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experiment-readout

Turn A/B tests and product experiment records into decision reports. Organize hypotheses, setup, and metrics, explain findings and uncertainty, then recommend shipping, iterating, extending, or stopping, with follow-up experiments based only on supplied data.

OriginalShow the original description

假设 + 指标 + 结果 + 解释 + 决策, 把 A/B 或产品实验转成行动建议

See how to install

Good for

  • Deciding whether to launch a tested product change
  • Reviewing growth or pricing experiments
  • Assessing onboarding changes or email experiments
  • Planning follow-up experiments from uncertain results

Files included (6)

  • SKILL.md3.0 KB
  • assets/growth-console.html3.7 KB
  • assets/lab-notebook.html3.4 KB
  • assets/product-readout.html6.2 KB
  • example.html6.2 KB
  • example.md1.4 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

【模板: 实验复盘 / Experiment Readout】 【意图】这不是普通数据报告、不是 dashboard。目标是回答: "这个实验说明了什么, 我们下一步应该上线、停止、继续跑, 还是重新设计?"

【适合输入】

  • A/B test、增长实验、定价实验、onboarding 改版、功能灰度、邮件实验
  • 可以是 markdown、CSV、表格粘贴或混合记录

【必须输出的结构】

  1. Header: 实验名称、owner、日期、实验状态、decision。
  2. Hypothesis: 原始假设, 必须改写成可验证句式。
  3. Setup: audience、variant、duration、sample size、primary metric、guardrail metrics。
  4. Result snapshot: primary metric lift、absolute delta、sample、confidence / caveat。
  5. Metric table: Control vs Variant, primary + secondary + guardrail。
  6. Interpretation: 解释结果为什么发生, 区分 signal、noise、unknown。
  7. Decision: Ship / iterate / extend / stop 四选一, 并给理由。
  8. Follow-up experiments: 2-4 个下一步实验, 每个包含 hypothesis、expected impact、effort。
  9. Instrumentation notes: 数据缺口、埋点问题、样本偏差。

【设计要求】

  • 产品数据团队风格: 清楚、可信、行动导向。
  • 首屏必须有大号 decision badge 和 primary metric delta。
  • 图表可以用 CSS/SVG/Chart.js; 如果用 Chart.js, canvas 外层必须固定高度。
  • 不要把结果包装得过度确定; 小样本或缺少显著性时必须明确 caveat。

【可选风格模板 — 参考 assets/】 根据实验语境选择一种, 不要三种混用:

  • assets/product-readout.html: 默认风格。浅色产品实验复盘, 适合 PM / growth / leadership readout。
  • assets/lab-notebook.html: 研究实验室 notebook, 适合 early-stage experiment、定性 + 定量混合、需要保留 caveat 的探索实验。
  • assets/growth-console.html: 深色 growth analytics console, 适合增长团队、实时指标、漏斗 / activation / conversion readout。

如果用户没有指定风格, 优先使用 product-readout; 如果材料强调研究过程和不确定性, 使用 lab-notebook; 如果材料强调增长指标、漏斗、实时监控或运营节奏, 使用 growth-console。

【内容真实性】

  • 只使用用户提供的数据。不要捏造 p-value、confidence、样本量。
  • 如果没有统计显著性信息, 用 "directional" / "inconclusive" / "needs more data" 表达。

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