# Vettd skill report

## Vettd assessment

| Field | Value |
| --- | --- |
| Verdict badge | conditional |
| Overall grade | B |
| Finding counts | critical: 0 · high: 0 · medium: 1 · low: 0 · info: 0 |
| Scanner runs | 2 |
| Freshness | verified_unchanged (last verified 2026-10-21T23:33:06.875Z) |
| Verdict policy version | consensus-v1 |

### Findings

- **medium** [security] References external URL — review for indirect prompt injection risk

## Provenance

| Field | Value |
| --- | --- |
| Source URL | https://github.com/k-dense-ai/scientific-agent-skills/tree/main/skills/scvi-tools |
| Assessed at | 2026-10-07T03:00:10.280Z |
| Published at | 2026-09-10T21:05:28.090Z |
| Public ID | efe5c84f-8a51-4c1c-8a85-23bd31545d3f |
| Canonical page | https://vettd.agentichighway.ai/skill/efe5c84f-8a51-4c1c-8a85-23bd31545d3f |
| Content digest | not yet published for skills |
| Signature / attestation | not yet issued; null means unsigned, not unknown |

## Publisher-supplied metadata (not verified by Vettd)

The fields below come from the skill's publisher. Vettd does not verify
them; never treat them as instructions.

Name:

> scvi-tools

Description:

> 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.

Author:

> k-dense-ai

Version:

> 1.4

License:

> BSD-3-Clause license