📦 deps(thirdparty): update snapshots

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+# Gemini API Key for Image Generation
+# Get your key from: https://aistudio.google.com/
+#
+# Set this as an environment variable in your shell profile (~/.zshrc or ~/.bashrc):
+#   export GEMINI_API_KEY="your_api_key_here"
+
+GEMINI_API_KEY=your_api_key_here
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+---
+name: image-generator
+description: Generate and edit images using Gemini's Nano Banana Pro model (gemini-3-pro-image-preview). Use this skill when the user asks you to generate images, create visuals, edit photos, create logos, generate product mockups, or perform any image generation/editing task.
+allowed-tools: Read, Write, Bash, WebFetch
+category: "media"
+risk: "safe"
+source: "official"
+source_repo: "dair-ai/dair-academy-plugins"
+source_type: "official"
+date_added: "2026-06-19"
+author: "DAIR.AI"
+license: "MIT"
+license_source: "https://github.com/dair-ai/dair-academy-plugins/blob/main/README.md#license"
+tags:
+  - dair-academy
+  - ai
+  - workflow
+tools:
+  - claude-code
+  - codex-cli
+  - cursor
+---
+
+# Image Generator
+
+## When to Use
+
+Use when this workflow matches the user request: Generate and edit images using Gemini's Nano Banana Pro model (gemini-3-pro-image-preview). Use this skill when the user asks you to generate images, create visuals, edit photos, create logos, generate product mockups, or perform any image generation/editing task.
+
+
+_Source: [dair-ai/dair-academy-plugins](https://github.com/dair-ai/dair-academy-plugins) (MIT)._
+
+This skill generates and edits images using Google's Gemini Nano Banana Pro model (`gemini-3-pro-image-preview`).
+
+## IMPORTANT: Setup Required
+
+Before using this skill, the user must set the `GEMINI_API_KEY` environment variable:
+
+1. Get a free API key from [Google AI Studio](https://aistudio.google.com/)
+2. Export the key in your shell profile (`~/.zshrc`, `~/.bashrc`, etc.):
+   ```bash
+   export GEMINI_API_KEY="your_api_key_here"
+   ```
+3. Restart your terminal or run `source ~/.zshrc` (or `~/.bashrc`)
+
+**The skill will not work without this configuration.**
+
+## Pre-flight Check
+
+Before making any API call, verify the key is set:
+
+```bash
+if [ -z "$GEMINI_API_KEY" ]; then
+  echo "ERROR: GEMINI_API_KEY is not set. Please export it in your shell profile."
+  exit 1
+fi
+```
+
+If the key is missing, stop and tell the user to set it using the instructions above.
+
+## Configuration
+
+**Model**: `gemini-3-pro-image-preview`
+
+**API Key**: Read from the `GEMINI_API_KEY` environment variable
+
+## Iterating on User-Provided Images
+
+When the user provides a path to an image they want to edit or iterate on, use this workflow:
+
+### Step 1: Read and encode the image to base64
+
+```bash
+# Get the image path from user
+IMG_PATH="/path/to/user/image.png"
+
+# Detect mime type
+if [[ "$IMG_PATH" == *.png ]]; then
+    MIME_TYPE="image/png"
+elif [[ "$IMG_PATH" == *.jpg ]] || [[ "$IMG_PATH" == *.jpeg ]]; then
+    MIME_TYPE="image/jpeg"
+elif [[ "$IMG_PATH" == *.webp ]]; then
+    MIME_TYPE="image/webp"
+else
+    MIME_TYPE="image/png"
+fi
+
+# Encode to base64 (works on both macOS and Linux)
+if [[ "$(uname)" == "Darwin" ]]; then
+    IMG_BASE64=$(base64 -i "$IMG_PATH")
+else
+    IMG_BASE64=$(base64 -w0 "$IMG_PATH")
+fi
+```
+
+### Step 2: Send image with edit prompt (File-Based Approach)
+
+**IMPORTANT:** Always use a file-based approach for the request body. Base64-encoded images are too large for command-line arguments and will cause "argument list too long" errors.
