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.
How do I install this agent skill?
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-testIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill provides instructional content and templates for designing A/B tests in digital advertising. It does not contain executable code, external dependencies, or network operations. No security risks were identified.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
- ZeroLeakspass
Score: 93/100 · 2 sections analyzed
What does this agent skill do?
Paid 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.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/agricidaniel/claude-ads/ads-test">View ads-test on skillZs</a>