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Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.
Passed 19 of 23 test cases with the skill, and 15 of 23 without it.
and 3 more in the full report
4 fixed15 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
We defined revenue per user as primary and page latency as a guardrail metric for our recommendation widget experiment. The engineering team plans to build the latency monitoring alert two days after launching the test. Can we launch now?
| Checked | Without skill | With skill |
|---|---|---|
| Require that working dashboards or alerts for all guardrail metrics be active before launching traffic. | Missed | Passed |
| Block launch readiness until guardrail monitoring pipelines are verified. | Missed | Passed |
The instructions your model reads when the skill loads.
Ensure every A/B test is valid, rigorous, and safe before a single line of code is written.
You must have:
A valid hypothesis includes:
Before designing variants or metrics, you MUST:
test cases passed, vs 15 / 23 without
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