Claude Skill MartBrowse skillsQuick linesLearn by videoTerminal guideWhat is a Skill?
 
← Back to list

Experimental Design

Picks the right study design and generates seeded randomization schedules and DOE matrices before any data is collected.

Data & AnalyticsIntermediate★ 33,030⑂ 3,248AI score 9/10Last updated: Aug 9, 2026

What it does

  • Walks a decision tree from your research question to a concrete design: completely randomized, randomized block, crossover/repeated measures, cluster-randomized, full or fractional factorial, response surface, or Latin hypercube.
  • Generates reproducible allocation schedules with scripts/randomization.py (simple, permuted-block, stratified-block, cluster) plus arm-balance checks and CSV export.
  • Builds DOE matrices in real factor units with scripts/doe_designs.py (full/2^k factorial, fractional, Plackett-Burman, central composite, Box-Behnken, Latin hypercube) with randomized run order.
  • Flags the eight structural mistakes analysis can never fix — pseudoreplication, batch confounding, plate edge effects, ignored aliasing, missing controls, and more.

Who it's for

  • Bench scientists, grad students, and lab managers planning comparative experiments.
  • Clinical/field trial planners who need auditable, pre-registrable allocation schedules.
  • Process engineers and data scientists running multi-factor screening or optimization studies.

Examples

  1. "Assign 60 mice to drug vs. control, balanced throughout enrollment" → permuted-block schedule plus per-arm balance check.
  2. "I have 7 candidate process factors and little budget" → Plackett-Burman screening matrix in real units, run order randomized.
  3. "Optimize temperature and concentration where the response is curved" → central composite design with a documented seed for reproducibility.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/experimental-design/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/experimental-design folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/experimental-design/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git /tmp/sas && mkdir -p ~/.claude/skills && cp -r /tmp/sas/skills/experimental-design ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal and confirm Python 3.10 or newer: python3 --version.
  2. Clone the repository: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git.
  3. Copy the skill into your Claude skills folder: mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/experimental-design ~/.claude/skills/.
  4. Install the Python dependencies: uv pip install "numpy>=1.26" "pandas>=2.0" pyDOE3 (use pip install if you don't have uv).
  5. Restart Claude Code and ask something like "how should I set up this experiment?" — the skill triggers automatically.
  6. Archive the generated CSV layouts together with the random seed so the schedule can be regenerated and audited later.
View source on GitHub ↗License: MIT