designing-experiments
Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.
Best use case
designing-experiments is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.
Teams using designing-experiments 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/designing-experiments/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How designing-experiments Compares
| Feature / Agent | designing-experiments | 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?
Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.
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
# Designing Experiments
Helps select the appropriate causal inference method.
## Decision Framework
1. **Control Group?**
* **Yes**: Go to Step 2.
* **No**: Consider **Interrupted Time Series (ITS)**.
2. **Unit Structure?**
* **Single Treated Unit**:
* With multiple controls: **Synthetic Control (SC)**.
* No controls: **ITS**.
* **Multiple Treated Units**:
* With control group: **Difference-in-Differences (DiD)**.
3. **Time Structure?**
* **Panel Data** (Multiple units over time): Required for DiD and SC.
* **Time Series** (Single unit over time): Required for ITS.
## Method Quick Reference
* **Difference-in-Differences (DiD)**: Compares trend changes between treated and control groups. Assumes **Parallel Trends**.
* **Interrupted Time Series (ITS)**: Analyzes trend/level change for a single unit after intervention. Assumes **Trend Continuity**.
* **Synthetic Control (SC)**: Constructs a synthetic counterfactual from weighted control units. Assumes **Convex Hull** (treated unit within range of controls).Related Skills
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