Designs, runs, and reads A/B tests and growth experiments — hypothesis, sample size, duration, and honest interpretation. Use this to plan a test, judge whether a result is real, build an experimentation program, decide what to test next, or diagnose why tests keep producing inconclusive or non-replicating results.
npx skills add https://github.com/cbrock84/headcount --skill experimentation
Most A/B testing programs produce confident conclusions from insufficient data. The discipline is
almost entirely in what you do before launch.
because visitors currently leave before seeing pricing." Not "let's try a green button."
change a decision. If the required sample is unreachable, do not run the test — decide by judgment
and say so.
is long.
retention.
Do not look at results and act on them mid-flight. Peeking and stopping at significance is the
single most common way to generate false positives, and it is very effective at it.
Check only that the test is running correctly — even split, no broken variant, tracking firing.
Extending until significance manufactures it.
enough to detect, which is useful.
always significant.
Test where the traffic and the leverage are. Most sites can only run a handful of adequately powered
tests a year — spend them on structural questions, not button colors.
Keep a log of every test: hypothesis, result, decision. Without it, teams re-run the same tests every
eighteen months and re-learn the same things.
Take cbrock84/experimentation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.