Dask

Dask is a Data skill for Claude Code, published by K-Dense-AI in scientific-agent-skills.

33.5K stars3.3K forkson K-Dense-AI/scientific-agent-skillsAdded 2026/08/14Repository updated 2026/08/13

agent-skillsai-scientistbioinformaticschemoinformaticsclaudeclaude-skillsclaudecodeclinical-researchcomputational-biologydata-analysisdrug-discoverygenomicsmaterials-sciencemetabolomicsproteomicsscientific-computingscientific-visualization

Install in seconds

Install Dask

Copy Dask into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/dask ~/.claude/skills/dask

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/dask/SKILL.md in K-Dense-AI/scientific-agent-skills
Installs to: ~/.claude/skills/dask
Collection: One of 25 skills cataloged from this repository
Category: Data — 668 skills

What Dask does

Dask scales pandas and NumPy workflows to larger-than-memory datasets and across clusters. Use it when you need parallel file processing, distributed ML, or to scale existing pandas/NumPy code beyond memory.

Dask is cataloged under Data on DirSkills. Dask comes from a repository tagged agent-skills, ai-scientist, bioinformatics, chemoinformatics and claude.

Documentation

README

Excerpt

Dask

Overview

Dask is a Python library for parallel and distributed computing that enables three critical capabilities:

Larger-than-memory execution on single machines for data exceeding available RAM
Parallel processing for improved computational speed across multiple cores
Distributed computation supporting terabyte-scale datasets across multiple machines

Dask scales from laptops (processing ~100 GiB) to clusters (processing ~100 TiB) while maintaining familiar Python APIs.

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Dask

What else does K-Dense-AI publish alongside Dask?
Dask is one of 25 skills that DirSkills catalogs from K-Dense-AI/scientific-agent-skills, the repository it ships in. Its siblings there include Adaptyv Bio Foundry API, Aeon and Analytical Method Validation. Each one is a separate skill with its own page in this directory, installs the same way Dask does, and is maintained by K-Dense-AI in that same repository. The rest of the collection is listed on the K-Dense-AI/scientific-agent-skills page.
How does Dask compare to other Data skills?
Dask ranks #30 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Dask against them. Open each page to compare what they document and how they install.