Individual skill
experiment-designer
Design statistically rigorous A/B tests and interpret experiment results. Use when asked to design an experiment, run an A/B test, calculate sample size, interpret test results, or assess whether an experiment was successful. Produces a complete experiment design with hypothesis, sample size, run time, success criteria, and risk flags — or a results interpretation with ship/iterate/kill recommendation.
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# Experiment Designer Skill
Produce rigorous experiment designs from product hypotheses, and interpret results with statistical and practical significance — so you can defend every decision to a sceptical engineering lead or data scientist.
## Required Inputs
Work from what is given. If any of these is missing, still produce the complete output: fill each gap with a reasonable assumption marked *(assumed, confirm)* and list those assumptions at the end. Ask a question first only when the core subject itself is missing (there is nothing to write about).
**For experiment design:**
- Hypothesis (what change, what metric, what expected movement)
- Current baseline metric value
- Minimum detectable effect (MDE) — the smallest lift worth caring about
- Available daily sample size
**For results interpretation:**