Skills
Biology Skills uses a small number of broad domain skills so AI agents can activate the relevant biological guidance reliably.
Each domain contains:
SKILL.mdfor cross-cutting rules and routingreferences/for focused expert guidance on individual biological or computational topics
Available skills
biology-core
Foundational biological reasoning that applies across domains.
Covers:
- biological and experimental context
- evidence and claim strength
- observation versus prediction and inference
- association, mechanism, and causality
- identifiers, versions, and provenance
- ambiguity and interpretation boundaries
Use biology-core whenever omitted context, provenance, evidence type, or inference level could materially change a biological conclusion.
genomics
Biological and computational correctness for genomic data, analysis, interpretation, and reporting.
Covers:
- genome organisation
- reference genomes and exact reference identity
- FASTA and reference sequence files
- FASTQ and sequencing quality
- SAM, BAM, CRAM, and alignment indexes
- genomic intervals and coordinate conventions
- VCF, BCF, gVCF, and variant indexes
- variant representation and normalisation
- HGVS variant nomenclature
- transcripts and isoforms
- coding and protein consequences
- inheritance, phase, segregation, and mosaicism
- gene expression and regulatory context
Use genomics whenever reference sequences, coordinates, file semantics, variants, transcripts, genotypes, inheritance, or genomic interpretation affect correctness.
Using skills together
biology-core provides the general foundation. Domain skills add the rules specific to a field.
For example, a variant-interpretation task may require both:
biology-core
→ What does the evidence justify claiming?
genomics
→ What reference, allele, transcript, phase, and nomenclature define the result?
Agents should load only the relevant detailed references for the task rather than treating every topic page as required context.