scvi-tools
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Fits probabilistic models for single-cell omics, including scVI batch integration, scANVI annotation, totalVI CITE-seq, MultiVI RNA/ATAC integration, and posterior differential expression. Use for generative modeling, reference mapping, multimodal analysis, or model-based uncertainty; use scanpy for standard preprocessing and exploratory analysis.
- Package
- 9 files, 68 KB
- SKILL.md
- 1102 words, 9 sections
- Code
- None. Instructions only.
- License
- BSD-3-Clause license
- Compatibility
- Requires Python 3.12+ and scvi-tools with model-specific dependencies. CPU supported; accelerator requirements depend on PyTorch and hardware. Network access is needed for installation or optional dataset/genome downloads, not local model fitting.
SKILL.md covers: scvi-tools · Choose the model and its input contract · Workflow · Illustrative RNA workflow · Outputs and differential expression · SCVI normalized expression: a potentially dense cells-by-genes matrix. · This comparison is conditional on the fitted model and selected genes. · Installation and verification · Citing Scientific Agent Skills
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 10.0 KB |
references/differential-expression.md | doc | 6.9 KB |
references/models-atac-seq.md | doc | 5.6 KB |
references/models-multimodal.md | doc | 8.3 KB |
references/models-scrna-seq.md | doc | 7.7 KB |
references/models-spatial.md | doc | 8.9 KB |
references/models-specialized.md | doc | 6.4 KB |
references/theoretical-foundations.md | doc | 5.1 KB |
references/workflows.md | doc | 9.1 KB |
External hosts referenced
github.com docs.scvi-tools.org arxiv.org scviva-tools.readthedocs.io doi.org export.arxiv.org
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-scvi-tools-scan.json
- Badge for your README:
- Request a re-scan