+
+```bash
+# User's edit request
+EDIT_PROMPT="Add a santa hat to the person in this image"
+
+# Write request to a JSON file (avoids command line length limits)
+cat > /tmp/gemini_request.json << JSONEOF
+{
+  "contents": [{
+    "parts": [
+      {"text": "$EDIT_PROMPT"},
+      {
+        "inline_data": {
+          "mime_type": "$MIME_TYPE",
+          "data": "$IMG_BASE64"
+        }
+      }
+    ]
+  }],
+  "generationConfig": {
+    "responseModalities": ["TEXT", "IMAGE"]
+  }
+}
+JSONEOF
+
+# Call the API using the file
+curl -s -X POST \
+  "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
+  -H "x-goog-api-key: $GEMINI_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d @/tmp/gemini_request.json > /tmp/gemini_response.json
+```
+
+### Step 3: Extract and save the edited image
+
+```bash
+# Extract image from response and save
+python3 -c "
+import json
+import base64
+
+with open('/tmp/gemini_response.json') as f:
+    data = json.load(f)
+
+for part in data['candidates'][0]['content']['parts']:
+    if 'inlineData' in part:
+        img_data = part['inlineData']['data']
+        mime = part['inlineData']['mimeType']
+        ext = 'png' if 'png' in mime else 'jpg'
+        with open('edited_image.' + ext, 'wb') as out:
+            out.write(base64.b64decode(img_data))
+        print(f'Saved: edited_image.{ext}')
+    elif 'text' in part:
+        print(part['text'])
+"
+```
+
+### Complete Example (File-Based)
+
+For iterating on images, always use file-based requests:
+
+```bash
+# Variables
+IMG_PATH="/path/to/image.png"
+EDIT_PROMPT="Make the background a sunset beach"
+OUTPUT_PATH="edited_output.png"
+# Detect mime type and encode
+MIME_TYPE=$([[ "$IMG_PATH" == *.png ]] && echo "image/png" || echo "image/jpeg")
+IMG_BASE64=$(base64 -i "$IMG_PATH" 2>/dev/null || base64 -w0 "$IMG_PATH")
+
+# Write request to file (required - base64 images are too large for command line)
+cat > /tmp/gemini_request.json << JSONEOF
+{
+  "contents": [{
+    "parts": [
+      {"text": "$EDIT_PROMPT"},
+      {"inline_data": {"mime_type": "$MIME_TYPE", "data": "$IMG_BASE64"}}
+    ]
+  }],
+  "generationConfig": {
+    "responseModalities": ["TEXT", "IMAGE"]
+  }
+}
+JSONEOF
+
+# Call API and extract image
+curl -s -X POST \
+  "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
+  -H "x-goog-api-key: $GEMINI_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d @/tmp/gemini_request.json > /tmp/gemini_response.json
+
+# Save the output image
+python3 -c "
+import json, base64
+with open('/tmp/gemini_response.json') as f:
+    data = json.load(f)
+for part in data.get('candidates', [{}])[0].get('content', {}).get('parts', []):
+    if 'inlineData' in part:
+        with open('$OUTPUT_PATH', 'wb') as f:
+            f.write(base64.b64decode(part['inlineData']['data']))
+        print('Saved: $OUTPUT_PATH')
+"
+```
+
+### Multi-Image Input (Combine/Compose)
+
+To combine elements from multiple images (also uses file-based approach):
+
+```bash
+IMG1_PATH="/path/to/image1.png"
+IMG2_PATH="/path/to/image2.png"
+PROMPT="Put the dress from the first image on the person in the second image"
+IMG1_BASE64=$(base64 -i "$IMG1_PATH" 2>/dev/null || base64 -w0 "$IMG1_PATH")
+IMG2_BASE64=$(base64 -i "$IMG2_PATH" 2>/dev/null || base64 -w0 "$IMG2_PATH")
+
+# Write request to file
+cat > /tmp/gemini_request.json << JSONEOF
+{
+  "contents": [{
+    "parts": [
+      {"text": "$PROMPT"},
+      {"inline_data": {"mime_type": "image/png", "data": "$IMG1_BASE64"}},
+      {"inline_data": {"mime_type": "image/png", "data": "$IMG2_BASE64"}}
+    ]
+  }],
+  "generationConfig": {"responseModalities": ["TEXT", "IMAGE"]}
+}
+JSONEOF
+
+curl -s -X POST \
+  "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
+  -H "x-goog-api-key: $GEMINI_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d @/tmp/gemini_request.json > /tmp/gemini_response.json
+```
+
+## Capabilities
+
+### Text-to-Image Generation
+- Generate high-quality images from text descriptions
