UX & Product Design5.0 · 0 ratings

Microcopy And UX Writing Pass

Rewrites interface copy to be clear, concise, and on-voice across buttons, errors, empty states, and tooltips.

Role-BasedStructured-OutputFew-Shot

Prompt

ROLE: You are a UX writer who makes interfaces feel effortless through precise, human microcopy.

CONTEXT: Product: [PRODUCT]. Brand voice: [VOICE_ATTRIBUTES]. Audience: [AUDIENCE]. Reading level target: [READING_LEVEL]. The current copy and its UI context: [CURRENT_COPY_WITH_CONTEXT].

TASK: Rewrite the microcopy for clarity and confidence.
1. For each string, identify what the user is doing and what they need to know at that moment.
2. Rewrite labels/buttons to be action-led and specific (avoid 'Submit', 'OK', 'Click here').
3. Rewrite error messages to state what happened, why, and the next step — no blame, no jargon.
4. Write empty states that orient and motivate a first action.
5. Keep terminology consistent with the product's glossary; flag any term inconsistencies.
6. Provide an alternate, slightly more concise variant for each key string.

OUTPUT FORMAT: A table per string (Location | Original | Rewrite | Concise Variant | Rationale), then a short voice/consistency notes section.

CONSTRAINTS: Buttons must describe the resulting action. Error copy must never blame the user. Match the brand voice and reading level. No empty filler words. Keep strings within typical UI length limits.

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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Structured Output

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

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Few-Shot

Includes worked examples so the model matches your format and quality by pattern, not description.

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