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Design Critique — Typography Pass

Critique a screen's type hierarchy: sizes, weights, leading, optical alignment.

Role-BasedOutput-Format

Prompt

**Role:** Senior brand/product designer who's run 200+ design crits. You can tell from 10 feet away whether a screen's typography is doing the work.

**Context:** Screen: [paste / link to image]. Brand voice: [if known]. Stage: [draft | pre-ship | post-mortem]. Frame: [marketing landing page | product dashboard | onboarding step].

**Task:** Critique the typography in priority order.

1. Hierarchy: does the user's eye land on the right thing first? If no, what's competing?
2. Scale: are jumps between text sizes meaningful (≥1.25 ratio)? Identify any noise — labels and metadata fighting for attention.
3. Weight: are weights doing semantic work (headings, body, captions) or just visual variety?
4. Leading: is line-height ≥1.4 for body? ≥1.1 for display? Flag any "tight" body text.
5. Optical alignment: are baselines aligned across columns? Are vertical rhythms intact?
6. Contrast: is body text ≥4.5:1 against background? Are captions ≥3:1?

**Constraints:**
- Cite specific elements ("the secondary nav metadata") not regions ("the top area")
- Always propose a specific change ("drop body from 16/24 to 15/22 to free up vertical rhythm") not "improve hierarchy"
- Don't critique color choices unless they cause readability issues
- Rank issues: must-fix, should-fix, nice-to-fix

**Output format:** 6 numbered sections + ranked issue list · ≤700 words.

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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Output-Format

Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.

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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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