nanobanana-skill — community nanobanana-skill, codex-settings, community, ide skills

v1.0.0

About this Skill

Perfect for Visual Content Agents needing advanced image generation and editing capabilities with Google Gemini API Generate or edit images using Google Gemini API via nanobanana. Use when the user asks to create, generate, edit images with nanobanana, or mentions image generation/editing tasks.

feiskyer feiskyer
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Updated: 2/20/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reviewed Landing Page Review Score: 9/11

Killer-Skills keeps this page indexable because it adds recommendation, limitations, and review signals beyond the upstream repository text.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review Locale and body language aligned
Review Score
9/11
Quality Score
75
Canonical Locale
en
Detected Body Locale
en

Perfect for Visual Content Agents needing advanced image generation and editing capabilities with Google Gemini API Generate or edit images using Google Gemini API via nanobanana. Use when the user asks to create, generate, edit images with nanobanana, or mentions image generation/editing tasks.

Core Value

Empowers agents to generate and edit images using the Google Gemini API, leveraging libraries like google-genai and Pillow, and supporting environment variables for seamless integration, enabling precise image tasks automation

Ideal Agent Persona

Perfect for Visual Content Agents needing advanced image generation and editing capabilities with Google Gemini API

Capabilities Granted for nanobanana-skill

Automating image editing tasks with precision using Python3 and dependent packages
Generating images through the Google Gemini API for various applications
Editing images with advanced capabilities using the nanobanana tool

! Prerequisites & Limits

  • Requires Google Gemini API Key configured in ~/.nanobanana.env or exported as GEMINI_API_KEY
  • Needs Python3 with dependent packages installed, including google-genai, Pillow, and python-dotenv
  • Executable requires specific installation and configuration

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

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FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is nanobanana-skill?

Perfect for Visual Content Agents needing advanced image generation and editing capabilities with Google Gemini API Generate or edit images using Google Gemini API via nanobanana. Use when the user asks to create, generate, edit images with nanobanana, or mentions image generation/editing tasks.

How do I install nanobanana-skill?

Run the command: npx killer-skills add feiskyer/codex-settings/nanobanana-skill. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for nanobanana-skill?

Key use cases include: Automating image editing tasks with precision using Python3 and dependent packages, Generating images through the Google Gemini API for various applications, Editing images with advanced capabilities using the nanobanana tool.

Which IDEs are compatible with nanobanana-skill?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for nanobanana-skill?

Requires Google Gemini API Key configured in ~/.nanobanana.env or exported as GEMINI_API_KEY. Needs Python3 with dependent packages installed, including google-genai, Pillow, and python-dotenv. Executable requires specific installation and configuration.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add feiskyer/codex-settings/nanobanana-skill. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use nanobanana-skill immediately in the current project.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

nanobanana-skill

Install nanobanana-skill, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
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Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Nanobanana Image Generation Skill

Generate or edit images using Google Gemini API through the nanobanana tool.

Requirements

  1. GEMINI_API_KEY: Must be configured in ~/.nanobanana.env or export GEMINI_API_KEY=<your-api-key>
  2. Python3 with depedent packages installed: google-genai, Pillow, python-dotenv. They could be installed via python3 -m pip install -r ~/.codex/skills/nanobanana-skill/requirements.txt if not installed yet.
  3. Executable: ~/.codex/skills/nanobanana-skill/nanobanana.py

Example .nanobanana.env:

bash
1GEMINI_API_KEY=sk-dummy

Instructions

For image generation

  1. Ask the user for:

    • What they want to create (the prompt)
    • Desired aspect ratio/size (optional, defaults to 9:16 portrait)
    • Output filename (optional, auto-generates UUID if not specified)
    • Model preference (optional, defaults to gemini-3-pro-image-preview)
    • Resolution (optional, defaults to 1K)
  2. Run the nanobanana script with appropriate parameters:

    bash
    1python3 ~/.codex/skills/nanobanana-skill/nanobanana.py --prompt "description of image" --output "filename.png"
  3. Show the user the saved image path when complete

For image editing

  1. Ask the user for:

    • Input image file(s) to edit
    • What changes they want (the prompt)
    • Output filename (optional)
  2. Run with input images:

    bash
    1python3 ~/.codex/skills/nanobanana-skill/nanobanana.py --prompt "editing instructions" --input image1.png image2.png --output "edited.png"

Available Options

Aspect Ratios (--size)

  • 1024x1024 (1:1) - Square
  • 832x1248 (2:3) - Portrait
  • 1248x832 (3:2) - Landscape
  • 864x1184 (3:4) - Portrait
  • 1184x864 (4:3) - Landscape
  • 896x1152 (4:5) - Portrait
  • 1152x896 (5:4) - Landscape
  • 768x1344 (9:16) - Portrait (default)
  • 1344x768 (16:9) - Landscape
  • 1536x672 (21:9) - Ultra-wide

Models (--model)

  • gemini-3-pro-image-preview (default) - Higher quality
  • gemini-2.5-flash-image - Faster generation

Resolution (--resolution)

  • 1K (default)
  • 2K
  • 4K

Optional Flags

  • --enable-google-search Enable Google Search tool for the model (default: disabled)
  • --include-thoughts Include model thinking in output (default: disabled)

Examples

Generate a simple image

bash
1python3 ~/.codex/skills/nanobanana-skill/nanobanana.py --prompt "A serene mountain landscape at sunset with a lake"

Generate with specific size and output

bash
1python3 ~/.codex/skills/nanobanana-skill/nanobanana.py \ 2 --prompt "Modern minimalist logo for a tech startup" \ 3 --size 1024x1024 \ 4 --output "logo.png"

Generate landscape image with high resolution

bash
1python3 ~/.codex/skills/nanobanana-skill/nanobanana.py \ 2 --prompt "Futuristic cityscape with flying cars" \ 3 --size 1344x768 \ 4 --resolution 2K \ 5 --output "cityscape.png"

Edit existing images

bash
1python3 ~/.codex/skills/nanobanana-skill/nanobanana.py \ 2 --prompt "Add a rainbow in the sky" \ 3 --input photo.png \ 4 --output "photo-with-rainbow.png"

Use faster model

bash
1python3 ~/.codex/skills/nanobanana-skill/nanobanana.py \ 2 --prompt "Quick sketch of a cat" \ 3 --model gemini-2.5-flash-image \ 4 --output "cat-sketch.png"

Error Handling

If the script fails:

  • Check that GEMINI_API_KEY is exported or set in ~/.nanobanana.env
  • Verify input image files exist and are readable
  • Ensure the output directory is writable
  • If no image is generated, try making the prompt more specific about wanting an image

Best Practices

  1. Be descriptive in prompts - include style, mood, colors, composition
  2. For logos/graphics, use square aspect ratio (1024x1024)
  3. For social media posts, use 9:16 for stories or 1:1 for posts
  4. For wallpapers, use 16:9 or 21:9
  5. Start with 1K resolution for testing, upgrade to 2K/4K for final output
  6. Use gemini-3-pro-image-preview for best quality, gemini-2.5-flash-image for speed

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