Design Of Experiments

Design Of Experiments is a Data skill for Claude Code, published by asgard-ai-platform in skills.

228 stars28 forkson asgard-ai-platform/skillsAdded 2026/09/03Repository updated 2026/06/06

ai-agentanthropicclaudeclaude-agent-skillsclaude-codecoding-agentknowledge-basemcpmethodologyopen-sourceprompt-engineeringskillstaiwan

Install in seconds

Install Design Of Experiments

Copy Design Of Experiments 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/asgard-ai-platform/skills/tree/main/algo-mfg-doe ~/.claude/skills/algo-mfg-doe

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/asgard-ai-platform/skills.git

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

In this catalog

Source file: algo-mfg-doe/SKILL.md in asgard-ai-platform/skills
Installs to: ~/.claude/skills/algo-mfg-doe
Collection: One of 25 skills cataloged from this repository
Category: Data — 710 skills

What Design Of Experiments does

Design Of Experiments designs and analyzes factorial experiments to find significant process factors and interactions. Use it to screen variables, optimize settings, or confirm which inputs affect quality or yield.

Design Of Experiments is cataloged under Data on DirSkills. Design Of Experiments comes from a repository tagged ai-agent, anthropic, claude, claude-agent-skills and claude-code.

Documentation

README

Excerpt

Design of Experiments (DOE)

Overview

DOE systematically varies process factors to identify their effects on responses. Full factorial tests all combinations; fractional factorial tests a strategic subset. Identifies main effects and interactions. More efficient than one-factor-at-a-time (OFAT) which misses interactions. Uses ANOVA for analysis.

When to Use

Trigger conditions:

Identifying which process factors significantly affect quality/yield
Optimizing process settings for target performance
Screening many factors to find the vital few

When NOT to use:

When the process is not stable (stabilize with SPC first)
For observational data with no ability to manipulate factors

Algorithm

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

Frequently asked about Design Of Experiments

What else does asgard-ai-platform publish alongside Design Of Experiments?
Design Of Experiments is one of 25 skills that DirSkills catalogs from asgard-ai-platform/skills, the repository it ships in. Its siblings there include ARIMA Time Series Model, Ad Bidding Strategies and Ad Budget Allocation. Each one is a separate skill with its own page in this directory, installs the same way Design Of Experiments does, and is maintained by asgard-ai-platform in that same repository. The rest of the collection is listed on the asgard-ai-platform/skills page.
How does Design Of Experiments compare to other Data skills?
Design Of Experiments ranks #643 by stars among the 710 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 Design Of Experiments against them. Open each page to compare what they document and how they install.