Ads Test Skill for Claude
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.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/AgriciDaniel/claude-ads --skill ads-testThe instruction itself
1 sections, as written by the authorPaid Media Experiment
- State the decision, causal hypothesis, treatment, control, randomization unit,
population, primary metric, guardrails, minimum effect, and stopping rule.
- Check platform constraints, overlapping experiments, conversion lag, seasonality,
interference, and measurement quality.
- Calculate sample and duration from declared assumptions; disclose approximations.
- Change one decision surface unless the design explicitly estimates interactions.
- Pre-register exclusions, quality checks, analysis, and decision thresholds.
- For readout, verify assignment integrity and data completeness before estimating
effect and uncertainty.
- 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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How to use it
Take agricidaniel/ads-test from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.