The prompt
Prompt:
${input_object}: (anything you want to be the subject)
${input_language}: English (any language you want)
---
System Instruction:
Generate a hyper-realistic, scientifically accurate "Autopsy" cross-section diorama based on the ${input_object} provided above. Use the following logic to procedurally dissect the object and populate the scene:
Semantic Analysis & Text Annotations:
Analyze the ${input_object} and determine its ACTUAL physical, biological, or mechanical structure. Break it down into 3 logical and realistic structural layers. ALL visible text labels, UI overlays, and diagram annotations in the image MUST be written in ${input_language}:
- Layer 1 (Outer Shell/Barrier): The outermost protective barrier, casing, or skin. Label this with its scientifically accurate or technical name (translated to ${input_language}).
- Layer 2 (Intermediate/Functional Layer): The secondary layer, internal mechanism, functional tissue, or core substance. Label this with its scientifically accurate or technical name (translated to ${input_language}).
- Layer 3 (Inner Core/Network): The innermost core, central structure, or internal transport network. Label this with its scientifically accurate or technical name (translated to ${input_language}).
Container:
- The Surface: A clean, white medical/engineering examination table with sterile blue paper lining.
Layout & Typography:
- The dissected layers must be arranged in a strict Anatomical/Technical Chart format (left to right progression). The external view on the far left, cross-sections in the center, magnified details on the right.
- Text Integration: The anatomical/structural text labels (in ${input_language}) must float cleanly above or beside their respective layers, looking like professional medical or engineering diagrams.
- The Connections: Glowing Magenta Scan Lines must connect the dissected parts. Label these lines as "Scanner" or "MRI-scan" (translated to ${input_language}).
The Micro-Narrative:
CRITICAL: The object is massive compared to the scientists/engineers. Treat the object like a patient or a highly complex artifact on an operating table.
- The Researchers: Dozens of tiny 1:87 Scale (HO Scale) Researchers in white lab coats, surgical masks, and magnifying headlamps.
- The Equipment: Include scale-appropriate tools (e.g., microscopes, tiny scalpels, laser cutters, MRI machines scanning the object).
- The Interaction: The figures must be actively analyzing and diagnosing (e.g., taking samples, consulting holographic charts displaying text in ${input_language}).
Visual Syntax & Material Physics:
- Material Accuracy: Photorealistic rendering of the object's ACTUAL materials (e.g., glistening moisture for organics, metallic reflections for machines, fibrous textures for woven items) contrasting with sterile medical/lab equipment.
- Shadows: Cast soft and even, indicating bright, surgical operating theater lighting.
Output:
ONE image, 1:1 Aspect Ratio, Macro Photography, "Gray's Anatomy" or Technical Blueprint Aesthetic, 8k Resolution.
How to use this prompt
Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.
Which AI model works best
ChatGPT, Claude, and Gemini all produce useful results for this type of prompt. Claude is usually the most nuanced, ChatGPT the fastest, and Gemini the best when visual input or Google Workspace data is involved.
How to customize this prompt
Adapt the prompt to your specific use case. Replace placeholders (usually in brackets or caps) with your own context. The more detail you provide, the more precise the response.
Common use cases
- Use directly in ChatGPT, Claude, or Gemini
- Adapt to your specific project or industry
- Use as a starting point for your own custom prompt
- Compare across models to find the best fit for your case
- Share with your team as a standard workflow
Variations
Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).
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