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skills/nanobanana-skill/SKILL.md

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+---
+name: nanobanana-skill
+description: 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.
+allowed-tools: Bash
+---
+
+# 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 ${CLAUDE_PLUGIN_ROOT}/skills/nanobanana-skill/requirements.txt` if not installed yet.
+3. **Executable**: `${CLAUDE_PLUGIN_ROOT}/skills/nanobanana-skill/nanobanana.py`
+
+## 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
+   python3 ${CLAUDE_PLUGIN_ROOT}/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
+   python3 ${CLAUDE_PLUGIN_ROOT}/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`
+
+## Examples
+
+### Generate a simple image
+
+```bash
+python3 ${CLAUDE_PLUGIN_ROOT}/skills/nanobanana-skill/nanobanana.py --prompt "A serene mountain landscape at sunset with a lake"
+```
+
+### Generate with specific size and output
+
+```bash
+python3 ${CLAUDE_PLUGIN_ROOT}/skills/nanobanana-skill/nanobanana.py \
+  --prompt "Modern minimalist logo for a tech startup" \
+  --size 1024x1024 \
+  --output "logo.png"
+```
+
+### Generate landscape image with high resolution
+
+```bash
+python3 ${CLAUDE_PLUGIN_ROOT}/skills/nanobanana-skill/nanobanana.py \
+  --prompt "Futuristic cityscape with flying cars" \
+  --size 1344x768 \
+  --resolution 2K \
+  --output "cityscape.png"
+```
+
+### Edit existing images
+
+```bash
+python3 ${CLAUDE_PLUGIN_ROOT}/skills/nanobanana-skill/nanobanana.py \
+  --prompt "Add a rainbow in the sky" \
+  --input photo.png \
+  --output "photo-with-rainbow.png"
+```
+
+### Use faster model
+
+```bash
+python3 ${CLAUDE_PLUGIN_ROOT}/skills/nanobanana-skill/nanobanana.py \
+  --prompt "Quick sketch of a cat" \
+  --model gemini-2.5-flash-image \
+  --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

skills/nanobanana-skill/nanobanana.py

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+#!/usr/bin/env python3
+# Generate or edit images using Google Gemini API
+import os
+import argparse
+import uuid
+from pathlib import Path
+from dotenv import load_dotenv
+from google import genai
+from google.genai import types
+from PIL import Image
+from io import BytesIO
+
+# Load environment variables
+load_dotenv(os.path.expanduser("~") + "/.nanobanana.env")
+
+# Google API configuration from environment variables
+api_key = os.getenv("GEMINI_API_KEY") or ""
+
+if not api_key:
+    raise ValueError(
+        "Missing GEMINI_API_KEY environment variable. Please check your .env file."
+    )
+
+# Initialize Gemini client
+client = genai.Client(api_key=api_key)
+
+# Aspect ratio to resolution mapping
+ASPECT_RATIO_MAP = {
+    "1024x1024": "1:1",  # 1:1
+    "832x1248": "2:3",  # 2:3
+    "1248x832": "3:2",  # 3:2
+    "864x1184": "3:4",  # 3:4
+    "1184x864": "4:3",  # 4:3
+    "896x1152": "4:5",  # 4:5
+    "1152x896": "5:4",  # 5:4
+    "768x1344": "9:16",  # 9:16
+    "1344x768": "16:9",  # 16:9
+    "1536x672": "21:9",  # 21:9
+}
+
+
+def main():
+    # Parse command-line arguments
+    parser = argparse.ArgumentParser(
+        description="Generate or edit images using Google Gemini API"
+    )
+    parser.add_argument(
+        "--prompt",
+        type=str,
+        required=True,
+        help="Prompt for image generation or editing",
+    )
+    parser.add_argument(
+        "--output",
+        type=str,
+        default=f"nanobanana-{uuid.uuid4()}.png",
+        help="Output image filename (default: nanobanana-<UUID>.png)",
+    )
+    parser.add_argument(
+        "--input", type=str, nargs="*", help="Input image files for editing (optional)"
+    )
+    parser.add_argument(
+        "--size",
+        type=str,
+        default="768x1344",
+        choices=list(ASPECT_RATIO_MAP.keys()),
+        help="Size/aspect ratio of the generated image (default: 768x1344 / 9:16)",
+    )
+    parser.add_argument(
+        "--model",
+        type=str,
+        default="gemini-3-pro-image-preview",
+        choices=["gemini-3-pro-image-preview", "gemini-2.5-flash-image"],
+        help="Model to use for image generation (default: gemini-3-pro-image-preview)",
+    )
+    parser.add_argument(
+        "--resolution",
+        type=str,
+        default="1K",
+        choices=["1K", "2K", "4K"],
+        help="Resolution of the generated image (default: 1K)",
+    )
+
+    args = parser.parse_args()
+
+    # Get aspect ratio from size
+    aspect_ratio = ASPECT_RATIO_MAP.get(args.size, "16:9")
+
+    # Build contents list for the API call
+    contents = []
+
+    # Check if input images are provided
+    if args.input and len(args.input) > 0:
+        # Use images.generate_content() with images for editing
+        print(f"Editing images with prompt: {args.prompt}")
+        print(f"Input images: {args.input}")
+        print(f"Aspect ratio: {aspect_ratio} ({args.size})")
+
+        # Add prompt first
+        contents.append(args.prompt)
+
+        # Add all input images
+        for img_path in args.input:
+            image = Image.open(img_path)
+            contents.append(image)
+    else:
+        print(f"Generating image (size: {args.size}) with prompt: {args.prompt}")
+        contents.append(args.prompt)
+
+    # Generate or edit image with config
+    response = client.models.generate_content(
+        model=args.model,
+        contents=contents,
+        config=types.GenerateContentConfig(
+            response_modalities=['TEXT', 'IMAGE'],
+            tools=[types.Tool(google_search=types.GoogleSearch())],
+            image_config=types.ImageConfig(
+                aspect_ratio=aspect_ratio,
+                image_size=args.resolution,
+            ),
+        ),
+    )
+
+    if (response.candidates is None
+        or len(response.candidates) == 0
+        or response.candidates[0].content is None
+        or response.candidates[0].content.parts is None):
+        raise ValueError("No data received from the API.")
+
+    # Extract image from response
+    image_saved = False
+    for part in response.candidates[0].content.parts:
+        if part.text is not None:
+            print(f"{part.text}", end="")
+        elif part.inline_data is not None and part.inline_data.data is not None:
+            image = Image.open(BytesIO(part.inline_data.data))
+
+            image.save(args.output)
+            image_saved = True
+            print(f"\n\nImage saved to: {args.output}")
+
+    if not image_saved:
+        print(f"\n\nWarning: No image data found in the API response. This usually means the model returned only text. Please try again with a different prompt to make image generation more clear.")
+
+
+if __name__ == "__main__":
+    main()

skills/nanobanana-skill/requirements.txt

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+python-dotenv
+httpx[socks]
+google-genai
+Pillow