sragent
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. Use when working with SRA/GEO datasets, finding publications, or analyzing single-cell sequencing experiments.
npx skills add BioTender-max/awesome-bio-agent-skills --skill claude-skill --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# SRAgent: Sequence Read Archive Data and Publication Retrieval ## Overview 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. ## Setup Instructions ### 1. Install SRAgent SRAgent requires Python ≥3.11. Check to see if SRAgent is already installed: ```bash which SRAgent ``` If SRAgent is not installed, follow the instructions below. Install using `uv`: ```bash # 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: ```bash SRAgent --help ``` ### 2. Configure environment variables The following environment variables are required: - `OPENAI_API_KEY=sk-openai-...` - Needed to use OpenAI models - `ANTHROPIC_API_KEY=sk-ant-...` - Needed to use Claude models - `DYNACONF` - Needed to switch between Claude and OpenAI models - `EMAIL=user@example.com` - Needed for using the Entrez API - `NCBI_API_KEY=your-ncbi-key` - Optional f
- Overview
- Setup Instructions
- 1. Install SRAgent
- 2. Configure environment variables
- 3. Configure Settings
- 4. Verify Setup
- Core Capabilities
- 1. Accession Conversion
- 2. Metadata Extraction
- 3. BigQuery Analysis
- 4. Publication Retrieval
- When to Use This Skill
- Available Commands
- Command 1: SRAgent entrez
which SRAgent 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 . SRAgent --help
What does the sragent skill do?
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. Use when working with SRA/GEO datasets, finding publications, or analyzing single-cell sequencing experiments.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill claude-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.