scvelo
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
SkillSpector found no issues but could not fully inspect the package, usually because SKILL.md refers to a file that is not present, so it fails closed to CAUTION instead of SAFE. Read it as "not fully checked", not as a finding. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Performs RNA velocity analysis with scVelo from spliced and unspliced single-cell RNA counts. Fits deterministic or dynamical models, examines gene phase portraits, builds velocity graphs, estimates relative latent time, and ranks velocity-associated genes. Use for directional trajectory hypotheses and kinetic-model diagnostics alongside Scanpy; velocity alone does not establish cell fate or causal drivers.
- Package
- 3 files, 34 KB
- SKILL.md
- 1467 words, 12+ sections
- Code
- Python (1)
- License
- BSD-3-Clause
- Compatibility
- Requires Python 3.13 for the tested stack with scvelo 0.3.4, scanpy 1.12.4, anndata 0.13.4, numpy 2.5.3 and pandas 2.3.3. Loom import requires loompy. Local H5AD analysis needs no network or credentials. The default stochastic solver is incompatible with NumPy 2.
SKILL.md covers: scVelo RNA Velocity · When to use · Tested environment and compatibility · Input contract · Run the maintained workflow · Import a loom and align its raw counts to an existing annotation file: · Inspect the evidence before interpretation · Candidate kinetic genes, not experimentally established drivers. · This ranks group-associated velocities, not causal influence or condition DE. · Output interpretation · Troubleshooting · Sources and verification scope
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 12 KB |
references/velocity_models.md | doc | 9.2 KB |
scripts/rna_velocity_workflow.py | script | 13 KB |
External hosts referenced
scvelo.readthedocs.io github.com anndata.readthedocs.io cellrank.readthedocs.io doi.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-scvelo-scan.json
- Badge for your README:
- Request a re-scan