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Nano banana 2

Skill Sheshiyer/skill-clusters/skills/nano-banana-2

Generate images with Google Gemini 3.1 Flash Image Preview (Nano Banana 2) via the inference.sh CLI: text-to-image, image editing, multi-image input (up to 14 images), and Google Search grounding. USE WHEN asked for nano banana 2, gemini 3.1 flash image, or Google image generation.From its SKILL.md

Install
npx -y skills add Sheshiyer/skill-clusters --skill nano-banana-2

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.9 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

Nano Banana 2 - Gemini 3.1 Flash Image Preview

Generate images with Google Gemini 3.1 Flash Image Preview via inference.sh CLI.

Quick Start

curl -fsSL https://cli.inference.sh | sh && infsh login

infsh app run google/gemini-3-1-flash-image-preview --input '{"prompt": "a banana in space, photorealistic"}'

Install note: The install script only detects your OS/architecture, downloads the matching binary from dist.inference.sh, and verifies its SHA-256 checksum. No elevated permissions or background processes. Manual install & verification available.

Examples

Basic Text-to-Image

infsh app run google/gemini-3-1-flash-image-preview --input '{
  "prompt": "A futuristic cityscape at sunset with flying cars"
}'

Multiple Images

infsh app run google/gemini-3-1-flash-image-preview --input '{
  "prompt": "Minimalist logo design for a coffee shop",
  "num_images": 4
}'

Custom Aspect Ratio

infsh app run google/gemini-3-1-flash-image-preview --input '{
  "prompt": "Panoramic mountain landscape with northern lights",
  "aspect_ratio": "16:9"
}'

Image Editing (with input images)

infsh app run google/gemini-3-1-flash-image-preview --input '{
  "prompt": "Add a rainbow in the sky",
  "images": ["https://example.com/landscape.jpg"]
}'

High Resolution (4K)

infsh app run google/gemini-3-1-flash-image-preview --input '{
  "prompt": "Detailed illustration of a medieval castle",
  "resolution": "4K"
}'

With Google Search Grounding

infsh app run google/gemini-3-1-flash-image-preview --input '{
  "prompt": "Current weather in Tokyo visualized as an artistic scene",
  "enable_google_search": true
}'

Input Options

ParameterTypeDescription
promptstringRequired. What to generate or change
imagesarrayInput images for editing (up to 14). Supported: JPEG, PNG, WebP
num_imagesintegerNumber of images to generate
aspect_ratiostringOutput ratio: "1:1", "16:9", "9:16", "4:3", "3:4", "auto"
resolutionstring"1K", "2K", "4K" (default: 1K)
output_formatstringOutput format for images
enable_google_searchbooleanEnable real-time info grounding (weather, news, etc.)

Output

FieldTypeDescription
imagesarrayThe generated or edited images
descriptionstringText description or response from the model
output_metaobjectMetadata about inputs/outputs for pricing

Prompt Tips

Styles: photorealistic, illustration, watercolor, oil painting, digital art, anime, 3D render

Composition: close-up, wide shot, aerial view, macro, portrait, landscape

Lighting: natural light, studio lighting, golden hour, dramatic shadows, neon

Details: add specific details about textures, colors, mood, atmosphere

Sample Workflow

# 1. Generate sample input to see all options
infsh app sample google/gemini-3-1-flash-image-preview --save input.json

# 2. Edit the prompt
# 3. Run
infsh app run google/gemini-3-1-flash-image-preview --input input.json

Python SDK

from inferencesh import inference

client = inference()

# Basic generation
result = client.run({
    "app": "google/gemini-3-1-flash-image-preview@0c7ma1ex",
    "input": {
        "prompt": "A banana in space, photorealistic"
    }
})
print(result["output"])

# Stream live updates
for update in client.run({
    "app": "google/gemini-3-1-flash-image-preview@0c7ma1ex",
    "input": {
        "prompt": "A futuristic cityscape at sunset"
    }
}, stream=True):
    if update.get("progress"):
        print(f"progress: {update['progress']}%")
    if update.get("output"):
        print(f"output: {update['output']}")

Related Skills

# Original Nano Banana (Gemini 3 Pro Image, Gemini 2.5 Flash Image)
npx skills add inference-sh/skills@nano-banana

# Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@inference-sh

# All image generation models
npx skills add inference-sh/skills@ai-image-generation

Browse all image apps: infsh app list --category image

Documentation

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most images graphics skills give in ~1.2k tokens

Counted across 371 of the 372 authors here whose files we hold, read 2026-08-07

  • Create a complete brand world in one imagein 19 of 371, across 5 files
  • Infer the brand strategy before generatingin 19 of 371, across 5 files
  • Use a clean presentation gridin 19 of 371, across 5 files
  • Confirm connection status is activein 19 of 371, across 4 files
  • Base the visual system on meaningin 17 of 371, across 3 files
  • Make every panel feel connectedin 17 of 371, across 3 files
  • Use very little textin 17 of 371, across 3 files
  • Call RUBE_SEARCH_TOOLS firstin 17 of 371, across 3 files
  • Convert dash-format node IDs to colon formatin 17 of 371, across 5 files
  • Match reference quality and rhythm if providedin 16 of 371, across 2 files
  • Narrow scope or reduce depth to avoid oversized payloadsin 16 of 371, across 4 files
  • Generate a simple and memorable logoin 15 of 371, across 1 file

Said here and by no other author read

  • install the cli via curl
  • authenticate using infsh login
  • provide a required prompt parameter
  • specify images array for image editing
  • specify resolution for output size

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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