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Query the Sequence Read Archive (SRA), retrieve scientific publications, and analyze genomics metadata using the SRAgent toolkit. Supports accession conversion (GSE→SRX→SRR), BigQuery metadata queries, manuscript downloads from multiple sources, and scRNA-seq technology identification.
Passed 11 of 15 test cases with the skill, and 3 of 15 without it.
and 11 more in the full report
11 fixed5 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
What Python one-liner can I run to verify that SRAgent settings load properly and print the configured default model?
| Checked | Without skill | With skill |
|---|---|---|
| Imports load_settings from SRAgent.agents.utils to verify configuration. | Missed | Passed |
The instructions your model reads when the skill loads.
SRAgent is an agentic workflow system for working with the NCBI Sequence Read Archive (SRA) and Gene Expression Omnibus (GEO) databases. It automates literature discovery, metadata extraction, and manuscript retrieval for genomics datasets.
SRAgent requires Python ≥3.11. Check to see if SRAgent is already installed:
which SRAgent
If SRAgent is not installed, follow the instructions below.
Install using uv:
# Clone the repository
git clone https://github.com/ArcInstitute/SRAgent.git
cd SRAgent
# Create and activate virtual environment with uv
uv venv
source .venv/bin/activate
# Install the package
uv pip install .
Verify installation:
SRAgent --help
test cases passed, vs 3 / 15 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.