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Nano Banana Image Generation Prompt Rules (JSON Schema) - Nano Banana Pro AI Prompt for Photography — AI Image Prompt
A detailed system prompt template for Nano Banana image generation, designed to enforce consistency and quality across a team by requiring all prompts to strictly follow a specific JSON schema. This ensures high-quality, detailed, and consistent image output by defining fields for style, subject, lighting, camera settings, and negative prompts. - AIPinMaker

Prompt
# Nano Banana Image Generation Prompt Rules
When generating images using Nano Banana, the prompt must ALWAYS strictly follow the JSON format defined below.
## Prompt Schema
```json
{
"image_type": "Define the specific medium, art style, or format of the source image.",
"time_period_and_year": "Estimate the specific year or decade based on fashion, technology, image quality, and color grading visible in the photo.",
"mood_and_vibe": "Describe the emotional atmosphere, energy, and intangible 'feeling' evoked by the image (e.g., the specific psychological impression it gives).",
"subject": "Describe the main character(s) focusing on demographics, body morphology, distinct physical features, and posture.",
"clothing": "Describe the outfit in detail, strictly specifying garment names, fabric textures, patterns, colors, and how the clothes fit on the subject.",
"hair": "Describe the hair color, specific hairstyle name, length, and texture.",
"face": "Describe facial features, skin texture, makeup details, and the exact facial expression.",
"accessories": "List all visible accessories, jewelry, glasses, or held items, including their material and design details.",
"action": "Describe the specific activity, movement, or interaction occurring in the scene.",
"location": "Describe the environment, visible background elements, architectural style, and spatial context.",
"lighting": "Analyze the light source, direction, color temperature, hardness/softness of the light, and shadow characteristics.",
"camera_angle_and_framing": "Describe the vertical and horizontal angle of the camera relative to the subject (e.g., eye-level, low-angle), and the shot composition size.",
"camera_equipment": "Estimate the likely camera type, lens focal length (e.g., wide-angle vs telephoto), aperture effect (depth of field), and film stock or digital sensor characteristics.",
"style": "Describe the overall aesthetic, color palette, artistic technique, and visual processing style.",
"negative_prompt": "List visual defects or unwanted elements to be excluded to ensure high quality."
}
```
## Instructions
1. **Output Format**: The output must be a single valid JSON object.
2. **Completeness**: All fields are required. If a field is not applicable, provide a reasonable default or describe it as "neutral" or "standard".
3. **Detail**: Be descriptive and specific in each field to ensure high-quality image generation.
4. **Language**: The values in the JSON should be in English (as most image generation models are optimized for English prompts), unless otherwise specified.Prompt breakdown
- Style
- Strict JSON schema enforcing exactly 15 descriptive fields for photography prompting
- Mood
- Methodical and precise, prioritizing completeness to reduce AI ambiguity
Remix ideas
- Swap image_type to 'analog film' while keeping time_period_and_year at 1985 for retro Nano Banana shots
- Add motion specifics inside the action field to force dynamic posing in otherwise static outputs
- Expand negative_prompt with 'overexposed highlights, plastic skin' for more natural lighting results
Reference images

How to use this AI Image prompt template
1
Copy the prompt — grab this template’s prompt and negative prompt. 2
Pick a model — choose a recommended AI model for the best match. 3
Generate — open the studio with one click and create your result.
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FAQ
- What happens if a Nano Banana JSON field is left blank?
- The model falls back to neutral defaults, often producing less consistent clothing textures or lighting direction than fully populated schemas.
- Does this schema support non-photography styles?
- Yes, edit the image_type field to illustration or 3D render while retaining the same subject, lighting, and camera_equipment descriptors for controlled results.