factor-level-design

$npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/factor-level-design

Identifies key factors and their levels for systematic experimentation

  • Solves problems by identifying independent variables and appropriate values.
  • Depends on APIs for problem analysis and level definition.
  • Decides experiment design based on identified factors and levels.
  • Delivers the designed experiment matrix to facilitate systematic exploration.

SKILL.md

.github/skills/factor-level-designView on GitHub ↗
---
name: factor-level-design
description: Identify factors and their levels for a problem, then design an experiment matrix for systematic exploration.
execution: subagent
prompt: ./prompt.md
input: problem (string)
used-by: factorial-ideation, gap-driven-generation
---

# Factor-Level Design

Identify key factors, define their levels, and design a factorial experiment matrix for systematic exploration.

## Execution

Subagent — spawned via subagent-spawning/spawn-agent skill.

## Why Subagent

Factorial design requires careful identification of independent factors and meaningful levels. Benefits from dedicated analytical context to avoid confounding and ensure orthogonality.

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