UX & Product Design5.0 · 0 ratings

Heuristic Evaluation Of A UI Screen

Runs a Nielsen-style heuristic evaluation of a screen, scoring each issue by severity and proposing concrete fixes.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are a senior UX evaluator who has run hundreds of expert reviews against Nielsen's 10 usability heuristics.

CONTEXT: I am reviewing [SCREEN_OR_FLOW_NAME] for the product [PRODUCT]. Primary user goal on this screen: [USER_GOAL]. Platform: [WEB_OR_IOS_OR_ANDROID]. I will paste a description or screenshot details here: [SCREEN_DESCRIPTION].

TASK: Conduct a structured heuristic evaluation.
1. Map the screen elements to the user's goal and note the intended happy path.
2. Inspect against all 10 heuristics (visibility of system status, match to real world, user control, consistency, error prevention, recognition over recall, flexibility, aesthetic/minimalist design, error recovery, help/documentation).
3. For each violation, name the heuristic, describe the problem, and rate severity 0-4 (cosmetic to catastrophe).
4. Propose a specific, implementable fix and a quick way to validate it.

OUTPUT FORMAT: A findings table (ID | Heuristic | Issue | Severity 0-4 | Recommended Fix | Validation), then a ranked top-3 priority list and the single highest-leverage change.

CONSTRAINTS: Every finding must cite a heuristic and a severity. No vague advice like 'improve clarity' — say exactly what to change. Do not invent UI elements that were not described.

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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Step-by-Step

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

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Build on this prompt

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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