Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
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.
npx skills add K-Dense-AI/scientific-agent-skills --skill scvi-toolsgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/scvi-tools)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/scvi-tools"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/scvi-tools/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/scvi-tools"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/scvi-tools.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.02263 |
| Opus 5 | $0.00032 | $0.01131 |
| Sonnet 5 | $0.00013 | $0.00453 |
| Haiku 4.5 | $0.00006 | $0.00226 |
Grade A, and why
scvi-tools scanned grade A with 0 findings 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 8d ago.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
8 near-identical copies found in the catalogue:
- scvi-tools — 89% identical, 20 lines differ
- scvi-tools — 81% identical, 37 lines differ
- scvi-tools — 81% identical, 36 lines differ
- scvi-tools — 80% identical, 38 lines differ
- scvi-tools — 80% identical, 37 lines differ
- scvi-tools — 80% identical, 37 lines differ
- scvi-tools — 75% identical, 40 lines differ
- scvi-tools — 75% identical, 40 lines differ
How it starts
The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
scvi-tools
Overview
scvi-tools is a comprehensive Python framework for probabilistic models in single-cell genomics. Built on PyTorch and PyTorch Lightning, it provides deep generative models using variational inference for analyzing diverse single-cell data modalities. Current stable release: scvi-tools 1.4.3 (May 2026).
Model namespaces matter: core models (scVI, scANVI, totalVI, MultiVI, PeakVI, AUTOZI, CondSCVI, DestVI, LinearSCVI, AmortizedLDA, JaxSCVI) live under scvi.model. Most other models (VeloVI, contrastiveVI, CellAssign, PoissonVI, scBasset, MrVI, MethylVI/MethylANVI, CytoVI, SysVI, Decipher, gimVI, scVIVA, ResolVI, Stereoscope, Solo, totalANVI, DIAGVI) live under scvi.external. The reference files specify the correct namespace per model.
When to Use This Skill
Use this skill when:
- Analyzing single-cell RNA-seq data (dimensionality reduction, batch correction, integration)
- Working with single-cell ATAC-seq or chromatin accessibility data
- Integrating multimodal data (CITE-seq, multiome, paired/unpaired datasets)
- Analyzing spatial transcriptomics data (deconvolution, spatial mapping)
- Performing differential expression analysis on single-cell data
- Conducting cell type annotation or transfer learning tasks
- Working with specialized single-cell modalities (methylation, cytometry, RNA velocity)
- Building custom probabilistic models for single-cell analysis
Core Capabilities
scvi-tools provides models organized by data modality:
1. Single-Cell RNA-seq Analysis
Core models for expression analysis, batch correction, and integration. See references/models-scrna-seq.md for:
- scVI: Unsupervised dimensionality reduction and batch correction
- scANVI: Semi-supervised cell type annotation and integration
- AUTOZI: Zero-inflation detection and modeling
- VeloVI: RNA velocity analysis
- contrastiveVI: Perturbation effect isolation
2. Chromatin Accessibility (ATAC-seq)
Models for analyzing single-cell chromatin data. See references/models-atac-seq.md for:
- PeakVI: Peak-based ATAC-seq analysis and integration
- PoissonVI: Quantitative fragment count modeling
- scBasset: Deep learning approach with motif analysis
What ships with it
8 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.
- references/differential-expression.md 14 KB
- references/models-atac-seq.md 9.8 KB
- references/models-multimodal.md 12 KB
- references/models-scrna-seq.md 10 KB
- references/models-spatial.md 12 KB
- references/models-specialized.md 10.0 KB
- references/theoretical-foundations.md 11 KB
- references/workflows.md 13 KB
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.
- 8d ago First seen · 218 lines · 65 tokens per session scan A 8426ebdb26da
scvi-tools is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,469 stars, last pushed today), licensed MIT. It adds 65 tokens to every session and 2,263 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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