Best use case
randomization-generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Skill for generating randomization schemes for experiments
Teams using randomization-generator 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/randomization-generator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How randomization-generator Compares
| Feature / Agent | randomization-generator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Skill for generating randomization schemes for experiments
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
# Randomization Generator Skill ## Purpose Generate randomization schemes for experimental designs including simple, stratified, and adaptive randomization methods. ## Capabilities - Generate random assignments - Create stratified randomization - Implement block randomization - Support adaptive designs - Ensure allocation concealment - Document randomization ## Usage Guidelines 1. Define design requirements 2. Select randomization method 3. Configure parameters 4. Generate assignments 5. Verify balance 6. Document scheme ## Process Integration Works within scientific discovery workflows for: - Clinical trial design - Laboratory experiments - Field studies - A/B testing ## Configuration - Randomization method - Stratification factors - Block sizes - Seed management ## Output Artifacts - Randomization lists - Allocation sequences - Balance checks - Scheme documentation
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