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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.

56

Quality

71%

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tessl review fix ./bundled/skills/omero-integration/SKILL.md
SKILL.md
Quality
Evals
Security

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-organized with excellent progressive disclosure pointing to real, one-level-deep reference files and executable connection examples. Its main weaknesses are redundant scenario/notes content and batch workflows that lack explicit validation checkpoints.

Suggestions

Add a validation/verification step to the batch workflows (e.g., after batch ROI analysis, confirm row counts in the OMERO table before proceeding).

Trim the per-capability 'Common scenarios' bullets and the Notes section, which duplicate content already in the reference files.

Add at least one inline runnable snippet for a non-connection capability (e.g., retrieving an image or adding a tag) so the body is actionable beyond connection setup.

DimensionReasoningScore

Conciseness

Mostly efficient, but the Overview restates the description, the per-capability 'Common scenarios' bullets (32 total) duplicate material in the reference files, and the Notes section repeats hierarchy facts already covered.

3 / 5

Actionability

Quick Start and Error Handling provide executable, copy-paste-ready BlitzGateway patterns plus an install command; the eight capability sections are descriptive and defer code to references, which is appropriate but leaves the body itself light on runnable examples.

4 / 5

Workflow Clarity

Three workflows are clearly numbered, but Workflows 2 and 3 are batch operations with no validation or verification checkpoint; per the rubric this caps workflow clarity at 3.

3 / 5

Progressive Disclosure

A clear overview routes to eight one-level-deep reference files, all of which exist and contain no further nested references; each capability is explicitly signaled with its file path and a 'Selecting the Right Capability' section aids navigation.

5 / 5

Total

15

/

20

Passed

Description

66%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 conveys a clear, fairly specific capability set for a microscopy data platform but lacks an explicit use-when trigger clause and does not name OMERO, the platform it targets. It is solid but stops short of the strongest examples.

Suggestions

Add an explicit 'Use when...' clause naming concrete trigger phrases (e.g., 'Use when working with OMERO servers, the omero-py API, or microscopy image data in OMERO').

Name OMERO directly in the description to sharpen distinctiveness and give users the most natural trigger term.

Tighten 'batch processing' to a concrete action with an object (e.g., 'batch-process images and screening plates').

DimensionReasoningScore

Specificity

Lists several concrete actions ('Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing') covering the domain well; minor gap as 'batch processing' is stated without an object.

4 / 5

Completeness

The 'what' is clear (microscopy data management platform plus five actions), but there is no explicit 'Use when...' clause; the trailing 'for high-content screening and microscopy workflows' only weakly implies when, capping completeness at 3 per the rubric.

3 / 5

Trigger Term Quality

Good coverage of domain-natural terms (microscopy, images, datasets, pixels, ROIs/annotations, high-content screening) but omits the most natural trigger 'OMERO' and file extensions like .ome.tif.

4 / 5

Distinctiveness Conflict Risk

The microscopy/HCS/ROI framing carves a mostly distinct niche with minor overlap risk from generic terms (images, datasets, batch processing); naming OMERO would further reduce conflict risk.

4 / 5

Total

15

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository

foryourhealth111-pixel/Vibe-Skills

Path

bundled/skills/omero-integration/SKILL.md

Reviewed

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