nano-banana
Nano Banana generates or edits images using three different model options (standard, pro, and legacy), with support for single image editing, multi-image composition up to 14 images, and customizable resolutions up to 4K. Use this skill when users request image generation, image editing, or image composition tasks through natural language prompts.
git clone --depth 1 https://github.com/nexu-io/nexu /tmp/nano-banana && cp -r /tmp/nano-banana/skills/nexubot/nano-banana ~/.claude/skills/nano-bananaSKILL.md
# Nano Banana — Image Generation
Image generation script supporting three models. Requires `sharp` for input image compression (auto-installed on first run).
## Models
| Flag | Notes |
|------|-------|
| `--model nano-banana` | **Default.** Fast, good quality. |
| `--model nano-banana-pro` | Highest quality, slower. |
| `--model nano-banana-2` | Legacy model. |
## Generate an image
```bash
node {baseDir}/scripts/generate-image.js --prompt "a cat sitting on mars" --filename "cat-on-mars.png"
```
## Edit a single image
```bash
node {baseDir}/scripts/generate-image.js \
--prompt "make the sky purple" \
--filename "edited.png" \
-i "/path/to/input.png" \
--model nano-banana-pro
```
## Multi-image composition (up to 14 images)
```bash
node {baseDir}/scripts/generate-image.js \
--prompt "combine these into a collage" \
--filename "collage.png" \
-i img1.png -i img2.png -i img3.png
```
## Options
| Flag | Short | Default | Description |
|------|-------|---------|-------------|
| `--prompt` | `-p` | required | Image description or editing instruction |
| `--filename` | `-f` | required | Output filename |
| `--input-image` | `-i` | — | Input image(s), repeatable, max 14 |
| `--model` | — | `nano-banana` | `nano-banana`, `nano-banana-pro`, or `nano-banana-2` |
| `--resolution` | `-r` | `1K` | `1K`, `2K`, or `4K` |
| `--aspect-ratio` | — | — | e.g. `1:1`, `16:9`, `4:3`, `3:4`, `9:16` |
## API key
The API key is pre-configured on this machine. No flags or environment variables needed.
## Input image handling
All input images are sent as inline base64. Images over 500 KB are automatically compressed to JPEG and resized to fit under the limit. This keeps requests fast and avoids File API auth issues with the enterprise endpoint.
## Output
Relative filenames are saved to `$OPENCLAW_STATE_DIR/media/outbound/{slugid}/nano-banana/{filename}`. Absolute paths are used as-is. Absolute paths are used as-is. Use timestamps in filenames to avoid overwrites: `cat-on-mars-20260304-165000.png`.
## Sending images to the user
The script prints a `MEDIA: <absolute-path>` line on stdout. **You MUST include this exact MEDIA: line in your reply text** so the image is delivered as an attachment in Discord/Slack/chat.
Example reply:
```
Here's your image!
MEDIA: /Users/alche/.openclaw/media/outbound/my-bot/nano-banana/cat-on-mars.png
```
Rules:
- Copy the `MEDIA:` line from the script output into your reply verbatim — this is how images get sent
- Do NOT read the generated image back with the read tool
- Do NOT try to base64 encode or manually attach the image
- The `MEDIA:` line must be on its own line in your responseUse when the user asks to process, triage, fetch, view, count, list, or resolve review feedback in a GitHub PR. Supports both CodeRabbit and Codex review workflows. In this workflow, “real review feedback” is strictly defined as actionable inline comments; for CodeRabbit, exclude review summaries and nitpicks, and for Codex, exclude review summary cards and use PR main-thread reactions only as status signals.
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|
Fetch GitHub issues, spawn sub-agents to implement fixes and open PRs, then monitor and address PR review comments. Usage: /gh-issues [owner/repo] [--label bug] [--limit 5] [--milestone v1.0] [--assignee @me] [--fork user/repo] [--watch] [--interval 5] [--reviews-only] [--cron] [--dry-run] [--model glm-5] [--notify-channel -1002381931352]
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