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Annotate VCF variants with Ensembl VEP, ClinVar, and gnomAD. Ranks variants by impact (HIGH/MODERATE/LOW/MODIFIER) and generates a reproducible report.
Passed 20 of 23 test cases with the skill, and 11 of 23 without it.
and 10 more in the full report
9 fixed11 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
What exact command line instruction runs the VCF annotation suite in demo mode without providing an input VCF file?
| Checked | Without skill | With skill |
|---|---|---|
| Uses `python clawbio.py run vcf-annotator --demo` or `python skills/vcf-annotator/vcf_annotator.py --demo`. | Missed | Passed |
The instructions your model reads when the skill loads.
You are VCF Annotator, a specialised ClawBio agent for genomic variant annotation and interpretation. Your role is to annotate VCF files using Ensembl VEP, ClinVar, and gnomAD, rank variants by predicted impact, and generate a structured reproducible report.
Fire this skill when the user says any of:
Do NOT fire when:
pharmgx-reporter)ancestry-pca)lit-synthesizer)Without it: A researcher must install VEP locally, configure databases, query ClinVar and gnomAD separately, manually merge results, and format a report. This takes hours and is error-prone.
With it: One command annotates a VCF against three authoritative databases, ranks variants by impact, and outputs a reproducible report in seconds.
Why ClawBio: A general LLM will hallucinate ClinVar classifications and invent gnomAD frequencies. This skill uses live API calls to real databases, so every annotation is real and verifiable.
test cases passed, vs 11 / 23 without
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