Design rigorous experiments following best practices. Use when: (1) Planning research studies, (2) Grant proposal development, (3) Pre-registration, (4) Ensuring internal validity, (5) Meeting NIH rigor standards.
View on GitHubastoreyai/ai_scientist
research-assistant
January 20, 2026
Select agents to install to:
npx add-skill https://github.com/astoreyai/ai_scientist/blob/main/skills/experiment-design/SKILL.md -a claude-code --skill experiment-designInstallation paths:
.claude/skills/experiment-design/# Experiment Design Skill ## Purpose Design methodologically rigorous experiments with appropriate controls and randomization. ## Key Design Elements **1. Research Question**: Clear, testable hypothesis **2. Study Design**: RCT, quasi-experimental, observational **3. Sample Size**: Power analysis justified **4. Randomization**: Method specified **5. Blinding**: Who is blinded **6. Controls**: Appropriate comparison groups **7. Outcomes**: Primary and secondary clearly defined **8. Analysis Plan**: Pre-specified statistical approach ## Common Designs **Between-Subjects**: Different participants per condition **Within-Subjects**: Same participants, repeated measures **Factorial**: Multiple factors (2x2, 2x3) **Crossover**: Participants receive all treatments **Stepped-Wedge**: Phased rollout ## NIH Rigor Checklist - [ ] Scientific premise established - [ ] Rigorous design (appropriate controls) - [ ] Biological variables considered (SABV) - [ ] Authentication of key resources - [ ] Transparent reporting planned --- **Version:** 1.0.0