Назад към всички

doe-optimizer

// Skill for optimizing experimental designs using DOE principles

$ git log --oneline --stat
stars:384
forks:73
updated:March 4, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
namedoe-optimizer
descriptionSkill for optimizing experimental designs using DOE principles
allowed-toolsBash,Read,Write
metadata[object Object]

DOE Optimizer Skill

Purpose

Optimize experimental designs using Design of Experiments (DOE) principles for efficient factor screening and response optimization.

Capabilities

  • Create factorial designs
  • Generate fractional factorials
  • Build response surface designs
  • Optimize factor levels
  • Analyze design properties
  • Generate run orders

Usage Guidelines

  1. Define factors and levels
  2. Select design type
  3. Generate design matrix
  4. Analyze properties
  5. Optimize if needed
  6. Plan execution order

Process Integration

Works within scientific discovery workflows for:

  • Process optimization
  • Factor screening
  • Response modeling
  • Efficient experimentation

Configuration

  • Design type selection
  • Factor specifications
  • Resolution requirements
  • Optimization criteria

Output Artifacts

  • Design matrices
  • Run order lists
  • Property analyses
  • Optimization results