omero-integration

Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.

Quality

70%

Does it follow best practices?

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Securityby

Passed

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Fix and improve this skill with Tessl

tessl review fix ./backend/cli/skills/biology/omero-integration/SKILL.md

Quality

Content

65%Weight 40%Scale 1-5

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

The body is well-structured with excellent progressive disclosure and executable connection code, but it repeats capability information across sections and its batch workflows lack the validation checkpoints the rubric requires.

Suggestions

Add explicit validation/verification checkpoints to the batch workflows (e.g. 'verify connection succeeded before iterating', 'confirm images were retrieved before processing', 'validate table schema before storing').

Consolidate the capability catalog so each capability's scenarios and routing appear once, removing the repetition across Core Capabilities, Selecting the Right Capability, Common Workflows, and Notes.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with no over-explanation of known concepts, but the capability catalog is repeated across four sections (Core Capabilities, Selecting the Right Capability, Common Workflows, Notes) and the Overview restates the description verbatim, so it could be tightened.	3 / 5
Actionability	Provides executable, copy-paste-ready connection code in two variants plus a real install command and error-handling example, but the other seven capability areas are only described via scenario bullets with code delegated to references.	4 / 5
Workflow Clarity	Three workflows are clearly sequenced with numbered steps, but the batch-processing workflows (batch ROI analysis, analysis scripts) lack any validation or verification checkpoints, which caps workflow clarity at 3.	3 / 5
Progressive Disclosure	SKILL.md is a clear overview with eight well-signaled, one-level-deep references (each verified to exist), explicit 'File:' labels, and routing guidance, making navigation easy with no nested references.	5 / 5
	Total	15 / 20 Passed

Description

75%Weight 40%Scale 1-5

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

The description is specific and distinctive with comprehensive concrete actions, but it lacks an explicit 'Use when...' trigger clause and omits the 'OMERO' keyword that users would most naturally say, leaving trigger guidance only weakly implied.

Suggestions

Add an explicit 'Use when...' clause stating when Claude should invoke this skill, e.g. 'Use when working with OMERO servers, microscopy images, or high-content screening data.'

Include the term 'OMERO' and common file extensions (e.g. '.ome.tiff', '.tiff') so the description matches what users actually say.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Access images via Python', 'retrieve datasets', 'analyze pixels', 'manage ROIs/annotations', 'batch processing' — giving comprehensive coverage of the OMERO domain.	5 / 5
Completeness	Has a clear 'what' (microscopy data management with several concrete actions) but 'when' is only weakly implied by 'for high-content screening and microscopy workflows' with no explicit 'Use when...' trigger clause, which caps completeness at 3.	3 / 5
Trigger Term Quality	Strong domain keywords ('microscopy', 'datasets', 'ROIs/annotations', 'high-content screening') but omits the most natural term users would say — 'OMERO' — and common file extensions like .ome.tiff, so a few natural terms are missing.	4 / 5
Distinctiveness Conflict Risk	Carves a clear niche around microscopy/OMERO-specific concepts (ROIs, high-content screening) with distinct triggers and minimal overlap risk against generic data or file skills.	5 / 5
	Total	17 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/biology/omero-integration/SKILL.md
Commit: a820c2f

Reviewed: 3 days ago

Table of Contents

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