lamindb
Use when working with LaminDB, the open-source lineage-native lakehouse for biological datasets and models. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation with Bionty, collections, branches, storage, and workflow integrations.
npx skills add K-Dense-AI/scientific-agent-skills --skill lamindb --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LaminDB ## Overview LaminDB is an open-source, lineage-native lakehouse for biology. It makes datasets and models queryable, traceable, validated, reproducible, and FAIR (Findable, Accessible, Interoperable, Reusable) while storing data in open formats across local filesystems, S3, GCS, Hugging Face, SQLite, and Postgres. **Core Value Proposition:** - **Queryability**: Search and filter artifacts, records, runs, features, schemas, and collections - **Traceability**: Track inputs, outputs, parameters, source code, and environments for notebooks, scripts, functions, and pipelines - **Validation**: Curate DataFrame, AnnData, SpatialData, TileDB-SOMA, Parquet, Zarr, and other biological formats with schemas - **FAIR Compliance**: Standardize annotations with Bionty-backed ontologies and custom registries - **Change management**: Organize work with projects, branches, spaces, collections, and saved notes or plans ## When to Use This Skill Use this skill when: - **Managing biological datasets**: scRNA-seq, bulk RNA-seq, spatial transcriptomics, flow cytometry, multi-modal data, EHR data - **Tracking computational workflows**: Notebooks, scripts, functions, shell scripts, and pipeline e
- Overview
- When to Use This Skill
- Core Capabilities
- 1. Core Concepts and Data Lineage
- 2. Data Management and Querying
- 3. Annotation and Validation
- 4. Biological Ontologies
- 5. Integrations
- 6. Setup and Deployment
- Safety and Security Defaults
- Common Use Case Workflows
- Use Case 1: Single-Cell RNA-seq Analysis with Ontology Validation
- Use Case 2: Building a Queryable Data Lakehouse
- Use Case 3: ML Pipeline with W&B Integration
What does the lamindb skill do?
Use when working with LaminDB, the open-source lineage-native lakehouse for biological datasets and models. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation with Bionty, collections, branches, storage, and workflow integrations.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill lamindb --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.