Skills lamindb
📦

lamindb

Content revision r1 Safe ⚙️ External commands🌐 Network access📁 Filesystem access🔑 Env variables

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.

Supports: Claude Codex Code(CC)
📊 75 Adequate

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
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.

Markdown detail GET /skills/k-dense-ai-lamindb.md Signed manifest GET /api/skills/k-dense-ai-lamindb/manifest Signed lockfile GET /api/skills/k-dense-ai-lamindb/lockfile

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

Safe
v7 • 7/6/2026 Open versioned report

The 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.

8
Files scanned
3,893
Lines analyzed
0
Review items
0
False positives ignored

Risk Factors

⚙️ External commands (49)
evaluation_output.json:24 evaluation_output.json:111 evaluation_output.json:114 references/setup-deployment.md:633 references/setup-deployment.md:351 references/setup-deployment.md:352 references/setup-deployment.md:362 references/setup-deployment.md:363 SKILL.md:49 SKILL.md:51 SKILL.md:54 SKILL.md:60 SKILL.md:61 SKILL.md:75 SKILL.md:98 SKILL.md:99 SKILL.md:100 SKILL.md:104 SKILL.md:117 SKILL.md:126 SKILL.md:157 SKILL.md:162 SKILL.md:163 SKILL.md:188 SKILL.md:194-221 SKILL.md:221-225 SKILL.md:225-254 SKILL.md:254-258 SKILL.md:258-284 SKILL.md:284-288 SKILL.md:288-308 SKILL.md:308-314 SKILL.md:314-316 SKILL.md:316-317 SKILL.md:317-319 SKILL.md:319-322 SKILL.md:322 SKILL.md:324-329 SKILL.md:329-334 SKILL.md:334-339 SKILL.md:339-348 SKILL.md:348-354 SKILL.md:354-364 SKILL.md:364-372 SKILL.md:372-373 SKILL.md:373-374 SKILL.md:374-375 SKILL.md:375-376 SKILL.md:376-377
🌐 Network access (17)
evaluation_output.json:60 references/integrations.md:535 references/integrations.md:46 references/integrations.md:72 references/integrations.md:491 references/integrations.md:494 references/integrations.md:535 references/setup-deployment.md:118 references/setup-deployment.md:260 references/setup-deployment.md:266 references/setup-deployment.md:407 references/setup-deployment.md:423 SKILL.md:383 SKILL.md:384 SKILL.md:385 SKILL.md:386 SKILL.md:387
📁 Filesystem access (49)
evaluation_output.json:30 evaluation_output.json:132 evaluation_output.json:138 evaluation_output.json:30 evaluation_output.json:108 evaluation_output.json:132 evaluation_output.json:138 evaluation_output.json:144 evaluation_output.json:150 references/annotation-validation.md:22-24 references/annotation-validation.md:83-85 references/core-concepts.md:13-15 references/core-concepts.md:143-145 references/data-management.md:10-12 references/integrations.md:14-16 references/integrations.md:105-107 references/integrations.md:138-139 references/integrations.md:159-161 references/integrations.md:183-185 references/integrations.md:212-214 references/integrations.md:250-252 references/integrations.md:287-289 references/integrations.md:327-329 references/integrations.md:363-365 references/integrations.md:390-392 references/integrations.md:419-421 references/integrations.md:530-532 references/integrations.md:558-560 references/integrations.md:431 references/ontologies.md:36-37 references/ontologies.md:212-214 references/ontologies.md:405-407 references/setup-deployment.md:77 references/setup-deployment.md:77 references/setup-deployment.md:286 references/setup-deployment.md:499 references/setup-deployment.md:505 references/setup-deployment.md:54-55 references/setup-deployment.md:329-331 references/setup-deployment.md:369-371 references/setup-deployment.md:389-391 references/setup-deployment.md:601-603 references/setup-deployment.md:683-684 references/setup-deployment.md:381 references/setup-deployment.md:685 SKILL.md:195-196 SKILL.md:226-228 SKILL.md:259-260 SKILL.md:290-292
🔑 Env variables (17)
evaluation_output.json:66 evaluation_output.json:72 evaluation_output.json:78 references/integrations.md:49 references/integrations.md:50 references/integrations.md:612 references/integrations.md:613 references/integrations.md:620 references/setup-deployment.md:205 references/setup-deployment.md:206 references/setup-deployment.md:257 references/setup-deployment.md:258 references/setup-deployment.md:263 references/setup-deployment.md:264 references/setup-deployment.md:244 references/setup-deployment.md:206 references/setup-deployment.md:264
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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Security Assessment

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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/7

BibTeX 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 variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score
K-Dense-AI Recommended Current

k-dense-ai-lamindb

Skillstore Score 75
Evidence Confidence High
Skillstore usage 12
Updated

2026-08-21

davila7

davila7-lamindb

Skillstore Score 50
Evidence Confidence High
Skillstore usage 8
Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High
45
Architecture
85
Maintainability
87
Content
70
Community
83
Spec Compliance

What 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

Start a LaminDB project 
Help me set up a local LaminDB instance for a new biology project. Explain the decisions I need to make.
Plan dataset curation 
Design a LaminDB curation plan for my dataset. I have these metadata fields and these ontology requirements: [details].
Build queryable lineage 
Show how to structure LaminDB artifacts, features, collections, and lineage tracking for this analysis workflow: [workflow].
Review production deployment 
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?
LaminDB manages biological datasets with metadata, lineage, validation, and query support for reproducible research.
Does this skill execute LaminDB commands?
No. It provides guidance and examples that users can adapt in their own environment.
Which data types does it cover?
It covers DataFrames, AnnData, MuData, SpatialData, TileDB-SOMA, Parquet, CSV, and related biological artifacts.
Can it help with biological ontologies?
Yes. It explains validation and standardization with Bionty for genes, cell types, tissues, diseases, and related terms.
Can it support cloud deployments?
Yes. It describes local SQLite, cloud storage, PostgreSQL, cache configuration, and team deployment patterns.
Is this a replacement for official documentation?
No. Use it as task-focused guidance and confirm version-specific details in the official LaminDB documentation.

Developer Details

Author

K-Dense-AI

License

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/lamindb

Ref

b8ca75d2c0a7e7102978993058777d82b8ab2610

Maintenance freshness

7/21/2026

Usage

9 downloads · 219 views

File structure

📁 references/

📄 annotation-validation.md

📄 core-concepts.md

📄 data-management.md

📄 integrations.md

📄 ontologies.md

📄 setup-deployment.md

📄 evaluation_output.json

📄 SKILL.md

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