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davila7/claude-code-templates

If you're wrangling biological datasets like scRNA-seq or spatial transcriptomics and need more than a file dump, this gives you queryable data with automatic lineage tracking. It's built around making data FAIR compliant without the usual pain, letting you annotate with proper biological ontologies (genes, cell types, diseases via Bionty) and validate schemas before things break downstream. The workflow integration is solid, hooks into Nextflow, Snakemake, Weights & Biases, and MLflow so your computational provenance actually gets captured. It's Python-based lakehouse architecture that tracks what notebook produced what dataset from what inputs. Best for teams tired of recreating analyses because nobody documented which version of which data went into last year's results.

skills.sh installs
219
GitHub stars
33.2K
last updated
Aug 21, 2026
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Install

$ npx -y skills add davila7/claude-code-templates --skill lamindb --agent claude-code

Installs into .claude/skills of the current project.

Files

LaminDB

Overview

LaminDB is an open-source data framework for biology designed to make data queryable, traceable, reproducible, and FAIR (Findable, Accessible, Interoperable, Reusable). It provides a unified platform that combines lakehouse architecture, lineage tracking, feature stores, biological ontologies, LIMS (Laboratory Information Management System), and ELN (Electronic Lab Notebook) capabilities through a single Python API.

Core Value Proposition:

  • Queryability: Search and filter datasets by metadata, features, and ontology terms
  • Traceability: Automatic lineage tracking from raw data through analysis to results
  • Reproducibility: Version control for data, code, and environment
  • FAIR Compliance: Standardized annotations using biological ontologies

When to Use This Skill

Use this skill when:

SKILL.md on GitHub

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Details

Repository
github.com/davila7/claude-code-templates
Categories
Data Science & ML, Automation & Workflows
First seen
Jun 3, 2026

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