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.

Quality

78%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/lamindb/SKILL.md

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Well-structured and actionable with strong progressive disclosure, but it is verbose through repetition and lacks explicit validation feedback loops in its curation workflows.

Suggestions

Deduplicate the reference list: keep the inline 'Reference:' pointer per capability and drop the separate Reference Files section, or vice versa.

Add an explicit validation feedback loop to the annotation/validation workflow, e.g. 'Run curator.validate(); if it fails, fix the offending values, re-run validate(), and only call save_artifact() once it passes.'

Trim the generic 'Key Principles' list to the few that add non-obvious guidance, removing items that restate the capability bullets.

Dimension	Reasoning	Score
Conciseness	Largely relevant LaminDB specifics with no basic-concept fluff, but the reference files are listed three times (inline, Getting Started Checklist, Reference Files), the 'When to Use This Skill' section restates the description, and the generic 'Key Principles' could be trimmed.	2 / 3
Actionability	Concrete APIs (ln.track(), bt.CellType.import_source(), AnnDataCurator, .cat.standardize()) and four complete, copy-paste-ready code examples give fully executable guidance.	3 / 3
Workflow Clarity	The curation process and use cases are sequenced, but for validation/batch operations there is no explicit validate→fix→re-validate feedback loop, so checkpoints are only implicit.	2 / 3
Progressive Disclosure	A clear overview body points to six one-level-deep reference files that all exist, each signaled with 'Reference: references/<file>.md - Read this for...', giving easy navigation.	3 / 3
	Total	10 / 12 Passed

Description

85%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: third-person, concrete, and explicit about what and when. The only weakness is trigger-term breadth, relying on a single 'Use when working with LaminDB' phrasing.

Suggestions

Broaden the trigger clause with natural user phrasings, e.g. 'Use when working with LaminDB, registering biological datasets, tracking lineage, or annotating data with Bionty ontologies.'

Dimension	Reasoning	Score
Specificity	Lists multiple concrete capabilities — 'setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation with Bionty, collections, branches, storage, and workflow integrations' — rather than vague language.	3 / 3
Completeness	Explicitly states both what it does ('lineage-native lakehouse for biological datasets and models... Covers...') and when to use it ('Use when working with LaminDB'), matching the both-what-and-when anchor.	3 / 3
Trigger Term Quality	The only natural trigger phrase is 'Use when working with LaminDB'; the remaining terms (lineage-native lakehouse, artifact registration) are capability names rather than the varied keyword forms users would naturally say, so coverage is partial.	2 / 3
Distinctiveness Conflict Risk	LaminDB plus Bionty-backed ontology annotation is a narrow, distinct niche unlikely to fire for unrelated skills.	3 / 3
	Total	11 / 12 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: K-Dense-AI/scientific-agent-skills
Path: skills/lamindb/SKILL.md
Commit: 757b63b

Reviewed: about 12 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.