
Scvi Tools
Wire single-cell RNA-seq analysis and probabilistic latent models into agent-assisted Python notebooks or batch pipelines.
Overview
scvi-tools is an agent skill for the Build phase that helps solo builders implement single-cell variational inference workflows with the scVI Python library.
Install
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill scvi-toolsWhat is this skill?
- Guides use of scVI-family models for single-cell expression and multimodal assays
- Covers latent representation, batch correction, and differential expression workflows
- Maps to Python scientific stack patterns (AnnData, PyTorch-backed variational inference)
- Useful when agents must pick the right model class instead of generic sklearn defaults
- Apache 2.0–licensed upstream tooling suitable for research and internal analytics products
Adoption & trust: 1.1k installs on skills.sh; 19.6k GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need trustworthy single-cell integration or latent-space analysis but your agent keeps proposing generic ML steps that ignore AnnData and scvi-tools APIs.
Who is it for?
Indie builders adding omics analytics, lab tooling, or research assistants where scVI is already on the roadmap.
Skip if: Teams with no single-cell data, no Python GPU environment, or problems solvable with simple SQL aggregates—skip until you have count matrices and a clear assay.
When should I use this skill?
User asks for scVI, scANVI, totalVI, single-cell integration, or AnnData training code using scvi-tools.
What do I get? / Deliverables
After the skill runs, you get scaffolded Python that uses scvi-tools model classes, training loops, andAnnData conventions appropriate to your assay type.
- Python training or inference script using scvi-tools APIs
- Notebook or module outline for integration and downstream DE/export steps
Recommended Skills
Journey fit
Canonical shelf is Build because the skill supports implementing analysis code and model training rather than market research or production incident response. Backend fits computational workflows, AnnData/scanpy-style pipelines, and training or inference scripts agents generate alongside your product data layer.
How it compares
Use for library-specific scVI workflows instead of asking the agent for hand-rolled PCA on raw counts.
Common Questions / FAQ
Who is scvi-tools for?
Solo and indie developers building Python data or research products that analyze single-cell or related high-dimensional biological count data with variational models.
When should I use scvi-tools?
Use it in Build (backend notebooks and batch jobs) when integrating batches, training latent models, or exporting embeddings; it is not aimed at Validate landing pages or Operate on-call runbooks.
Is scvi-tools safe to install?
Treat it like any third-party scientific dependency: review the Security Audits panel on this Prism page, pin versions, and run training in isolated environments with your own data-handling policies.
SKILL.md
READMESKILL.md - Scvi Tools
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