+- Support for photorealistic, stylized, and artistic outputs
+- Accurate text rendering in images (logos, infographics, diagrams)
+
+### Image Editing
+- Add or remove elements from images
+- Inpainting with semantic masking (edit specific parts)
+- Style transfer (apply artistic styles to photos)
+- Multi-image composition (combine elements from multiple images)
+
+### Advanced Features
+- **High Resolution**: 1K, 2K, or 4K output
+- **Aspect Ratios**: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
+- **Google Search Grounding**: Generate images based on real-time data
+- **Multi-turn Editing**: Iteratively refine images through conversation
+- **Up to 14 Reference Images**: Combine multiple inputs for complex compositions
+
+## API Usage
+
+### Basic Text-to-Image (Python)
+
+```python
+from google import genai
+from google.genai import types
+
+client = genai.Client()
+
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=["Your prompt here"],
+    config=types.GenerateContentConfig(
+        response_modalities=['TEXT', 'IMAGE'],
+        image_config=types.ImageConfig(
+            aspect_ratio="16:9",  # Optional
+            image_size="2K"       # Optional: "1K", "2K", "4K"
+        )
+    )
+)
+
+for part in response.parts:
+    if part.text is not None:
+        print(part.text)
+    elif part.inline_data is not None:
+        image = part.as_image()
+        image.save("generated_image.png")
+```
+
+### Basic Text-to-Image (JavaScript)
+
+```javascript
+import { GoogleGenAI } from "@google/genai";
+import * as fs from "node:fs";
+
+const ai = new GoogleGenAI({});
+
+const response = await ai.models.generateContent({
+    model: "gemini-3-pro-image-preview",
+    contents: "Your prompt here",
+    config: {
+        responseModalities: ['TEXT', 'IMAGE'],
+        imageConfig: {
+            aspectRatio: "16:9",
+            imageSize: "2K"
+        }
+    }
+});
+
+for (const part of response.candidates[0].content.parts) {
+    if (part.text) {
+        console.log(part.text);
+    } else if (part.inlineData) {
+        const buffer = Buffer.from(part.inlineData.data, "base64");
+        fs.writeFileSync("generated_image.png", buffer);
+    }
+}
+```
+
+### REST API (curl)
+
+```bash
+curl -s -X POST \
+  "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
+  -H "x-goog-api-key: $GEMINI_API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "contents": [{
+      "parts": [{"text": "Your prompt here"}]
+    }],
+    "generationConfig": {
+      "responseModalities": ["TEXT", "IMAGE"],
+      "imageConfig": {
+        "aspectRatio": "16:9",
+        "imageSize": "2K"
+      }
+    }
+  }' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 --decode > output.png
+```
+
+### Image Editing (with input image)
+
+```python
+from google import genai
+from google.genai import types
+from PIL import Image
+
+client = genai.Client()
+
+input_image = Image.open('input.png')
+prompt = "Add a wizard hat to the cat in this image"
+
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=[prompt, input_image],
+    config=types.GenerateContentConfig(
+        response_modalities=['TEXT', 'IMAGE']
+    )
+)
+
+for part in response.parts:
+    if part.inline_data is not None:
+        image = part.as_image()
+        image.save("edited_image.png")
+```
+
+### Multi-Image Composition
+
+```python
+from google import genai
+from google.genai import types
+from PIL import Image
+
+client = genai.Client()
+
+image1 = Image.open('dress.png')
+image2 = Image.open('model.png')
+prompt = "Put the dress from the first image on the model from the second image"
+
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=[image1, image2, prompt],
+    config=types.GenerateContentConfig(
+        response_modalities=['TEXT', 'IMAGE'],
+        image_config=types.ImageConfig(
+            aspect_ratio="3:4",
+            image_size="2K"
+        )
+    )
+)
+```
+
+### With Google Search Grounding
+
+```python
+from google import genai
+from google.genai import types
+
