gget

A command-line tool and Python package for looking up information in more than 20 bioinformatics databases. Bioinformatics databases store data about genes, DNA and protein sequences, structures, expression, and diseases.

In plain words
What is it for?
Use it to find gene information, run BLAST sequence searches, inspect AlphaFold protein structures, and perform enrichment analysis from the command line or Python.
Why use it?
It removes the need to learn a different query method for each database when doing quick research or exploration.

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

Made for: Claude Code, Codex.

Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,017 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00066 $0.07017
Opus 5 $0.00033 $0.03508
Sonnet 5 $0.00013 $0.01403
Haiku 4.5 $0.00007 $0.00702

Measured 3d ago against content hash 85e2fe27336e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gget 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 3d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/batch_sequence_analysis.py, scripts/enrichment_pipeline.py, scripts/gene_analysis.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

- `-d/--download`: Download files (requires curl)
Origin

Copies of this mod

5 near-identical copies found in the catalogue:

  • gget — 100% identical, 3 lines differ
  • gget — 100% identical, 3 lines differ
  • gget — 100% identical, 3 lines differ
  • gget — 97% identical, 7 lines differ
  • gget — 94% identical, 5 lines differ
backend/cli/skills/biology/gget/SKILL.md · 871 lines

How it starts

The opening of the file, as written. The whole thing — 871 lines — stays where its author put it; the contents beside it link to each section on GitHub.

gget

Overview

gget is a command-line bioinformatics tool and Python package providing unified access to 20+ genomic databases and analysis methods. Query gene information, sequence analysis, protein structures, expression data, and disease associations through a consistent interface. All gget modules work both as command-line tools and as Python functions.

Important: The databases queried by gget are continuously updated, which sometimes changes their structure. gget modules are tested automatically on a biweekly basis and updated to match new database structures when necessary.

Installation

Install gget in a clean virtual environment to avoid conflicts:

# Using uv (recommended)
uv uv pip install gget

# Or using pip
uv pip install --upgrade gget

# In Python/Jupyter
import gget

Quick Start

Basic usage pattern for all modules:

# Command-line
gget <module> [arguments] [options]

# Python
gget.module(arguments, options)

Most modules return:

  • Command-line: JSON (default) or CSV with -csv flag
  • Python: DataFrame or dictionary

Common flags across modules:

  • -o/--out: Save results to file
  • -q/--quiet: Suppress progress information
  • -csv: Return CSV format (command-line only)

Module Categories

1. Reference & Gene Information

gget ref - Reference Genome Downloads

Retrieve download links and metadata for Ensembl reference genomes.

Parameters:

  • species: Genus_species format (e.g., 'homo_sapiens', 'mus_musculus'). Shortcuts: 'human', 'mouse'
  • -w/--which: Specify return types (gtf, cdna, dna, cds, cdrna, pep). Default: all
  • -r/--release: Ensembl release number (default: latest)
  • -l/--list_species: List available vertebrate species
  • -liv/--list_iv_species: List available invertebrate species
  • -ftp: Return only FTP links
  • -d/--download: Download files (requires curl)

Examples:

# List available species
gget ref --list_species

# Get all reference files for human
gget ref homo_sapiens

# Download only GTF annotation for mouse
gget ref -w gtf -d mouse

Read the full file on GitHub · 871 lines

Files

What ships with it

6 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. 3d ago First seen · 871 lines · 66 tokens per session scan A 85e2fe27336e

Subscribe to this mod's changes

gget is a skill published in the GitHub repository synthetic-sciences/openscience (3,385 stars, last pushed today), licensed Apache-2.0. It adds 66 tokens to every session and 7,017 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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