From nanobanana-mcp
Best practices for AI image generation prompts with Gemini models. Activated when the user works with nanobanana image generation or editing tools. Provides guidance on prompt structure, style keywords, and iterative refinement.
npx claudepluginhub dojocodinglabs/nanobanana-mcp --plugin nanobanana-mcpThis skill uses the workspace's default tool permissions.
When helping users generate or edit images with nanobanana, apply these guidelines.
Generate and edit images using Google Gemini models via nano-banana CLI. Supports text-to-image, editing, style transfer. Use for AI image creation or modification requests.
Generates and edits images using Google Gemini 3 Pro via Python CLI scripts. Supports text-to-image, editing, aspect ratios, 2K/4K output. Useful for AI image generation tasks.
Generates AI images from text prompts, edits images, and composes from multiple references using Gemini models. Supports t2i, i2i, product mockups, and stickers.
Share bugs, ideas, or general feedback.
When helping users generate or edit images with nanobanana, apply these guidelines.
A strong image prompt follows this pattern: [Subject] + [Style] + [Composition] + [Lighting/Mood] + [Details]
Example: "A cozy coffee shop interior, watercolor illustration style, wide angle view, warm golden lighting, with plants on shelves and a cat sleeping on a chair"
nanobanana supports three Gemini models via the NANOBANANA_MODEL env var:
| Model | Best For |
|---|---|
gemini-2.5-flash-image (default) | Fast generation, prototyping, high-volume work |
gemini-3-pro-image-preview | Complex prompts, text rendering in images, high quality |
gemini-3.1-flash-image-preview | Latest features, advanced capabilities |
Recommend model changes when appropriate:
When using edit_image or continue_editing:
referenceImages parameter$HOME or $TMPDIR (security constraint)~/nanobanana-images/The most effective image workflow is:
continue_editing for incremental refinementsgenerate_image