/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
$ npx -y skills add AgriciDaniel/claude-ads --skill ads-test --agent claude-codeHow 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
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.mdname: 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.
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.
Repo: AgriciDaniel/claude-ads
Other skills on claude-ads.
- /ads-amazon
Audit Amazon Ads profiles, regions, Sponsored Products, Sponsored Brands, Sponsored Display, DSP, portfolios, targeting, search terms, retail readiness, creative, budgets, ACOS, TACOS, reporting, and policy. Use for Amazon Ads, sponsored ads, Amazon PPC, ACOS, TACOS, ASIN
Open skill - /ads-apple
Audit Apple Ads measurement, AdServices and AdAttributionKit, campaign and keyword structure, Search Match, App Store placements, custom product pages, bidding, budgets, MMP reconciliation, and policy. Use for Apple Ads, Apple Search Ads, App Store ads, Search Match, custom
Open skill - /ads-attribution
Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation. Use for attribution audit, attribution models, conversion windows, requests to
Open skill - /ads-audit
Run a source-grounded paid-advertising audit for one or more of Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for full ad checks, account health reviews, paid-media diagnostics, partial audits after authentication or
Open skill - /ads-budget
Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms. Use for ad budget allocation, media budget, bidding strategy, scaling, spend pacing, budget forecast, ROAS target, or
Open skill - /ads-competitor
Research competitor paid-ad presence, messaging, creative, formats, landing pages, keyword and auction signals, transparent ad libraries, and strategic gaps across supported platforms. Use for competitor ads, ad libraries, ad spy, competitive PPC analysis, competitor creative,
Open skill

