doe-optimizer
// Skill for optimizing experimental designs using DOE principles
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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
- Define factors and levels
- Select design type
- Generate design matrix
- Analyze properties
- Optimize if needed
- 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