lamindb
Manage Biological Data with LaminDB
Biology teams need reproducible data systems that connect datasets, metadata, workflows, and ontology terms. This skill guides LaminDB setup, curation, querying, lineage tracking, and integrations.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "lamindb" from https://skillstore.io/skills/k-dense-ai-lamindb.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-lamindb/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "lamindb". I need to organize scRNA-seq batches and query by tissue and treatment.
Expected outcome:
A practical data model with artifact keys, typed metadata features, ontology-backed tissue terms, and query steps before loading large files.
Using "lamindb". My cell type labels contain synonyms and invalid names.
Expected outcome:
A curation workflow that standardizes labels, separates invalid terms, maps accepted terms to Bionty records, and records validation decisions.
Using "lamindb". We want to move from a local instance to a shared cloud deployment.
Expected outcome:
A migration checklist covering storage choice, database choice, credential handling, cache location, backup planning, and team access boundaries.
Security Audit
SafeThe skill is documentation for LaminDB and contains no executable helper scripts, hidden automation, or prompt-injection override text. The static alerts are Markdown examples, setup placeholders, LaminDB alias usage, and generated report text rather than active command execution, credential access, or exfiltration. No semantic security issue was found beyond the static patterns.
Risk Factors
⚙️ External commands (49)
🌐 Network access (17)
📁 Filesystem access (49)
🔑 Env variables (17)
Share & cite this report
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https://skillstore.io/skills/k-dense-ai-lamindb/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown badge
[](https://skillstore.io/skills/k-dense-ai-lamindb?utm_source=security_passport_badge)HTML badge
<a href="https://skillstore.io/skills/k-dense-ai-lamindb?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/k-dense-ai-lamindb/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/k-dense-ai-lamindb.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
K-Dense-AI. (2026). lamindb security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-lamindb/audits/7BibTeX citation
@techreport{k-dense-ai-k-dense-ai-lamindb-2026,
author = {K-Dense-AI},
title = {lamindb security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/k-dense-ai-lamindb/audits/7},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "lamindb security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/k-dense-ai-lamindb/audits/7"
identifiers:
- type: other
value: "skillstore:k-dense-ai-lamindb:audit:7"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
k-dense-ai-lamindb
2026-09-09
davila7-lamindb
2026-09-09
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Curate single-cell datasets
Plan registration, metadata validation, ontology mapping, and lineage tracking for scRNA-seq or spatial datasets.
Design research data infrastructure
Compare local, cloud, and production deployment patterns for storage, databases, cache, and team access.
Connect model experiments to data
Link W&B, MLflow, workflow managers, and versioned biological artifacts through shared provenance.
Try These Prompts
Help me set up a local LaminDB instance for a new biology project. Explain the decisions I need to make.
Design a LaminDB curation plan for my dataset. I have these metadata fields and these ontology requirements: [details].
Show how to structure LaminDB artifacts, features, collections, and lineage tracking for this analysis workflow: [workflow].
Review my LaminDB deployment plan for cloud storage, PostgreSQL, cache settings, user access, and workflow integrations: [plan].
Best Practices
- Start tracking before each analysis so outputs keep clear lineage.
- Validate metadata and ontology terms before downstream analysis.
- Query metadata first, then load only the datasets you need.
Avoid
- Running analyses before tracking starts, which leaves lineage incomplete.
- Duplicating datasets under new keys instead of using versioning.
- Loading large files before narrowing results with metadata queries.
Frequently Asked Questions
What is LaminDB used for?
Does this skill execute LaminDB commands?
Which data types does it cover?
Can it help with biological ontologies?
Can it support cloud deployments?
Is this a replacement for official documentation?
Developer Details
Author
K-Dense-AILicense
Apache-2.0 license
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/lamindbRef
b8ca75d2c0a7e7102978993058777d82b8ab2610
Maintenance freshness
7/21/2026
Usage
9 downloads · 219 views
File structure