dask
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
The two scanners disagree: Cisco found nothing and SkillSpector says do not install. One of them has a blind spot here; read the skill before trusting either. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Scales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. Covers DataFrames, Arrays, Bags, Futures, chunking, schedulers, and distributed diagnostics. Use for partitioned file processing, scientific array computation, or parallel tasks whose memory and dependency structure require Dask.
- Package
- 8 files, 95 KB
- SKILL.md
- 2191 words, 12+ sections
- Code
- None. Instructions only.
- Allowed tools
ReadWriteEditBash- License
- BSD-3-Clause license
- Compatibility
- Requires Python 3.10+ and dask 2026.8.0; current Zarr 3.4 needs Python 3.12+. DataFrame workflows need pandas 2+ and PyArrow 16+. Cloud paths (s3://, gcs://) need s3fs or gcsfs. Cluster deployment uses dask.distributed (included with dask[complete]).
SKILL.md covers: Dask · Overview · Quick Start · Installation · When to Use This Skill · Core Capabilities · 1. DataFrames - Parallel Pandas Operations · Read multiple files as single DataFrame · Operations are lazy until compute() · 2. Arrays - Parallel NumPy Operations · Small executable example; size chunks from uncompressed memory before scaling · Operations are lazy
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 17 KB |
references/arrays.md | doc | 14 KB |
references/bags.md | doc | 11 KB |
references/best-practices.md | doc | 7.9 KB |
references/dataframes.md | doc | 10 KB |
references/futures.md | doc | 13 KB |
references/review.md | doc | 8.5 KB |
references/schedulers.md | doc | 13 KB |
External hosts referenced
docs.dask.org distributed.dask.org arxiv.org docs.scipy.org docs.xarray.dev doi.org export.arxiv.org jobqueue.dask.org kubernetes.dask.org ml.dask.org pypi.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-dask-scan.json
- Badge for your README:
- Request a re-scan