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ads-test

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.

测试9.8kskills/ads-test/SKILL.md

Install

Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.

读取 https://funcoding.ai/skills/agricidaniel/claude-ads/ads-test/install.md ，按里面的步骤帮我安装这个 Skill。

SKILL.md

  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.

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