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Skill

/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

From plugin
claude-ads
7.9k33 skills25 agents
Install
$ npx -y skills add AgriciDaniel/claude-ads --skill ads-test --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/ads-test

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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

SKILL.md

ads-test.SKILL.md
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.

Ships withclaude-ads

Claude-first, portable paid-media operations for agencies, consultants, and in-house performance teams. Claude Ads turns authorized exports or account reads into source-grounded audits, plans, creative workflows, experiments, monitoring, and reports.

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