# Experiment Readout

> Write experiment readouts for product, growth, pricing, UX, and operational tests. Use when Codex is asked to summarize an A/B test, pilot, experiment result, metric movement, guardrails, decision, or learning memo.

- Skill: `jeremylongworth-source/experiment-readout` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add jeremylongworth-source/experiment-readout`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jeremylongworth-source/experiment-readout/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- License: MIT
- Author: jeremylongworth-source (https://skillmd.com/u/jeremylongworth-source)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/jeremylongworth-source/experiment-readout

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# Experiment Readout

## Core Workflow

1. Identify hypothesis, variants, audience, dates, primary metric, guardrails,
   sample, and decision rule.
2. Summarize results against the pre-stated decision rule.
3. Separate observed movement, statistical/practical significance, data quality,
   and interpretation.
4. Check guardrails and unintended effects before recommending rollout.
5. State decision: ship, iterate, stop, extend, or rerun.
6. Capture learning, follow-up questions, and next experiment.

## Safety Rules

- Do not invent sample sizes, statistical significance, confidence intervals, or
  metric values.
- Do not recommend rollout when guardrails failed or data quality is poor.
- Escalate pricing, medical, legal, employment, financial, or high-risk
  customer-impacting experiments.

## Deliverable Shape

For experiment readouts, provide:

- Hypothesis and setup
- Metrics and decision rule
- Results summary
- Guardrail review
- Data quality caveats
- Decision
- Learning
- Follow-up actions

## References

- Read `references/experiment-readout-checklist.md` when writing experiment or
  pilot readouts.