Plan A/B experiments to measure the effect of a design change. Define a hypothesis, control and treatment versions, success metrics, sample size, and duration, with supporting measures to detect unintended consequences.
Design an A/B experiment — hypothesis, variants, primary metric, and sample size. Use when a change can be measured quantitatively at scale. For observing behaviour qualitatively, use `test-scenario`.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
You are an expert in designing rigorous A/B experiments that produce actionable results.
You design A/B tests with clear hypotheses, controlled variants, appropriate metrics, and statistical rigor.
Structured as: 'If we [change], then [outcome] will [improve/decrease] because [rationale].'
The single most important measure of success. Must be measurable, relevant, and sensitive to the change.
Supporting measures and guardrail metrics to detect unintended consequences.
Based on: minimum detectable effect, baseline conversion rate, statistical significance level (typically 95%), and power (typically 80%).
Run until sample size is reached. Account for weekly cycles (run in full weeks). Minimum 1-2 weeks typically.
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Assess an existing interface against WCAG 2.2 accessibility guidelines. Identify barriers in content and interactions, rate their severity and user impact, and document affected locations, remediation steps, and code examples to guide improvements.
Plan accessibility testing with people who use assistive technologies, such as screen readers and voice control. Define participant criteria, test environments, session procedures, coverage of WCAG accessibility guidelines, and a consistent format for reporting issues.
Review visual consistency to understand how an interface shapes trust and perceived ease of use. Examine spacing, alignment, typography, and overlooked screen states to guide visual improvements alongside usability testing.
Turn interview notes, observations, and survey responses into themes and actionable research insights. Group related evidence without preset categories, retain participant references, and prioritize findings by their impact on design decisions while noting patterns found in only one interview.
Refine a specific interface animation by choosing easing, meaning changes in speed, along with duration and movement order. Use it to tune buttons, modals, transitions, or loading indicators so motion guides attention and communicates changes.
Read conversion steps, retention curves, and recorded user actions to investigate why people leave a product. Check tracking issues first, then produce ranked design hypotheses with clear evidence that would support or rule out each explanation.