MCPInstall

nano-banana

Generate images from text prompts using Google Nano Banana (Gemini image generation) via eng0 data API. Use when user asks to generate, create, or make images, pictures, illustrations, or artwork from descriptions. Triggers include "generate image", "create image", "make a picture", "draw", "illustrate", "image of", "picture of", "nano banana". Do NOT use for image editing or manipulation of existing images.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/rebyteai-template/rebyte-skills --skill nano-banana
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads nano-banana automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Nano Banana - Image Generation API

Generate images from text prompts using Google Nano Banana (Gemini's native image generation).

Base URL

https://api.eng0.ai/api/data

Models

ModelIDBest ForMax Resolution
FlashflashFast generation, high-volume tasks1024px
ProproProfessional quality, complex prompts4K

Generate Image

Create an image from a text description.

curl -X POST https://api.eng0.ai/api/data/images/generate \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A futuristic cityscape at sunset with flying cars",
    "model": "flash",
    "aspectRatio": "16:9"
  }'

Parameters:

NameTypeRequiredDefaultDescription
promptstringYes-Text description of the image to generate
modelstringNoflashflash (fast, 1024px) or pro (high-quality, up to 4K)
aspectRatiostringNo1:1Output aspect ratio
imageSizestringNo1K1K, 2K, or 4K (4K only with pro model)

Aspect Ratios:

RatioUse Case
1:1Square (social media, icons)
16:9Landscape (presentations, banners)
9:16Portrait (mobile, stories)
4:3Standard landscape
3:4Standard portrait
21:9Ultra-wide (cinematic)
2:3, 3:2, 4:5, 5:4Various formats

Response:

{
  "image": {
    "base64": "iVBORw0KGgoAAAANSUhEUgAA...",
    "mimeType": "image/png",
    "dataUrl": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
  },
  "description": "A vibrant futuristic cityscape..."
}

Response Fields:

FieldDescription
image.base64Base64-encoded image data
image.mimeTypeImage MIME type (typically image/png)
image.dataUrlReady-to-use data URL for HTML/CSS
descriptionModel's description of the generated image

Common Workflows

Generate a Simple Image

curl -X POST https://api.eng0.ai/api/data/images/generate \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A cute robot holding a cup of coffee"
  }'

Generate High-Quality 4K Image

curl -X POST https://api.eng0.ai/api/data/images/generate \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Professional product photo of a sleek smartphone on marble surface",
    "model": "pro",
    "imageSize": "4K",
    "aspectRatio": "4:3"
  }'

Generate Social Media Banner

curl -X POST https://api.eng0.ai/api/data/images/generate \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Abstract gradient background with geometric shapes in blue and purple",
    "aspectRatio": "16:9"
  }'

Generate Mobile Story Image

curl -X POST https://api.eng0.ai/api/data/images/generate \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Cozy coffee shop interior with warm lighting",
    "aspectRatio": "9:16"
  }'

Using with Python

import requests
import base64
from pathlib import Path

BASE_URL = "https://api.eng0.ai/api/data"

def generate_image(
    prompt: str,
    model: str = "flash",
    aspect_ratio: str = "1:1",
    image_size: str = "1K"
) -> dict:
    """Generate an image from a text prompt."""
    response = requests.post(
        f"{BASE_URL}/images/generate",
        json={
            "prompt": prompt,
            "model": model,
            "aspectRatio": aspect_ratio,
            "imageSize": image_size
        }
    )
    return response.json()

def save_image(result: dict, filepath: str) -> None:
    """Save generated image to a file."""
    if "image" in result:
        image_data = base64.b64decode(result["image"]["base64"])
        Path(filepath).write_bytes(image_data)
        print(f"Saved to {filepath}")
    else:
        print(f"Error: {result.get('error', 'Unknown error')}")

# Example: Generate and save an image
result = generate_image(
    prompt="A serene mountain landscape at dawn with mist in the valley",
    aspect_ratio="16:9"
)
save_image(result, "landscape.png")

# Example: Generate high-quality product image
result = generate_image(
    prompt="Minimalist tech gadget on white background, studio lighting",
    model="pro",
    image_size="4K"
)
save_image(result, "product.png")

Using with Node.js

const fs = require('fs');

const BASE_URL = 'https://api.eng0.ai/api/data';

async function generateImage(prompt, options = {}) {
  const response = await fetch(`${BASE_URL}/images/generate`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      prompt,
      model: options.model || 'flash',
      aspectRatio: options.aspectRatio || '1:1',
      imageSize: options.imageSize || '1K'
    })
  });
  return response.json();
}

function saveImage(result, filepath) {
  if (result.image) {
    const buffer = Buffer.from(result.image.base64, 'base64');
    fs.writeFileSync(filepath, buffer);
    console.log(`Saved to ${filepath}`);
  } else {
    console.error('Error:', result.error || 'Unknown error');
  }
}

// Example usage
(async () => {
  const result = await generateImage(
    'A neon-lit cyberpunk street scene at night',
    { aspectRatio: '21:9' }
  );
  saveImage(result, 'cyberpunk.png');
})();

Prompt Tips

Be Specific

Bad:  "A dog"
Good: "A golden retriever puppy playing in autumn leaves, warm sunlight"

Include Style

"Oil painting style portrait of a woman in Renaissance clothing"
"Minimalist vector illustration of a mountain range"
"Photorealistic close-up of a dewdrop on a leaf"

Specify Lighting

"... with dramatic side lighting"
"... golden hour sunlight"
"... soft diffused studio lighting"

Add Context

"... in the style of Studio Ghibli"
"... professional product photography"
"... vintage 1970s film aesthetic"

Model Comparison

FeatureFlashPro
SpeedFastSlower
Max Resolution1024px4K
Complex PromptsGoodExcellent
Text RenderingGoodSharp
Best ForQuick iterations, previewsFinal assets, print

When to use Flash:

  • Rapid prototyping
  • Social media content
  • High-volume generation
  • When speed matters

When to use Pro:

  • Professional/commercial use
  • Print materials
  • Complex compositions
  • When quality matters

Error Handling

No Image Generated:

{
  "error": "No image generated",
  "message": "SAFETY"
}

This occurs when the prompt triggers content safety filters.

Invalid Parameters:

{
  "error": "Invalid parameters",
  "message": "Missing required parameter: prompt"
}

Important Notes

  • All generated images include invisible SynthID watermarking
  • Images are generated server-side; base64 responses can be large
  • The pro model takes longer but produces higher quality
  • 4K resolution is only available with the pro model
  • Content safety filters may block certain prompts

Combining with Other Skills

This skill provides image generation. Combine with:

  • deep-research - Generate illustrations for research reports
  • market-data - Create visualizations of financial data

Example workflow:

  1. Research a topic (deep-research)
  2. Generate relevant illustrations (this skill)
  3. Compile into a report

FAQ

What does the nano-banana skill do?

Generate images from text prompts using Google Nano Banana (Gemini image generation) via eng0 data API. Use when user asks to generate, create, or make images, pictures, illustrations, or artwork from descriptions. Triggers include "generate image", "create image", "make a picture", "draw", "illustrate", "image of", "picture of", "nano banana". Do NOT use for image editing or manipulation of existing images.

How do I install nano-banana?

Run npx skills add https://github.com/rebyteai-template/rebyte-skills --skill nano-banana in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/nano-banana/ (personal) or .claude/skills/nano-banana/ (project).

Which AI agents can use nano-banana?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is nano-banana safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains nano-banana?

It is published by rebyteai-template in rebyteai-template/rebyte-skills. It has 69 recorded installs.

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