geo-database

geo-database is a skill for Claude Code, Codex from AndyZhuang/Opentest. It costs 47 tokens per session (5,994 once invoked), scanned A, a copy of geo-database, MIT.

A tool for searching GEO, the Gene Expression Omnibus, a public repository of gene-expression and genomics experiments. It can find studies and samples and retrieve their raw or processed files.

In plain words
What is it for?
Use it to find microarray or RNA-sequencing datasets, download experiment files, inspect sample metadata, and support transcriptomics analysis.
Why use it?
It removes the need to navigate GEO's large collection manually and helps connect a study with its samples, platforms, and downloadable data. This makes public expression datasets easier to reuse.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to find microarray or RNA-sequencing datasets, download experiment files, inspect sample metadata, and support transcriptomics analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/andyzhuang/opentest/geo-database
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.

Any agent
npx skills add AndyZhuang/Opentest --skill geo-database
Clone the repo
git clone --depth 1 https://github.com/AndyZhuang/Opentest

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 geo-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/andyzhuang/opentest/geo-database.svg)](https://agentmods.dev/skills/andyzhuang/opentest/geo-database)
Your own site
<a href="https://agentmods.dev/skills/andyzhuang/opentest/geo-database"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/geo-database.svg" alt="Measured on agentmods" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,994 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 86% copy Near-identical to another mod 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 5.1 $0.00047 $0.05994
Opus 5 $0.00023 $0.02997
Sonnet 5 $0.00009 $0.01199
Haiku 4.5 $0.00005 $0.00599

Measured 4d ago against content hash 45dd249dbb16, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

geo-database scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

**Using wget or curl for Downloads:**
Origin

This is a copy

86% identical to geo-database — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/labclaw/literature/geo-database/SKILL.md · 815 lines

How it starts

The opening of the file, as written. The whole thing — 815 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GEO Database

Overview

The Gene Expression Omnibus (GEO) is NCBI's public repository for high-throughput gene expression and functional genomics data. GEO contains over 264,000 studies with more than 8 million samples from both array-based and sequence-based experiments.

When to Use This Skill

This skill should be used when searching for gene expression datasets, retrieving experimental data, downloading raw and processed files, querying expression profiles, or integrating GEO data into computational analysis workflows.

Core Capabilities

1. Understanding GEO Data Organization

GEO organizes data hierarchically using different accession types:

Series (GSE): A complete experiment with a set of related samples

  • Example: GSE123456
  • Contains experimental design, samples, and overall study information
  • Largest organizational unit in GEO
  • Current count: 264,928+ series

Sample (GSM): A single experimental sample or biological replicate

  • Example: GSM987654
  • Contains individual sample data, protocols, and metadata
  • Linked to platforms and series
  • Current count: 8,068,632+ samples

Platform (GPL): The microarray or sequencing platform used

  • Example: GPL570 (Affymetrix Human Genome U133 Plus 2.0 Array)
  • Describes the technology and probe/feature annotations
  • Shared across multiple experiments
  • Current count: 27,739+ platforms

DataSet (GDS): Curated collections with consistent formatting

  • Example: GDS5678
  • Experimentally-comparable samples organized by study design
  • Processed for differential analysis
  • Subset of GEO data (4,348 curated datasets)
  • Ideal for quick comparative analyses

Profiles: Gene-specific expression data linked to sequence features

  • Queryable by gene name or annotation
  • Cross-references to Entrez Gene
  • Enables gene-centric searches across all studies

2. Searching GEO Data

GEO DataSets Search:

Search for studies by keywords, organism, or experimental conditions:

from Bio import Entrez

# Configure Entrez (required)
Entrez.email = "[email protected]"

# Search for datasets
def search_geo_datasets(query, retmax=20):
    """Search GEO DataSets database"""
    handle = Entrez.esearch(
        db="gds",
        term=query,
        retmax=retmax,
        usehistory="y"
    )
    results = Entrez.read(handle)
    handle.close()
    return results

# Example searches
results = search_geo_datasets("breast cancer[MeSH] AND Homo sapiens[Organism]")
print(f"Found {results['Count']} datasets")

# Search by specific platform
results = search_geo_datasets("GPL570[Accession]")

# Search by study type
results = search_geo_datasets("expression profiling by array[DataSet Type]")

Read the full file on GitHub · 815 lines

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 · 815 lines · 47 tokens per session scan A 45dd249dbb16

Subscribe to this mod's changes

geo-database is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 5mo ago), licensed MIT. It adds 47 tokens to every session and 5,994 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 86% identical to geo-database, differing in 6 lines, and is treated as a copy.

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