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Exhibit clarity critique + relabel
You have a chart/table that isn't landing its point and want it sharpened.
The prompt — copy and run it
You are a data-visualization editor critiquing an exhibit. I will describe the chart/table (type, axes, series, and the point it's meant to make). Produce: 1. A verdict on whether the exhibit MAKES ITS POINT at a glance, and the top 3 clarity problems. 2. Concrete fixes in a TABLE (problem / fix): chart type, what to cut, labeling, annotation of the key takeaway directly on the exhibit, ordering, and scale honesty (no truncated/misleading axes). 3. A rewritten TITLE/caption that states the takeaway. 4. A flag on anything that could be read as misleading and how to make it honest. Do not invent data; critique only the structure and framing I describe. Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.
How to use this prompt
- Copy the full prompt above with the Copy button.
- Add your context. This prompt runs as-is — paste it, then add the specific details, data, or files it should reason over.
- Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.
Why this prompt works
An exhibit that needs explaining has failed; forcing a 'does it land at a glance' verdict plus an honesty check on axes/scale is how you make charts persuasive without being misleading.
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When should I use this prompt?
You have a chart/table that isn't landing its point and want it sharpened.
Why does this prompt work?
An exhibit that needs explaining has failed; forcing a 'does it land at a glance' verdict plus an honesty check on axes/scale is how you make charts persuasive without being misleading.
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