lamindb

8.7

149

406

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

biology

8.7

Rating

Installs

Data & Analytics

Quick Review

Excellent skill for LaminDB biological data management. The description clearly articulates when to use this skill (biological datasets, workflow tracking, ontologies, data lakehouses). SKILL.md provides an outstanding structure: concise overview with six well-defined capability areas, each pointing to detailed reference files. Task knowledge is comprehensive with concrete code examples for common workflows (scRNA-seq, data lakehouse, ML pipelines, Nextflow integration) and actionable getting-started guidance. The modular organization prevents clutter while ensuring depth. Novelty is strong—managing biological data with lineage tracking, ontology validation, and FAIR compliance is complex and token-intensive for a CLI agent alone. The skill meaningfully reduces the cost of these specialized biological data workflows. Minor opportunity: could slightly expand description to mention specific pain points solved (e.g., 'reproducibility crises' or 'ontology standardization challenges').