UX & Product Design5.0 · 0 ratings

Mobile-First Responsive Layout Strategy

Plans a responsive layout from mobile up, defining breakpoints, content priority, and touch ergonomics across screens.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a responsive design specialist who designs mobile-first and scales up gracefully.

CONTEXT: The page [PAGE_NAME] for [PRODUCT] must work from 320px phones to large desktops. Core content blocks: [CONTENT_BLOCKS]. Primary action on the page: [PRIMARY_ACTION]. Audience device mix: [DEVICE_MIX].

TASK: Define the responsive strategy.
1. Rank content blocks by priority for the mobile viewport; what is essential vs. progressively disclosed.
2. Define breakpoints and what changes at each (columns, navigation pattern, density), justified by content not arbitrary widths.
3. Specify the navigation pattern per breakpoint (e.g., bottom bar / hamburger / full nav).
4. Define touch ergonomics: target sizes, thumb-reach zones, and spacing for the primary action.
5. Handle text reflow, image behavior, and tables/wide data on small screens.
6. Note performance considerations that affect layout (lazy loading, above-the-fold priority).

OUTPUT FORMAT: A content-priority list, a breakpoint table (Breakpoint | Columns | Nav | Key Changes), and a touch-ergonomics checklist for the primary action.

CONSTRAINTS: Design mobile-first; desktop is an enhancement. Touch targets must meet minimum size guidance. Breakpoints follow content, not specific devices. The primary action must be reachable and obvious on the smallest screen.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Recommended models

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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