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Fast CLI/Python queries to 20+ bioinformatics databases.
Passed 22 of 23 test cases with the skill, and 4 of 23 without it.
and 37 more in the full report
18 fixed4 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 18 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a Python invocation to introduce a nucleotide substitution 'c.4G>T' into the sequence 'ATCGCTAAGCT' and write the resulting sequence directly to a FASTA file named mutated.fasta.
| Checked | Without skill | With skill |
|---|---|---|
| The code calls gget.mutate. | Missed | Passed |
| The output parameter specifies mutated.fasta. | Missed | Passed |
The instructions your model reads when the skill loads.
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, viral sequences, expression data, disease associations, and mouse tissue/cell specificity metrics through a consistent interface. Most 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. Guidance here targets gget 0.30.5 (PyPI current as of 2026-06-07). For reproducible work, pin gget==0.30.5; for broken upstream database adapters, update gget after checking release notes.
Install gget in a clean virtual environment to avoid conflicts:
# Reproducible install targeting this skill
uv venv .venv
source .venv/bin/activate
uv pip install "gget==0.30.5"
# In Python/Jupyter
import gget
Basic usage pattern for all modules:
# Command-line
gget <module> [arguments] [options]
# Python
gget.module(arguments, options)
Most modules return:
-csv flagCommon flags across modules:
-o/--out: Save results to filetest cases passed, vs 4 / 23 without
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