Agent Skills › advaitpaliwal/feynman › scvi-tools

scvi-tools

GitHub

用于执行 scvi-tools 单细胞分析工作流，涵盖模型训练、潜变量嵌入、批次校正、差异表达及细胞注释等任务。强调可重复性，要求记录环境参数、保存预处理与训练日志，并验证数据质量。

skills/scvi-tools/SKILL.md advaitpaliwal/feynman

触发场景

需要进行单细胞 RNA 测序数据分析请求 scVI 或 scANVI 模型设置需要执行批次校正或差异表达分析要求生成可复现的 AnnData 分析结果

安装

npx skills add advaitpaliwal/feynman --skill scvi-tools -g -y

更多选项

不安装直接使用

npx skills use advaitpaliwal/feynman@scvi-tools

指定 Agent (Claude Code)

npx skills add advaitpaliwal/feynman --skill scvi-tools -a claude-code -g -y

安装 repo 全部 skill

npx skills add advaitpaliwal/feynman --all -g -y

预览 repo 内 skill

npx skills add advaitpaliwal/feynman --list

SKILL.md

Frontmatter

{
    "name": "scvi-tools",
    "description": "Run scvi-tools single-cell workflows. Use when a task asks for scVI\/scANVI setup, latent embeddings, batch correction, differential expression, cell annotation, or reproducible AnnData analysis."
}

scvi-tools

Use this skill for reproducible scvi-tools analysis.

Workflow:

Record AnnData path, organism, assay, batch keys, label keys, covariates, train/test split, and filtering choices.
Verify Python environment, GPU/CPU route, package version, and data availability before training.
Save preprocessing notebook, model parameters, training logs, latent embeddings, differential-expression tables, and plots.
Check batch mixing, biological separation, marker consistency, and sensitivity to preprocessing choices.
Attach exact commands and artifact paths to the final summary.

Keep raw counts, normalized values, and model-derived latent variables clearly separated.