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DataRust

Experimental Design

by xintaofei

Experimental Design is a Data skill for Claude Code, published by xintaofei in codeg.

2.8K stars345 forkson xintaofei/codegAdded 2026/08/17+3% in starsRepository updated 2026/08/17
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Install in seconds
Install Experimental Design
Copy Experimental Design 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/xintaofei/codeg/tree/main/src-tauri/science/skills/experimental-design ~/.claude/skills/experimental-design

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/xintaofei/codeg.git

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

In this catalog

Source file
src-tauri/science/skills/experimental-design/SKILL.md in xintaofei/codeg
Installs to
~/.claude/skills/experimental-design
Collection
One of 25 skills cataloged from this repository
Category
Data — 668 skills

What Experimental Design does

Experimental Design plans experiments and studies before data collection, choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use it when assigning subjects to groups, screening factors, or setting up factorial or response-surface designs.

Experimental Design is cataloged under Data on DirSkills. Experimental Design comes from a repository tagged acp, agent, claude-code, cline and code-generation.

Documentation

README

Experimental Design

Overview

The design of a study — how units are assigned to conditions, what is held constant, what is varied, and in what structure — determines what questions the data can answer. No analysis can rescue a confounded or pseudoreplicated design after the fact. This skill is about the decisions made before data collection: picking a design that isolates the effect of interest, randomizing to license causal claims, blocking to remove known nuisance variation, and structuring multi-factor experiments so effects are estimable rather than tangled together.

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

Frequently asked about Experimental Design

  • What else does xintaofei publish alongside Experimental Design?

    Experimental Design is one of 25 skills that DirSkills catalogs from xintaofei/codeg, the repository it ships in. Its siblings there include Brainstorming, Citation Management and Code Review Reception. Each one is a separate skill with its own page in this directory, installs the same way Experimental Design does, and is maintained by xintaofei in that same repository. The rest of the collection is listed on the xintaofei/codeg page.

  • How does Experimental Design compare to other Data skills?

    Experimental Design ranks #296 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 Experimental Design against them. Open each page to compare what they document and how they install.

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