A skill for using scvi-tools, a software framework for deep-learning analysis of single-cell biological data. It supports workflows such as combining datasets, correcting batch differences, and analyzing RNA, protein, DNA-accessibility, and spatial data.

Use it for single-cell RNA analysis, label transfer, batch correction, CITE-seq, multiome, ATAC-seq, spatial transcriptomics, and related workflows.

It helps choose and apply suitable models when biological datasets contain technical differences, multiple data types, or incomplete labels.

scvi-tools — Skill for Claude Code and Codex by Shoko-official

Install

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.

Any agent

npx skills add Shoko-official/Claude-Science-System-Prompts --skill scvi-tools

Clone the repo

git clone --depth 1 https://github.com/Shoko-official/Claude-Science-System-Prompts

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/shoko-official/claude-science-system-prompts/scvi-tools/github.svg)](https://agentmods.dev/skills/shoko-official/claude-science-system-prompts/scvi-tools)

Your own site

<a href="https://agentmods.dev/skills/shoko-official/claude-science-system-prompts/scvi-tools"><img src="https://agentmods.dev/badge/skills/shoko-official/claude-science-system-prompts/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/shoko-official/claude-science-system-prompts/scvi-tools"><img src="https://agentmods.dev/badge/skills/shoko-official/claude-science-system-prompts/scvi-tools.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 193 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,867 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 100% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.00193	$0.01867
Opus 5	$0.00097	$0.00933
Sonnet 5	$0.00039	$0.00373
Haiku 4.5	$0.00019	$0.00187

Measured 12d ago against content hash 03a69b32b77d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 12d ago.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/cluster_embed.py, scripts/differential_expression.py, scripts/integrate_datasets.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

100% identical to scvi-tools — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/scvi-tools/SKILL.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

scvi-tools Deep Learning Skill

This skill provides guidance for deep learning-based single-cell analysis using scvi-tools, the leading framework for probabilistic models in single-cell genomics.

How to Use This Skill

Identify the appropriate workflow from the model/workflow tables below
Read the corresponding reference file for detailed steps and code
Use scripts in scripts/ to avoid rewriting common code
For installation or GPU issues, consult references/environment_setup.md
For debugging, consult references/troubleshooting.md

When to Use This Skill

When scvi-tools, scVI, scANVI, or related models are mentioned
When deep learning-based batch correction or integration is needed
When working with multi-modal data (CITE-seq, multiome)
When reference mapping or label transfer is required
When analyzing ATAC-seq or spatial transcriptomics data
When learning latent representations of single-cell data

Model Selection Guide

Data Type	Model	Primary Use Case
scRNA-seq	scVI	Unsupervised integration, DE, imputation
scRNA-seq + labels	scANVI	Label transfer, semi-supervised integration
CITE-seq (RNA+protein)	totalVI	Multi-modal integration, protein denoising
scATAC-seq	PeakVI	Chromatin accessibility analysis
Multiome (RNA+ATAC)	MultiVI	Joint modality analysis
Spatial + scRNA reference	DestVI	Cell type deconvolution
RNA velocity	veloVI	Transcriptional dynamics
Cross-technology	sysVI	System-level batch correction

Workflow Reference Files

Workflow	Reference File	Description
Environment Setup	`references/environment_setup.md`	Installation, GPU, version info
Data Preparation	`references/data_preparation.md`	Formatting data for any model
scRNA Integration	`references/scrna_integration.md`	scVI/scANVI batch correction
ATAC-seq Analysis	`references/atac_peakvi.md`	PeakVI for accessibility
CITE-seq Analysis	`references/citeseq_totalvi.md`	totalVI for protein+RNA
Multiome Analysis	`references/multiome_multivi.md`	MultiVI for RNA+ATAC
Spatial Deconvolution	`references/spatial_deconvolution.md`	DestVI spatial analysis
Label Transfer	`references/label_transfer.md`	scANVI reference mapping
scArches Mapping	`references/scarches_mapping.md`	Query-to-reference mapping
Batch Correction	`references/batch_correction_sysvi.md`	Advanced batch methods
RNA Velocity	`references/rna_velocity_velovi.md`	veloVI dynamics
Troubleshooting	`references/troubleshooting.md`	Common issues and solutions

Read the full file on GitHub · 156 lines

Files

What ships with it

20 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.

Changes

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.

12d ago First seen · 156 lines · 193 tokens per session scan A 03a69b32b77d

Subscribe to this mod's changes

scvi-tools is a skill published in the GitHub repository Shoko-official/Claude-Science-System-Prompts (10 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 193 tokens to every session and 1,867 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to scvi-tools, differing in 0 lines, and is treated as a copy.

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