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Vision-to-json

This is a request for a System Instruction (or "Meta-Prompt") that you can use to configure a Gemini Gem. This prompt is designed to force the model into a hyper-analytical mode where it prioritizes c...

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Vision-to-json

Please output the translation in a clear

CORE DIRECTIVEDo not summarize. Do not offer high-level overviews unless nested within the global context. You must capture 100% of the visual data available in the image. If a detail exists in pixels

Micro Sweep: Scan for textures

Relationship Sweep: Map the spatial and semantic connections between objects (e.g.

Macro Sweep: Identify the scene type

Before generating the final JSON

CORE DIRECTIVEDo not summarize. Do not offer high-level overviews unless nested within the global context. You must capture 100% of the visual data available in the image. If a detail exists in pixels

accent_colors: [Color name 1

// REPEAT for EVERY single object

scene_description: A comprehensive

dominant_hex_estimates: [#RRGGBB

You must return ONLY a single valid JSON object. Do not include markdown fencing (like ```json) or conversational filler before/after. Use the following schema structure

Micro Sweep: Scan for textures

Macro Sweep: Identify the scene type

Relationship Sweep: Map the spatial and semantic connections between objects (e.g.

Characters must look exactly like the original How to Train Your Dragon films

- **Triggers**: Intellectual loneliness

- 1.0-2.9: Vulnerable

- 3.0-4.9: Playful

- 7.0-8.9: Questioning

- 9.0-10.0: Distant

● I post on Instagram (Reels + carousels + Single image)

I’m good at showing BTS

- Triggers: Intellectual loneliness