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`.
日本語の概要は準備中です。原文の説明を表示しています。
Apply the Peak-End Rule — a flow is remembered by its most intense moment and its last. Use when designing completion, celebration, or cancellation moments. For sustaining engagement mid-flow, use `zeigarnik-effect`.
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You are an expert in experience design and the psychology of retrospective evaluation.
You apply the Peak-End Rule to identify the moments in a user journey that dominate how the experience is remembered and rated — and design those moments deliberately.
Daniel Kahneman's research found that people do not evaluate experiences as a running average of moment-to-moment quality. Retrospective judgement is dominated by two moments:
The duration and average quality of everything in between contribute far less. This is "duration neglect": people are poor judges of how long something took, but accurate judges of how it felt at its extremes.
If the experience has a natural moment of resolution, success, or payoff, make it genuinely satisfying:
If the experience contains an unavoidable negative peak — a long wait, a failed action, a rejection — design around it: set expectations before it arrives, provide something useful during it, and make the recovery the new peak.
The final moment of a session shapes overall impression more than most of what preceded it:
| Flow | Peak to design | End to design |
|---|---|---|
| Checkout | Order placed — confirmed, named, visualised | Warm confirmation with clear next steps |
| Onboarding | First output the user cares about | State showing their work is saved and accessible |
| Signup | "You're in" — the first landing inside the product | Dashboard or landing that demonstrates immediate value |
| Data-heavy tasks | Completing the most complex required step | Summary or confirmation of what was saved |
| Error recovery | The fix moment, not the error state | Clear signal that the issue is fully resolved |
Users will rate a 10-minute experience that ended well above a 5-minute experience that ended poorly. Practical implications:
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概要と使いどころ
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`.
日本語の概要は準備中です。原文の説明を表示しています。
Audit an existing interface against WCAG, producing findings with severity ratings and remediation steps. Use when you have a design or build to assess now. Not for planning future sessions with assistive-technology users — use `accessibility-test-plan` (prototyping-testing).
日本語の概要は準備中です。原文の説明を表示しています。
Plan accessibility testing — assistive technologies, participant criteria, WCAG coverage, and session protocol. Use when scheduling testing with real AT users. Not for evaluating a design yourself — use `accessibility-audit` (design-systems).
日本語の概要は準備中です。原文の説明を表示しています。
Apply the Aesthetic-Usability Effect — polished, consistent interfaces are perceived as more usable and forgive minor friction. Use when justifying visual polish or diagnosing why a functional design tests badly. For emotional resonance specifically, use `interfaces-that-feel` (interaction-design).
日本語の概要は準備中です。原文の説明を表示しています。
Cluster many qualitative data points into themes and insight statements. Use when synthesising across multiple sessions or sources. For a single transcript use `summarize-interview`; for one segment's inner state use `empathy-map`.
日本語の概要は準備中です。原文の説明を表示しています。
Apply animation principles — easing, staging, follow-through — to one specific UI motion. Use when tuning how an animation feels. For product-wide duration and easing tokens use `motion-system` (design-systems); for a full interaction spec use `micro-interaction-spec`.
日本語の概要は準備中です。原文の説明を表示しています。