Skills omero-integration

📦

omero-integration

Name: omero-integration
Author: davila7

Content revision r2 Safe 📁 Filesystem access🔑 Env variables⚙️ External commands🌐 Network access

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.

Supports: Claude Codex Code(CC)

🥉 77 Bronze

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "omero-integration" from https://skillstore.io/skills/davila7-omero-integration.md and its manifest at https://skillstore.io/api/skills/davila7-omero-integration/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/davila7-omero-integration.md Signed manifest GET /api/skills/davila7-omero-integration/manifest Signed lockfile GET /api/skills/davila7-omero-integration/lockfile

Test it

Using "omero-integration". Connect to my OMERO server and summarize available projects.

Expected outcome:

A connection plan using protected OMERO environment variables
A project inventory with identifiers, owners, and groups
Session cleanup and connection error guidance

Using "omero-integration". Measure channel intensity for every rectangular ROI on an image.

Expected outcome:

A workflow that retrieves rectangles, reads the selected pixel plane, computes bounded-region statistics, and prepares table rows linked to the image.

Using "omero-integration". Design a batch analysis script for a large dataset.

Expected outcome:

A batch-script design with parameters, progress reporting, a result-table schema, permission checks, bounded processing, failure handling, and cleanup steps.

Security Audit

Safe

v9 • 7/23/2026 Open versioned report

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.

Files scanned

4,968

Lines analyzed

Review items

False positives ignored

Capability review items (2)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

Medium

references/advanced.md:157

Python file write/append

with open(file_path, 'wb') as f:

The example joins server-provided orig_file.getName() to a local directory without validation before writing. A crafted filename could escape the intended download directory.

Medium

references/metadata.md:223

Python file write/append

with open(file_path, 'wb') as f:

The example writes a server-provided annotation filename after a direct os.path.join without sanitization. Path separators or traversal segments could overwrite files outside the download directory.

Risk Factors

📁 Filesystem access (5)

references/advanced.md:157 references/advanced.md:144 references/metadata.md:223 references/metadata.md:210 references/scripts.md:635

🔑 Env variables (6)

references/connection.md:315 references/connection.md:316 references/connection.md:317 references/connection.md:318 references/connection.md:301 references/connection.md:302

⚙️ External commands (34)

🌐 Network access (4)

SKILL.md:233 SKILL.md:234 SKILL.md:235 SKILL.md:236

Audited by: codex View Audit History →

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Academic citations (APA · BibTeX · CFF)

APA citation

davila7. (2026). omero-integration security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-omero-integration/audits/9

BibTeX citation

@techreport{davila7-davila7-omero-integration-2026,
  author = {davila7},
  title = {omero-integration security audit report (audit version 9)},
  institution = {Skillstore},
  year = {2026},
  number = {9},
  url = {https://skillstore.io/skills/davila7-omero-integration/audits/9},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "omero-integration security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
  - name: "davila7"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/davila7-omero-integration/audits/9"
identifiers:
  - type: other
    value: "skillstore:davila7-omero-integration:audit:9"
    description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score

Author / source Skillstore Score Evidence Confidence Skillstore usage Updated

davila7 Recommended Current

davila7-omero-integration

Skillstore Score 77

Evidence Confidence High

Skillstore usage 6

Updated

2026-08-21

K-Dense-AI

k-dense-ai-omero-integration

Skillstore Score 38

Evidence Confidence Medium

Skillstore usage 10

Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

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.

Try These Prompts

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.

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.

Avoid

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.

Frequently Asked Questions

Does this skill connect to OMERO directly?

No. It provides guidance and code patterns. The user or agent must run them with authorized network access and required dependencies.

How should I provide OMERO credentials?

Use environment variables, a protected configuration file, or an approved secret manager. Never place real credentials in prompts or committed files.

Can the generated workflows modify OMERO data?

Yes. Annotation, table, ROI, rendering, and deletion examples can change server data when executed with sufficient permissions.

Does it support high-content screening data?

Yes. The references cover screens, plates, wells, well samples, images, and table-based measurement results.

Does the skill install omero-py automatically?

No. It documents an installation command, but installation and dependency management remain explicit user actions.

Which operations need additional review?

Review downloads, deletions, administrator actions, user substitution, cross-group queries, and all writes against local permissions and retention policies.