADD, REVEL) - Regulatory region annotation ## Usage Guidelines - Configure VEP with relevant annotation sources - Include population frequency databases - Add clinical databases for interpretation - Use pathogenicity predictors for prioritization - Document annotation database versions - Update annotations regularly ## Dependencies - Ensembl VEP - ANNOVAR - SnpEff ## Process Integration - Whole Genome Sequencing Pipeline (wgs-analysis-pipeline) - Clinical Variant Interpretation (clinical-variant-interpretation) - Pharmacogenomics Analysis (pharmacogenomics-analysis) - Rare Disease Diagnostic Pipeline (rare-disease-diagnostics)
Related Skills
loop-invariant-generator
Automatically generate and verify loop invariants for algorithm correctness proofs
structural-variant-detector
Structural variant detection skill for identifying CNVs, inversions, translocations, and complex rearrangements
pharmgkb-annotator
PharmGKB pharmacogenomics annotation skill for drug-gene interaction assessment
gatk-variant-caller
GATK best practices skill for germline and somatic variant calling with joint genotyping
deepvariant-caller
DeepVariant deep learning variant calling skill for high-accuracy SNV and indel detection
acmg-variant-classifier
ACMG/AMP variant classification skill for systematic pathogenicity assessment
invariant-analyzer
Identify and verify loop invariants for correctness proofs
process-builder
Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
babysitter
Orchestrate via @babysitter. Use this skill when asked to babysit a run, orchestrate a process or whenever it is called explicitly. (babysit, babysitter, orchestrate, orchestrate a run, workflow, etc.)
yolo
Run Babysitter autonomously with minimal manual interruption.
user-install
Install the user-level Babysitter Codex setup.
team-install
Install the team-pinned Babysitter Codex workspace setup.