nanobanana
Gemini-native Nano Banana image generation and editing across Nano Banana, Nano Banana 2, and Nano Banana Pro. Use when you need text-to-ima
Open source Repository Open in the app JSON README (API)
About
Gemini-native Nano Banana image generation and editing across Nano Banana, Nano Banana 2, and Nano Banana Pro. Use when you need text-to-image, image-to-image edits, repeated local references, batch generation, dry-run request inspection, or a custom Gemini-compatible base URL such as a self-hosted gateway.
Details
- Kind
- Agent skills
- Topic
- AI, RAG & memory
- Publisher
- gargantuax
- Origin
- skillssh
- Category
- ferramentas
- Stars
- 5
- Forks
- 1
- Open pull requests
- 1
- Last push
- 2026-04-22T21:25:34Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-30 15:21:15
- Updated
- 2026-09-11 08:04:18
- Origin id
gargantuax/openskills/nanobanana
README
# openskills
A curated collection of **agent skills** — reusable capability packs that plug into skill-aware coding agents like Codex, Claude, and Cursor. Each skill is self-contained: one folder, one `SKILL.md` entry point, plus the scripts and references needed to do the job well.
This repository is a **multi-skill collection**. The discovery convention is:
```text
skills/<skill-name>/SKILL.md
```
That is the same collection layout used by repositories such as `obra/superpowers`, where one repo publishes multiple independently installable skills.
## How This Collection Works
You can treat this repository in two ways:
1. As a **collection**: install `GargantuaX/openskills` and let your agent discover any bundled skill.
2. As a **package of individual skills**: install only the one sub-skill you want, such as `nanobanana` or `gpt-image-2`.
In other words, the repository itself is the distribution unit, while each `skills/<name>/` directory is an installable skill unit.
## What is a skill?
A skill is a small, versioned folder that teaches an agent how to perform a specific task reliably:
- **`SKILL.md`** — the agent-facing manual: triggers, workflow, rules, examples.
- **`scripts/`** — deterministic code the agent can execute instead of re-deriving logic.
- **`references/`** — deep docs loaded on demand.
- **`agents/`** — optional runtime-specific registration files (e.g. Codex YAML).
Skills follow the [skill-creator](https://github.com/anthropics/skills) conventions: concise frontmatter (`name` + `description`), imperative workflow, one source of truth per topic.
## Skills in this repo
| Skill | Description |
| --- | --- |
| [gpt-image-2](./skills/gpt-image-2/) | Full OpenAI-compatible GPT Image 2 coverage: text-to-image, mask edits, multi-image batches, streaming, partial_images, and the Responses `image_generation` tool. |
| [nanobanana](./skills/nanobanana/) | Gemini-native Nano Banana coverage for Nano Banana, Nano Banana 2, and Nano Banana Pro with custom endpoint support, dry runs, batch generation, and multi-reference edits. |
## Repository layout
```
openskills/
└─ skills/
└─ <skill-name>/
├─ SKILL.md
├─ README.md # optional, human-facing
├─ agents/ # optional, runtime registration
├─ references/ # optional, deep docs
├─ scripts/ # optional, executable helpers
└─ assets/ # optional, templates and sample files
```
## Using a skill
Most skills are designed to be consumed two ways:
1. **By an agent** — install either the full collection or a single skill through [Skills](https://skills.sh/).
2. **By hand** — read the skill's own `README.md` for human-facing setup, then run `scripts/` directly from a terminal.
Install the full collection:
```powershell
pnpm dlx skills add GargantuaX/openskills
```
For Codex specifically, a simpler option is to junction the repository's [`skills/`](./skills/) directory into your local agent skills root instead of copying skills into many agent-specific folders. See [.codex/INSTALL.md](./.codex/INSTALL.md).
Install one skill from the collection:
```powershell
pnpm dlx skills add https://github.com/GargantuaX/openskills --skill nanobanana
pnpm dlx skills add https://github.com/GargantuaX/openskills --skill gpt-image-2
```
`skills.sh` ecosystem docs also show a shorthand form for single-skill installs:
```powershell
pnpm dlx skills add GargantuaX/openskills@nanobanana
pnpm dlx skills add GargantuaX/openskills@gpt-image-2
```
Prefer the `--skill` form in human-facing docs when you want the most explicit command. Use the `owner/repo@skill` shorthand when brevity matters or when another tool expects a single package-like token.
Each skill folder documents its own requirements, configuration, and commands. Start there.
## Quick Setup
For the fastest path:
1. Install the full repo with `pnpm dlx skills add GargantuaX/openskills`, or install one skill with either `pnpm dlx skills add https://github.com/GargantuaX/openskills --skill <name>` or `pnpm dlx skills add GargantuaX/openskills@<name>`.
2. Open the target skill's `README.md`.
3. Copy the repository-level `.env.example` or the skill's documented `.env` example, then set your own API key and endpoint.
4. Run that skill's documented `--dry-run` command first to verify configuration before making live API calls.
For the current image skills, detailed setup and env vars are documented in [skills/gpt-image-2/README.md](./skills/gpt-image-2/README.md), [skills/gpt-image-2/references/config.md](./skills/gpt-image-2/references/config.md), [skills/nanobanana/README.md](./skills/nanobanana/README.md), and [skills/nanobanana/references/config.md](./skills/nanobanana/references/config.md).
## Shared `.env` Strategy
For this collection, the recommended setup is to keep one shared `.env` at your project root and let each skill inherit from it.
The current lookup order is:
1. `--env-file <path>`
2. Process environment variables
3. The nearest `.env` found by searching from the current working directory upward through parent directories
4. Built-in defaults
This means you can place a single `.env` in a project root and run `gpt-image-2` or `nanobanana` from nested subdirectories without duplicating config files.
## Adding a new skill
1. Scaffold a new folder under `skills/` (e.g. via `skill-creator`).
2. Write `SKILL.md` with a frontmatter `name` and a trigger-rich `description`.
3. Put deterministic logic in `scripts/`, deep docs in `references/`, templates in `assets/`.
4. Validate the layout (`quick_validate.py` from skill-creator, or equivalent).
5. Add an entry to the **Skills in this repo** table above.
## Conventions
- Skills must be self-contained; do not share code across skills at the repo level.
- Keep `SKILL.md` body ASCII-friendly when tooling reads it with the platform default encoding.
- Prefer the standard library and zero third-party dependencies in `scripts/` unless there is a clear reason not to.
- Never commit API keys or other secrets; rely on environment variables and `.env` files that are gitignored.
## License
MIT. See [LICENSE](./LICENSE).