dask
dask is an Exploratory analysis & notebooks skill for AI agents, published by K-Dense-AI in the scientific-agent-skills repository on GitHub. Skillspace rates dask C (72/100) and it passed the safety scan; a judge model has also reviewed it.
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 44,723
Placed #5 of 6 in the judged category final for Exploratory analysis & notebooks.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #5 of 6 in the judged category final for Exploratory analysis & notebooks.
- Trigger
78 78 - Instructions
75 75 - Specificity
78 78 - Safety
85 85 - Disclosure
80 80 - Maintenance
75 75
Good comparative framing against vaex/polars and current version tracking, but reads more like docs than a task workflow.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Also published in 1 other repo
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