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skills/gemini-imagen/SKILL.md

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+---
+name: gemini-imagegen
+description: Generate and edit images using Gemini API (Nano Banana Pro). Supports text-to-image, image editing, multi-turn refinement, Google Search grounding for factual accuracy, and composition from multiple reference images.
+---
+
+# Gemini Image Generation (Nano Banana Pro)
+
+Generate professional-quality images using Google's **Gemini 3 Pro Image** model (aka Nano Banana Pro). The environment variable `GEMINI_API_KEY` must be set.
+
+## Model
+
+**gemini-3-pro-image-preview** (Nano Banana Pro)
+- Resolution: Up to 4K (1K, 2K, 4K)
+- Built on Gemini 3 Pro with advanced reasoning and real-world knowledge
+- Best for: Professional assets, illustrations, diagrams, text rendering, product mockups
+- Features: Google Search grounding, automatic "Thinking" process for refined composition
+
+## Quick Start Scripts
+
+CRITICAL FOR AGENTS: These are executable scripts in your PATH. All scripts now default to **gemini-3-pro-image-preview**.
+
+### Text-to-Image
+```bash
+scripts/generate_image.py "A technical diagram showing microservices architecture" output.png
+```
+
+### Edit Existing Image
+```bash
+scripts/edit_image.py diagram.png "Add API gateway component with arrows showing data flow" output.png
+```
+
+### Multi-Turn Chat (Iterative Refinement)
+```bash
+scripts/multi_turn_chat.py
+```
+
+For high-resolution technical diagrams:
+```bash
+scripts/generate_image.py "Your prompt" output.png --size 4K --aspect 16:9
+```
+
+## Core API Pattern
+
+All image generation uses the `generateContent` endpoint with `responseModalities: ["TEXT", "IMAGE"]`:
+
+```python
+import os
+from google import genai
+
+client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
+
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=["Your prompt here"],
+)
+
+for part in response.parts:
+    if part.text:
+        print(part.text)
+    elif part.inline_data:
+        image = part.as_image()
+        image.save("output.png")
+```
+
+## Image Configuration Options
+
+Control output with `image_config`:
+
+```python
+from google.genai import types
+
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=[prompt],
+    config=types.GenerateContentConfig(
+        response_modalities=['TEXT', 'IMAGE'],
+        image_config=types.ImageConfig(
+            aspect_ratio="16:9",  # 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
+            image_size="4K"       # 1K, 2K, 4K (Nano Banana Pro supports up to 4K)
+        ),
+    )
+)
+```
+
+## Editing Images
+
+Pass existing images with text prompts:
+
+```python
+from PIL import Image
+
+img = Image.open("input.png")
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=["Add a sunset to this scene", img],
+)
+```
+
+## Multi-Turn Refinement
+
+Use chat for iterative editing:
+
+```python
+from google.genai import types
+
+chat = client.chats.create(
+    model="gemini-3-pro-image-preview",
+    config=types.GenerateContentConfig(response_modalities=['TEXT', 'IMAGE'])
+)
+
+response = chat.send_message("Create a logo for 'Acme Corp'")
+# Save first image...
+
+response = chat.send_message("Make the text bolder and add a blue gradient")
+# Save refined image...
+```
+
+## Prompting Best Practices
+
+### Core Prompt Structure
+Keep prompts concise and specific. Research shows prompts under 25 words achieve **30% higher accuracy**. Structure as:
+
+**Subject + Adjectives + Action + Location/Context + Composition + Lighting + Style**
+
+### Photorealistic Scenes
+Include camera details: lens type, lighting, angle, mood.
+> "Photorealistic close-up portrait, 85mm lens, soft golden hour light, shallow depth of field"
+
+### Stylized Art
+Specify style explicitly:
+> "Kawaii-style sticker of a happy red panda, bold outlines, cel-shading, white background"
+
+### Text in Images
+Be explicit about font style and placement:
+> "Logo with text 'Daily Grind' in clean sans-serif, black and white, coffee bean motif"
+
+### Product Mockups
+Describe lighting setup and surface:
+> "Studio-lit product photo on polished concrete, three-point softbox setup, 45-degree angle"
+
+### Technical Diagrams
+Be explicit about positions, relationships, and labels:
+> "Technical diagram: Component A at top, Component B at bottom. Arrow from A to B labeled 'HTTP GET'. Clean boxes, directional arrows, white background."
+
+## Advanced Features
+
+### Google Search Grounding
+Generate images based on real-time data:
+
+```python
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=["Visualize today's weather in Tokyo as an infographic"],
+    config=types.GenerateContentConfig(
+        response_modalities=['TEXT', 'IMAGE'],
+        tools=[{"google_search": {}}]
+    )
+)
+```
+
+### Multiple Reference Images (Up to 14)
+Combine elements from multiple sources:
+
+```python
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=[
+        "Create a group photo of these people in an office",
+        Image.open("person1.png"),
+        Image.open("person2.png"),
+        Image.open("person3.png"),
+    ],
+)
+```
+
+## 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": "Technical diagram showing RESTful API architecture"}]}]
+  }' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 --decode > output.png
+```
+
+## Notes
+
+- All generated images include SynthID watermarks
+- Image-only mode (`responseModalities: ["IMAGE"]`) won't work with Google Search grounding
+- For editing, describe changes conversationally—the model understands semantic masking
+- Be specific about positions, colors, labels, and relationships for best results