Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
72
62%
Does it follow best practices?
Impact
88%
1.49xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/omero-integration/SKILL.mdImage processing pipeline with physical dimensions
Context manager connection
0%
100%
Default port 4064
100%
100%
Env var credentials
100%
100%
getPrimaryPixels plane access
100%
60%
0-indexed channel pixel access
100%
100%
Generator for image creation
100%
100%
createImageFromNumpySeq
100%
100%
Physical size with LengthI
100%
50%
saveObject for pixel update
62%
100%
Error handling
100%
100%
uv pip install
0%
0%
ROI creation, intensity measurement, and OMERO tables
omero.model.RoiI creation
100%
100%
rdouble/rint/rstring for shape props
100%
100%
rgba_to_int for colors
100%
100%
getShapeStatsRestricted
0%
100%
getRoiService
0%
100%
OMERO table initialization
100%
100%
Correct column types
0%
100%
StringColumn with max_length
0%
0%
table.close() called
100%
100%
FileAnnotationI table linking
100%
100%
BlitzGateway context manager
0%
100%
Structured metadata annotations and cross-group data access
Cross-group query setOmeroGroup
100%
100%
MapAnnotationWrapper usage
0%
100%
NSCLIENTMAPANNOTATION namespace
0%
0%
Custom namespace reverse domain
25%
100%
createFileAnnfromLocalFile
0%
100%
CSV MIME type
75%
100%
linkAnnotation
0%
100%
Env var credentials
100%
100%
BlitzGateway context manager
0%
100%
metadata_design.md content
85%
100%
b58ad7e
Table of Contents
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.