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Found 143 Skills
Run hypothesis tests, analyze A/B experiment results, calculate sample sizes, and interpret statistical significance with effect sizes. Use when you need to validate whether observed differences are real, size an experiment correctly before launch, or interpret test results with confidence.
How to read experiment results without fooling yourself. Confidence intervals, p-values, multiple testing, sequential testing, CUPED, heterogeneous treatment effects, ratio metrics, network effects, dashboard reconciliation, and the interpretation failures that produce confidently wrong shipping decisions.
Compress an agent's routing file (RESOLVER.md or AGENTS.md) by converting granular skill-per-row tables into functional-area dispatchers. Each area lists sub-skills in a "(dispatcher for: ...)" clause. The LLM reads one area entry and routes to the correct sub-skill. Proven via held-out A/B eval: dispatcher pattern outperforms naive pipe-table compression.
This skill should be used when the user asks to "set up an A/B test", "calculate sample size", "design an experiment", "analyze A/B test results", "check statistical significance", "determine test duration", or "evaluate conversion rate experiments".
Plan Amazon product listing images for maximum conversion. Create shot lists, infographic layouts, lifestyle scene briefs, and A/B testing plans following Amazon's image requirements and best practices.
Executes optimization hypotheses with keep/discard testing loop. Use when applying validated performance improvements.
Optimize product titles for search visibility and click-through rate across e-commerce platforms. Platform-specific title rules for Amazon (200 chars), Etsy (140 chars), Walmart, Shopify SEO, and eBay.
When the user wants to design, test, or optimize their app's paywall — layout, copy, pricing display, trial offers, plan structure, hard vs soft paywall, paywall placement, or paywall A/B tests. Use when the user mentions "paywall", "paywall design", "paywall conversion", "trial-to-paid", "soft paywall", "hard paywall", "paywall A/B test", "paywall copy", "plan picker", "annual vs monthly display", "best paywall", "RevenueCat paywall", "Superwall", "Adapty", or "my paywall isn't converting". For overall pricing strategy and monetization model choice, see monetization-strategy. For trial nurture, dunning, and churn, see subscription-lifecycle. For where in the onboarding the paywall fires, see onboarding-optimization.
Optimize conversion rates. Use when: auditing landing pages, testing forms, or improving checkout flow.
Build and run a full email marketing channel — list building, deliverability, segmentation, newsletter strategy, campaign types, A/B testing, and email design. Use when the user says "email marketing", "email strategy", "email list", "newsletter", "email campaigns", "email list building", "email deliverability", "email open rates", "email segmentation", "email design", "email calendar", "grow my email list", "email marketing plan", "broadcast emails", "email engagement", or wants to use email as a primary owned marketing channel beyond just automated flows.
Use when the user asks to "design an A/B test", "set up a creative/landing test", "run an incrementality test", or "is this result statistically and practically material?"; produces a hypothesis, variant matrix, sample-size/duration/power plan, and a documented effect/uncertainty read from own exported results. It applies only a precommitted owner-approved action rule; the statistical helper never chooses a business action. Not for producing variants — use ad-creative-builder; not for reading back one shipped change — use paid-measurement-loop. 广告AB测试设计/实验设计/显著性判定/增效测试