cellxgene-census
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
Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census summary counts, source H5AD URIs/downloads, embeddings, spatial Census data, or reference atlas comparisons across organisms, tissues, diseases, assays, and cell types. For analyzing your own local single-cell data use scanpy, anndata, or scvi-tools.
- Package
- 5 files, 54 KB
- SKILL.md
- 1524 words, 12+ sections
- Code
- None. Instructions only.
- Allowed tools
ReadWriteEditBash- License
- MIT
- Compatibility
- Requires Linux or macOS, Python 3.10+ and network access to public HTTPS manifests and S3. Tested with Python 3.12, cellxgene-census 1.18.0 and TileDB-SOMA 2.3.0. Spatial export needs the spatial extra; ML needs tiledbsoma-ml and PyTorch. No Census credentials required.
SKILL.md covers: CZ CELLxGENE Census · Overview · When to Use This Skill · Installation and Setup · Core Workflow Patterns · Key Concepts and Best Practices · Always Filter for Primary Data · Specify Census Version for Reproducibility · Estimate Query Size Before Loading · Query axes consume memory too; stream expression if the matrix will not fit. · Use tissue_general for Broader Groupings · Broader grouping
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 13 KB |
references/api_access.md | doc | 5.8 KB |
references/census_schema.md | doc | 9.3 KB |
references/common_patterns.md | doc | 15 KB |
references/core_workflow_patterns.md | doc | 11 KB |
External hosts referenced
chanzuckerberg.github.io arxiv.org census.cellxgene.cziscience.com github.com contrib.cellxgene.cziscience.com doi.org export.arxiv.org pypi.org scanpy.readthedocs.io single-cell-data.github.io
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-cellxgene-census-scan.json
- Badge for your README:
- Request a re-scan