Doe Optimizer

---
name: doe-optimizer
description: Skill for optimizing experimental designs using DOE principles
allowed-tools:
  - Bash
  - Read
  - Write
metadata:
  specialization: scientific-discovery
  domain: science
  category: Experimental Design
  skill-id: SK-SCIDISC-016
graph:
  domains: [domain:scientific-discovery]
  specializations: [specialization:scientific-research-methods]
  skillAreas: [skill-area:data-analysis, skill-area:statistical-analysis, skill-area:deep-web-research]
  workflows: [workflow:experiment-design, workflow:peer-review-cycle]
  roles: [role:research-engineer, role:computational-scientist]
---

# 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