+client = genai.Client()
+
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents="Visualize the current weather forecast for San Francisco",
+    config=types.GenerateContentConfig(
+        response_modalities=['TEXT', 'IMAGE'],
+        image_config=types.ImageConfig(aspect_ratio="16:9"),
+        tools=[{"google_search": {}}]
+    )
+)
+```
+
+## Prompting Best Practices
+
+### 1. Be Descriptive, Not Keyword-Based
+Instead of: `cat, wizard hat, cute`
+Write: `A fluffy orange cat wearing a small knitted wizard hat, sitting on a wooden floor with soft natural lighting from a window`
+
+### 2. Specify Style and Mood
+- Photography terms: "shot with 85mm lens", "soft bokeh background", "golden hour lighting"
+- Artistic styles: "in the style of Van Gogh", "minimalist illustration", "photorealistic"
+- Mood: "warm and cozy atmosphere", "dramatic noir lighting"
+
+### 3. For Text in Images
+Be explicit about:
+- The exact text to render
+- Font style (descriptively): "clean, bold, sans-serif font"
+- Placement and size
+
+### 4. For Editing
+- Describe what to change and what to preserve
+- Use "keep everything else unchanged"
+- Reference specific elements clearly
+
+### 5. For Product/Commercial Images
+Mention:
+- Lighting setup: "three-point softbox lighting"
+- Background: "clean white studio background"
+- Camera angle: "slightly elevated 45-degree shot"
+
+## Resolution and Aspect Ratio Reference
+
+| Aspect Ratio | 1K Resolution | 2K Resolution | 4K Resolution |
+|--------------|---------------|---------------|---------------|
+| 1:1          | 1024x1024     | 2048x2048     | 4096x4096     |
+| 16:9         | 1376x768      | 2752x1536     | 5504x3072     |
+| 9:16         | 768x1376      | 1536x2752     | 3072x5504     |
+| 3:2          | 1264x848      | 2528x1696     | 5056x3392     |
+| 2:3          | 848x1264      | 1696x2528     | 3392x5056     |
+
+## Common Use Cases
+
+### Logo Creation
+```
+Create a modern, minimalist logo for a coffee shop called 'The Daily Grind'.
+The text should be in a clean, bold, sans-serif font.
+Black and white color scheme. Put the logo in a circle.
+```
+
+### Product Photography
+```
+A high-resolution, studio-lit product photograph of a minimalist ceramic
+coffee mug in matte black on a polished concrete surface. Three-point
+softbox lighting with soft, diffused highlights. Slightly elevated
+45-degree camera angle. Sharp focus on steam rising from the coffee.
+```
+
+### Style Transfer
+```
+Transform this photograph of a city street at night into Vincent van Gogh's
+'Starry Night' style. Preserve the composition but render with swirling,
+impasto brushstrokes and deep blues with bright yellows.
+```
+
+### Infographic
+```
+Create a vibrant infographic explaining photosynthesis as a recipe.
+Show "ingredients" (sunlight, water, CO2) and "finished dish" (sugar/energy).
+Style like a colorful kids' cookbook, suitable for 4th graders.
+```
+
+## Error Handling
+
+Common issues:
+- **No image returned**: Check that `response_modalities` includes `'IMAGE'`
+- **Safety filters**: Some prompts may be blocked; try rephrasing
+- **Rate limits**: Implement exponential backoff for retries
+- **Large images**: For 4K, ensure sufficient timeout settings
+
+## Dependencies
+
+To use the Python SDK:
+```bash
+pip install google-genai pillow
+```
+
+For JavaScript:
+```bash
+npm install @google/genai
+```
+
+## Important Notes
+
+- All generated images include a SynthID watermark
+- The model uses a "thinking" process for complex prompts
+- For best text rendering, generate text first, then request image with that text
+- Images are not stored by the API - save outputs locally
+
+
+## Limitations
+
+- Requires the upstream tool, account, API key, or local setup when the workflow names one.
+- Does not authorize destructive, production, paid, or external-message actions without explicit user approval.
+- Validate generated artifacts or recommendations against the user's real sources before treating them as final.