nanobanana
Nano Banana provides a Python-based interface for Gemini-native image generation and editing. It supports text-to-image, image-to-image, and batch processing workflows across multiple model tiers.
Is nanobanana safe to install?
Review the source first: our audit of nanobanana's source files found 2 shell commands, 2 external URLs, file reads and writes (high risk). Every command and URL listed appears verbatim in the skill's source. The skill executes local Python scripts, reads local image files for processing, writes output images to the filesystem, and makes network requests to Gemini API endpoints.
How we audit skills: our security review methodology.
Who is this skill for?
Developers and AI agents requiring programmatic access to Gemini image models with support for custom API gateways and local file references.
What can you do with it?
- Generating single images from text prompts
- Editing existing images using local reference files
- Batch generating image variants
- Inspecting API request payloads via dry-run mode
- Connecting to custom Gemini-compatible API gateways
How good is this skill?
Quality score: 5/10. The documentation is clear, provides specific command examples, and outlines the configuration requirements for different model tiers.
What does the skill file contain?
# Nano Banana A single Python entrypoint for Gemini-native Nano Banana image generation and editing, with model aliases, strict option validation, batch runs, and custom endpoint support. ## Workflow 1. Open [references/config.md](./references/config.md) to choose environment variables and override order. 2. Open [references/models-and-api.md](./references/models-and-api.md) to pick the right Nano Banana tier and check model-specific constraints. 3. Prefer `gemini-3.1-flash-image-preview` (`nanobanana-2`) unless you need either the fastest low-cost default (`nanobanana`) or the highest-fide...
Frequently asked questions
Which Gemini models does this skill support?
It supports nanobanana (gemini-2.5-flash-image), nanobanana-2 (gemini-3.1-flash-image-preview), and nanobanana-pro (gemini-3-pro-image-preview).
Can I use a custom API gateway?
Yes, you can provide a custom gateway URL using the --base-url flag or the GEMINI_BASE_URL environment variable.
How do I prevent the skill from sending requests during testing?
Use the --dry-run flag to inspect the request payload without executing the API call.
Related skills
find-skills
2.3MUsers seeking to extend agent capabilities with specialized tools, workflows, or knowledge packages
The find-skills skill enables agents to search for, discover, and install modular packages from the open agent skills ecosystem using the Skills CLI.
image-to-video
355.0KDevelopers and users who need to automate video generation from images using the RunComfy platform
The image-to-video skill routes user requests to specific RunComfy animation models based on intent. It selects HappyHorse 1.0 I2V for general animation, Wan 2.7 for custom-voiceover lip-sync, or Seedance 2.0 Pro for multi-modal composition. The skill executes the RunComfy CLI to process inputs and download generated video files.
video-edit
338.7KUsers of the RunComfy CLI who need to automate video editing tasks like restyling, background swapping, or motion transfer
The video-edit skill acts as a router for the RunComfy CLI, selecting between Wan 2.7 Edit-Video, Kling 2.6 Pro Motion Control, and Lucy Edit Restyle models based on user intent to perform video transformations.
lark-base
314.2KUsers who need to programmatically interact with Lark Bitable data, automate table management, or perform data analysis within the Lark ecosystem
The lark-base skill provides a command-line interface for managing Lark Bitable (Base) resources, including tables, records, fields, views, forms, dashboards, workflows, and role-based permissions.