omero-integration

omero-integration is a skill for Claude Code, Codex from synthetic-sciences/openscience. It costs 39 tokens per session (1,756 once invoked), scanned A, original, Apache-2.0.

A guide to OMERO, a platform for storing, viewing, and analysing microscopy images and their related information. It provides Python-based ways to access images, datasets, measurements, and annotations.

In plain words
What is it for?
Use it to retrieve images and datasets, analyse pixel data, create regions of interest, add annotations, store measurements, and run batch or high-content screening analyses.
Why use it?
It helps code interact with microscopy data kept on an OMERO server instead of handling image files and experiment records manually.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/synthetic-sciences/openscience/omero-integration
Any agent
npx skills add synthetic-sciences/openscience --skill omero-integration
Clone the repo
git clone --depth 1 https://github.com/synthetic-sciences/openscience

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for omero-integration

README.md
[![agentmods](https://agentmods.dev/badge/skills/synthetic-sciences/openscience/omero-integration.svg)](https://agentmods.dev/skills/synthetic-sciences/openscience/omero-integration)
Your own site
<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/omero-integration"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/omero-integration.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,756 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.01756
Opus 5 $0.00019 $0.00878
Sonnet 5 $0.00008 $0.00351
Haiku 4.5 $0.00004 $0.00176

Measured 4d ago against content hash 438f479b8794, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

omero-integration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

backend/cli/skills/biology/omero-integration/SKILL.md · 251 lines

How it starts

The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OMERO Integration

Overview

OMERO is an open-source platform for managing, visualizing, and analyzing microscopy images and metadata. Access images via Python API, retrieve datasets, analyze pixels, manage ROIs and annotations, for high-content screening and microscopy workflows.

When to Use This Skill

This skill should be used when:

  • Working with OMERO Python API (omero-py) to access microscopy data
  • Retrieving images, datasets, projects, or screening data programmatically
  • Analyzing pixel data and creating derived images
  • Creating or managing ROIs (regions of interest) on microscopy images
  • Adding annotations, tags, or metadata to OMERO objects
  • Storing measurement results in OMERO tables
  • Creating server-side scripts for batch processing
  • Performing high-content screening analysis

Core Capabilities

This skill covers eight major capability areas. Each is documented in detail in the references/ directory:

1. Connection & Session Management

File: references/connection.md

Establish secure connections to OMERO servers, manage sessions, handle authentication, and work with group contexts. Use this for initial setup and connection patterns.

Common scenarios:

  • Connect to OMERO server with credentials
  • Use existing session IDs
  • Switch between group contexts
  • Manage connection lifecycle with context managers

2. Data Access & Retrieval

File: references/data_access.md

Navigate OMERO's hierarchical data structure (Projects → Datasets → Images) and screening data (Screens → Plates → Wells). Retrieve objects, query by attributes, and access metadata.

Common scenarios:

  • List all projects and datasets for a user
  • Retrieve images by ID or dataset
  • Access screening plate data
  • Query objects with filters

3. Metadata & Annotations

File: references/metadata.md

Create and manage annotations including tags, key-value pairs, file attachments, and comments. Link annotations to images, datasets, or other objects.

Read the full file on GitHub · 251 lines

Files

What ships with it

8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 251 lines · 39 tokens per session scan A 438f479b8794

Subscribe to this mod's changes

omero-integration is a skill published in the GitHub repository synthetic-sciences/openscience (3,432 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 1,756 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

imaging-data-commons

Query and download public cancer imaging data from NCI Imaging Data Commons. Invoke for any question about IDC collections, cancer imaging datasets, DICOM data access, radiology (CT, MR, PET) or pathology AI training sets, metadata queries, visualization, or license checks — even when the user doesn't explicitly…

K-Dense-AI/scientific-agent-skills · 75 tokens

lab-hardware-cad

Design custom laboratory hardware as parametric build123d models and export fabrication-ready STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research…

K-Dense-AI/scientific-agent-skills · 106 tokens

analytical-method-validation

Plan, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP / / , ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays…

K-Dense-AI/scientific-agent-skills · 281 tokens

anndata

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

K-Dense-AI/scientific-agent-skills · 63 tokens

bulk-rnaseq

End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and…

K-Dense-AI/scientific-agent-skills · 218 tokens

cirq

Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for…

K-Dense-AI/scientific-agent-skills · 67 tokens