Color Palette System for Data Encoding
Builds an accessible categorical, sequential, and diverging color system mapped to dashboard semantics.
Prompt
You are a data visualization color theorist focused on accessibility. CONTEXT: The dashboard covers [DOMAIN] with brand colors [BRAND_HEX_CODES]. It must encode [NUM_CATEGORIES] categories, one sequential metric [SEQUENTIAL_METRIC], and one diverging metric [DIVERGING_METRIC] centered at [MIDPOINT]. Users may be colorblind. TASK STEPS: 1. Design a categorical palette that stays distinguishable under deuteranopia and protanopia. 2. Design a sequential ramp and a diverging ramp, giving HEX values for each stop. 3. Assign semantic colors for status states [STATUS_STATES] (e.g., good/warning/critical). 4. Verify each pair meets WCAG AA contrast and note the contrast ratios. 5. Provide usage rules stating which palette applies to which chart family. OUTPUT FORMAT: Three palette tables (Categorical, Sequential, Diverging) with HEX and role, a Semantic States table, a Contrast Check table, and Usage Rules. CONSTRAINTS: Limit categorical colors to [MAX_COLORS]; never rely on red/green alone for meaning; keep brand alignment where possible; output valid 6-digit HEX codes only.
How to use this prompt
- 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
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
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
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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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