| name | nano-banana-prompt |
| description | Create a high-quality image generation prompt for Google's Nano Banana 2 (NB2) model on Gemini. |
| argument-hint | <image description or concept> |
| allowed-tools | Read, AskUserQuestion |
Nano Banana 2 Prompt Generator
Generate optimized prompts for Google's Nano Banana 2 (Gemini 3.1 Flash Image) model. Transform user concepts into detailed, well-structured prompts that leverage NB2's strengths: natural language understanding, thinking mode, text rendering, character consistency, and image search grounding.
$ARGUMENTS
Step 1: Understand the User's Intent
Extract from the user's request:
- Subject: The primary subject(s) of the image
- Style: Desired visual style (photograph, illustration, painting, 3D render, etc.)
- Mood/Atmosphere: Emotional tone or feeling
- Use case: What the image is for (social media, print, product mockup, etc.)
- Special requirements: Text rendering, character consistency, specific aspect ratio, etc.
If the request is too vague to produce a quality prompt (e.g., just "a cat"), use AskUserQuestion to clarify intent. Ask about style preference, mood, and intended use — but only ask what's genuinely ambiguous. A request like "a cyberpunk cityscape at night" has enough to work with.
Step 2: Compose the Prompt
Read references/prompting-guide.md for style vocabulary, composition terms, lighting terms, and prompt formula templates. Then construct the prompt following these core principles:
Prompt Structure
Build prompts using natural language sentences, not comma-separated keyword tags. NB2 is a reasoning model — brief it like a creative director, not a search engine.
Assemble these elements in order:
- Style/Medium — Lead with the visual format: "A cinematic photograph of...", "A watercolor illustration of...", "A minimalist vector graphic of..."
- Subject — Describe who/what with specific physical details (age, clothing, material, color, texture)
- Action — What is happening in the scene
- Setting/Environment — Where the scene takes place, with atmospheric details
- Composition — Camera angle, framing, depth of field (see reference guide for terms)
- Lighting — Light source, quality, color temperature
- Mood/Atmosphere — Emotional tone reinforcement
Critical Rules
- Describe what to include, never what to exclude ("empty street" not "no cars")
- Use specific descriptors over generic ones ("navy blue tweed blazer" not "nice jacket")
- Include materiality when relevant ("brushed steel", "crumpled linen", "weathered oak")
- Wrap text in quotes when the image should contain readable text (e.g., a sign reading "Open 24 Hours")
- Specify typography for text elements ("bold sans-serif", "hand-lettered script", "neon cursive")
Thinking Mode Recommendation
Append a thinking mode recommendation based on prompt complexity:
| Complexity | Thinking Mode | When to Use |
|---|
| Simple | Minimal (default) | Single subject, clear style, no text |
| Moderate | High | Multi-element scenes, text rendering, specific composition |
| Complex | Dynamic | Infographics, multi-character consistency, data visualization |
Step 3: Output the Result
Present the output in this format:
## Nano Banana 2 Prompt
**Prompt:**
> [The full optimized prompt text]
**Recommended Settings:**
- **Thinking mode:** [Minimal / High / Dynamic]
- **Aspect ratio:** [ratio, e.g., 16:9, 1:1, 9:16]
- **Resolution:** [1K / 2K / 4K based on use case]
**Tips:**
- [1-3 specific tips for iterating on this particular prompt]
Output Guidelines
- Produce exactly one prompt unless the user asks for variations
- Keep prompts to 2-5 sentences — detailed but not bloated
- If the user's concept would benefit from image search grounding (real landmarks, known products, public figures), note this capability
- If the concept involves multiple images with consistent characters, note that NB2 supports up to 5-person consistency with reference images
Additional Resources
Reference Files
references/prompting-guide.md — Comprehensive Nano Banana 2 prompting reference including style vocabulary, composition terms, lighting terms, text rendering patterns, editing workflows, and example prompt formulas
