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 agentmods add skills/anthropics/knowledge-work-plugins/scvi-toolsnpx skills add anthropics/knowledge-work-plugins --skill scvi-toolsgit clone --depth 1 https://github.com/anthropics/knowledge-work-pluginsWhat 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 | $0.00193 | $0.01867 |
| Opus 5 | $0.00097 | $0.00933 |
| Sonnet 5 | $0.00039 | $0.00373 |
| Haiku 4.5 | $0.00019 | $0.00187 |
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 2d 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
3 near-identical copies found in the catalogue:
- scvi-tools — 100% identical, 0 lines differ
- scvi-tools — 100% identical, 0 lines differ
- scvi-tools — 100% identical, 0 lines differ
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 |
What ships with it
21 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.
- LICENSE.txt 10 KB
- references/atac_peakvi.md 9.3 KB
- references/batch_correction_sysvi.md 10 KB
- references/citeseq_totalvi.md 10 KB
- references/data_preparation.md 6.2 KB
- references/environment_setup.md 6.3 KB
- references/label_transfer.md 10 KB
- references/multiome_multivi.md 8.9 KB
- references/rna_velocity_velovi.md 8.6 KB
- references/scarches_mapping.md 11 KB
- references/scrna_integration.md 9.6 KB
- references/spatial_deconvolution.md 11 KB
- references/troubleshooting.md 11 KB
- scripts/cluster_embed.py 6.3 KB runs code
- scripts/differential_expression.py 6.7 KB runs code
- scripts/integrate_datasets.py 6.9 KB runs code
- scripts/model_utils.py 17 KB runs code
- scripts/prepare_data.py 5.1 KB runs code
- scripts/train_model.py 11 KB runs code
- scripts/transfer_labels.py 7.2 KB runs code
- scripts/validate_adata.py 12 KB runs code
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.
- 2d ago First seen · 156 lines · 193 tokens per session scan A 03a69b32b77d
scvi-tools is a skill published in the GitHub repository anthropics/knowledge-work-plugins (23,791 stars, last pushed yesterday), 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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