doe-optimizer

Skill for optimizing experimental designs using DOE principles

509 stars

Best use case

doe-optimizer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Skill for optimizing experimental designs using DOE principles

Teams using doe-optimizer should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/doe-optimizer/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/scientific-discovery/skills/doe-optimizer/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/doe-optimizer/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How doe-optimizer Compares

Feature / Agentdoe-optimizerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Skill for optimizing experimental designs using DOE principles

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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

Related Skills

svg-optimizer

509
from a5c-ai/babysitter

Optimize SVG assets, generate sprites, and convert to React components

circuit-optimizer

509
from a5c-ai/babysitter

Quantum circuit optimization skill for gate reduction, depth minimization, and hardware-aware compilation

nanoparticle-synthesis-optimizer

509
from a5c-ai/babysitter

Synthesis parameter optimization skill for metal, semiconductor, and oxide nanoparticle production with automated protocol generation and reproducibility validation

drug-encapsulation-optimizer

509
from a5c-ai/babysitter

Drug delivery formulation skill for optimizing drug loading, encapsulation efficiency, and release kinetics

warehouse-slotting-optimizer

509
from a5c-ai/babysitter

Warehouse slotting and layout optimization skill for pick path minimization and space utilization.

network-optimizer

509
from a5c-ai/babysitter

Network optimization skill for transportation, assignment, and flow problems on graph structures.

facility-layout-optimizer

509
from a5c-ai/babysitter

Facility layout optimization skill for material flow minimization and space utilization.

signal-timing-optimizer

509
from a5c-ai/babysitter

Traffic signal timing optimization skill for cycle length, phasing, and coordination

scaffold-design-optimizer

509
from a5c-ai/babysitter

Tissue engineering scaffold design optimization skill for pore size, porosity, and mechanical properties

prosthetics-design-optimizer

509
from a5c-ai/babysitter

Prosthetics and orthotics design optimization skill integrating biomechanical requirements with manufacturing constraints

inventory-optimizer

509
from a5c-ai/babysitter

Inventory management optimization skill with safety stock calculation, reorder point determination, and ABC analysis

changeover-optimizer

509
from a5c-ai/babysitter

Setup and changeover time reduction skill with SMED methodology and sequence optimization