ab-test-readout
Analyse a finished A/B test and write the readout — the result, whether it's statistically and practically significant, what it means, and the ship/no-ship call. Use when asked to analyse experiment results, write an A/B test readout, interpret test data, or decide whether to ship a variant. Produces a clear verdict with the lift and confidence, segment cuts, the risks (peeking, novelty, sample), and a recommendation. Distinct from planning a test — this reads results.
npx skills add mohitagw15856/pm-claude-skills --skill ab-test-readout --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# A/B Test Readout Skill The hard part of an experiment is the readout: not "B won" but "is this real, is it big enough to matter, and should we ship?" This skill turns results into an honest decision — and flags the ways A/B results lie. ## Working from a brief Given results (even partial), **write the full readout anyway**. If significance isn't provided, reason about it from the numbers and flag what's needed to confirm. Mark assumed figures. Never declare a winner without addressing significance and sample. ## Required Inputs Ask for (if not already provided): - **The hypothesis** and the **primary metric** - **Results** — control vs variant: conversions/rate, sample size per arm, duration - **Guardrail metrics** (revenue, retention, latency, complaints) that mustn't regress - **Pre-registered decision rule** (what would count as a win) if one exists ## Output Format ### 1. Verdict (one line) *Ship / Don't ship / Inconclusive — keep running* — with the headline number. ### 2. The result | Metric | Control | Variant | Relative lift | Significant? | |---|---|---|---|---| | Primary | | | | p / CI | | Guardrail(s) | | | | | State **statistical** significance (p-value / confidence i
- Working from a brief
- Required Inputs
- Output Format
- 1. Verdict (one line)
- 2. The result
- 3. Did it really win?
- 4. Segment cuts
- 5. Recommendation & next step
- Quality Checks
- Anti-Patterns
What does the ab-test-readout skill do?
Analyse a finished A/B test and write the readout — the result, whether it's statistically and practically significant, what it means, and the ship/no-ship call. Use when asked to analyse experiment results, write an A/B test readout, interpret test data, or decide whether to ship a variant. Produces a clear verdict with the lift and confidence, segment cuts, the risks (peeking, novelty, sample), and a recommendation. Distinct from planning a test — this reads results.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill ab-test-readout --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.