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ads-test

为付费广告实验提供从设计到读out的流程:明确决策与因果假设、处理组与对照组、随机化单位、主指标与护栏指标、最小效应与停止规则;检查平台限制、实验重叠、转化延迟与测量质量;按假设计算样本量与时长;预注册排除项与分析阈值;读out时先校验分组与数据完整性,再估计效应与不确定性,并以带版本JSON返回结论与通俗决策。

AgriciDaniel
热度 0.00
最近更新 2026-10-19 00:59:30
分类:营销依赖:纯提示词应用场景:市场分析 / 研究 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add agricidaniel/claude-ads/ads-test
Metadata
name
ads-test
description
Design and evaluate paid-ad experiments with hypotheses, randomization units, sample-size and duration assumptions, guardrails, platform experiment tools, analysis, and decision rules. Use for A/B test, split test, experiment design, hypothesis, statistical significance, sample size, test duration, or experiment readout.

Paid Media Experiment

  1. State the decision, causal hypothesis, treatment, control, randomization unit, population, primary metric, guardrails, minimum effect, and stopping rule.
  2. Check platform constraints, overlapping experiments, conversion lag, seasonality, interference, and measurement quality.
  3. Calculate sample and duration from declared assumptions; disclose approximations.
  4. Change one decision surface unless the design explicitly estimates interactions.
  5. Pre-register exclusions, quality checks, analysis, and decision thresholds.
  6. For readout, verify assignment integrity and data completeness before estimating effect and uncertainty.
  7. Return setup or readout in versioned JSON with a plain-language decision.

Do not repeatedly peek and stop on a favorable result, call underpowered noise a winner, or generalize beyond the tested population.