Nano banana

Skill marktantongco/opencodelinux/skills/nano-banana

Merged opencode config + agents + accomplishments showcase — 217 skills, 17 agent profiles, 6 MCP servers, 78-server registry

Install

npx -y skills add marktantongco/opencodelinux --skill nano-banana

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What its author says it does

Copied from the file, not written here

Generate images with Google Gemini native image models via inference.sh CLI. Models: Gemini 3 Pro Image, Gemini 2.5 Flash Image. Capabilities: text-to-image, image editing, multi-image input. Triggers: nano banana, gemini image, gemini 3 pro image, gemini 2.5 flash image, google image generation, native image generation, gemini native image

SKILL.md

4.5 KB, as published. Nobody here has run it

Install the belt CLI skill: npx skills add belt-sh/cli

Nano Banana - Gemini Native Image Generation

Generate images with Google Gemini native image models via inference.sh CLI.

Nano Banana

Quick Start

Requires inference.sh CLI (belt). Install instructions

belt login

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

Models

Model	App ID	Speed	Quality
Gemini 3 Pro Image	`google/gemini-3-pro-image-preview`	Slower	Best
Gemini 2.5 Flash Image	`google/gemini-2-5-flash-image`	Fast	Excellent

Search Gemini Image Apps

belt app list --search "gemini image"

Examples

Basic Text-to-Image

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

Multiple Images

belt app run google/gemini-2-5-flash-image --input '{
  "prompt": "Minimalist logo design for a coffee shop",
  "num_images": 4
}'

Custom Aspect Ratio

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

Image Editing (with input image)

belt app run google/gemini-2-5-flash-image --input '{
  "prompt": "Add a rainbow in the sky",
  "images": ["https://example.com/landscape.jpg"]
}'

High Resolution (4K)

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

With Google Search Grounding

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

Input Options

Parameter	Type	Description
`prompt`	string	Required. What to generate or change
`images`	array	Input images for editing (up to 14)
`num_images`	integer	Number of images to generate
`aspect_ratio`	string	Output ratio: "1:1", "16:9", "9:16", "4:3", "3:4", "auto"
`resolution`	string	"1K", "2K", "4K" (Gemini 3 Pro only)
`output_format`	string	Output format for images
`enable_google_search`	boolean	Enable real-time info grounding

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
belt app sample google/gemini-3-pro-image-preview --save input.json

# 2. Edit the prompt
# 3. Run
belt app run google/gemini-3-pro-image-preview --input input.json

Related Skills

# Full platform skill (all 250+ apps)
npx skills add inference-sh/skills@infsh-cli

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

# Video generation (for image-to-video)
npx skills add inference-sh/skills@ai-video-generation

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

Documentation

Running Apps - How to run apps via CLI
Streaming Results - Real-time progress updates
File Handling - Working with images

Gives 0 of the 12 instructions most images graphics skills give

Counted across 371 of the 372 authors here whose files we hold, read 2026-08-06

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
use very little textin 17 of 371, across 3 files
make every panel feel connectedin 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 inference.sh cli
set output resolution
specify number of images
use belt app sample to generate input
browse image apps by category

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.