# Integrate OMERO Microscopy Workflows

Microscopy teams need reliable access to OMERO data and analysis workflows. This skill provides practical Python patterns for connections, images, metadata, ROIs, tables, and batch scripts.

## Install

```bash
npx skillstore add davila7/omero-integration
```

## Metadata

- Status: approved
- Slug: davila7-omero-integration
- Skillstore revision: r2
- Version status: missing
- Tree hash: 4f66def462d4623d86cde68129b05b56f84065ec7e18790c826d3878ec373405
- Author: davila7
- GitHub username: davila7
- License: MIT
- Repository: https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/scientific/omero-integration
- Ref: c43861a65bb95efcae259cd161c9d6f4dc7eec6f
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: filesystem, env\_access, external\_commands, network
- Quality score: 77
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/davila7-omero-integration
- Manifest: https://skillstore.pages.dev/api/skills/davila7-omero-integration/manifest

## Capabilities

- Guide secure OMERO Python connections with credentials, sessions, group contexts, and connection cleanup.
- Retrieve projects, datasets, images, screens, plates, wells, and related metadata through BlitzGateway.
- Access pixel planes as NumPy arrays, configure rendering, create thumbnails, and generate derived images.
- Create, retrieve, and analyze ROI shapes, including intensity measurements within selected regions.
- Create annotations and OMERO tables for tags, key-value metadata, files, comments, and quantitative results.
- Design OMERO server scripts and batch workflows for repeated image processing and result storage.

## Use Cases

- Analyze screening images: Retrieve plate images, inspect pixel data, measure regions, and store quantitative results in OMERO tables.
- Standardize OMERO workflows: Create consistent connection, annotation, permission, and lifecycle patterns for shared imaging projects.
- Build server-side processing: Design parameterized OMERO scripts for authorized batch analysis, progress reporting, cleanup, and result publication.

## Prompt Templates

### Connect and list projects

```
Show a secure Python pattern to connect to OMERO at {host} and list projects. Use environment variables and always close the session.
```

### Retrieve dataset images

```
Create a workflow to retrieve images from OMERO dataset {dataset_id}. Include metadata fields, pagination, missing-object handling, and session cleanup.
```

### Measure ROI intensities

```
Plan an analysis for image {image_id} that retrieves ROIs, extracts channel {channel} pixels, calculates intensity statistics, and stores results in an OMERO table.
```

### Design an authorized batch pipeline

```
Design an OMERO server script that processes images from {dataset_id}, stores measurements in a table, handles failures, and reports progress. Include permission checks, idempotency, and a dry-run plan.
```

## Limitations

- Requires an accessible OMERO server, valid credentials, Python, omero-py, and compatible ZeroC Ice dependencies.
- Provides reference patterns, not a running connector or bundled automation service.
- Examples use placeholder identifiers and must be adapted to local permissions, namespaces, and data models.
- Administrative, deletion, and cross-group operations require explicit authorization and careful review before execution.

## Best Practices

- Use environment variables or protected configuration files for credentials, and never place real passwords in prompts or generated source.
- Confirm object identifiers, ownership, group context, and permissions before write, delete, or administrative operations.
- Sanitize downloaded filenames, close OMERO services, and process large pixel datasets in bounded chunks or generators.

## Anti Patterns

- Do not execute deletion, impersonation, or cross-group actions without explicit authorization and a reviewed object list.
- Do not trust server-provided filenames when writing downloads to the local filesystem.
- Do not load entire multidimensional image collections into memory when streaming or tiled access is available.

## Security Audit

- Audited at: 2026-07-23T14:31:33.3\+00:00
- Summary: Most findings are false positives caused by Markdown backticks, OMERO identifiers, documentation links, and safe configuration examples. Two filesystem examples have path traversal risks because server-provided filenames are joined directly to local download directories before writing. No prompt injection, concealed payload, data-exfiltration intent, or unauthorized command execution was found.

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