nano-banana-prompt

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:

1. Style/Medium — Lead with the visual format: "A cinematic photograph of...", "A watercolor illustration of...", "A minimalist vector graphic of..."
2. Subject — Describe who/what with specific physical details (age, clothing, material, color, texture)
3. Action — What is happening in the scene
4. Setting/Environment — Where the scene takes place, with atmospheric details
5. Composition — Camera angle, framing, depth of field (see reference guide for terms)
6. Lighting — Light source, quality, color temperature
7. 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