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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.

59

Quality

70%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

Quality

Content

57%Weight 40%Scale 1-3

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

A well-structured, progressively-disclosed skill body with solid navigation and connection examples, weakened by some redundancy and missing validation checkpoints in batch workflows.

Suggestions

Remove the Overview (it duplicates the description) and trim the Notes section to non-repeated facts to improve conciseness.

Add an explicit validation/verification step to Workflow 2 (Batch ROI Analysis) — e.g. verify ROI shapes loaded and non-empty before extracting intensities.

Include at least one small inline executable snippet for a non-connection capability (e.g. retrieving images from a dataset) so the body is actionable beyond connection setup.

DimensionReasoningScore

Conciseness

Mostly efficient with bullet-driven progressive disclosure, but the Overview duplicates the frontmatter description and the Notes section restates body content; it could be tightened, falling short of the lean level-3 anchor.

2 / 3

Actionability

Executable, copy-paste-ready connection code is present, but the body delegates the bulk of capability detail to references without code, so concrete guidance is incomplete rather than fully actionable.

2 / 3

Workflow Clarity

Three workflows are clearly sequenced with per-step reference pointers, but Workflow 2 is a batch operation with no validation/verification checkpoint, which caps workflow clarity at 2 per the batch-operations guideline.

2 / 3

Progressive Disclosure

The body is a clear overview with eight well-signaled one-level-deep references, all of which exist in references/; content is appropriately split and easy to navigate, matching the level-3 anchor.

3 / 3

Total

9

/

12

Passed

Description

82%Weight 40%Scale 1-3

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, specific description anchored in a clear domain niche with good natural trigger terms, held back only by the absence of an explicit 'Use when...' clause.

Suggestions

Add an explicit 'Use when...' clause, e.g. 'Use when working with OMERO servers, microscopy images, or high-content screening data via the omero-py API.'

Consider mentioning the concrete library/API name (omero-py / BlitzGateway) in the description to sharpen trigger matching.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing' — matching the multiple-specific-actions anchor.

3 / 3

Completeness

It clearly answers 'what' but lacks any explicit 'Use when...' trigger clause; per the judging guidelines a missing explicit trigger caps completeness at 2, not 1 because the 'what' is strong and the 'when' is only weakly implied by the domain framing.

2 / 3

Trigger Term Quality

Natural domain terms a user would actually say are well covered: 'microscopy', 'images', 'datasets', 'pixels', 'ROIs/annotations', 'high-content screening'.

3 / 3

Distinctiveness Conflict Risk

The microscopy/OMERO data-management niche is highly specific with distinct triggers, making conflict with other skills unlikely; it is not the generic level below.

3 / 3

Total

11

/

12

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

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
Reviewed

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