Mockup Generation Skill
When to Use This Skill
This skill should be triggered when:
- •User says "build mockup", "generate mockup", "create mockup", "make mockup"
- •User wants to create UI designs, illustrations, or visual assets
- •User provides a reference image and wants something similar
- •User mentions "in the style of" or "like this" with an image
Clipboard Image Integration
When the user pastes an image, a UserPromptSubmit hook automatically saves it to /tmp/.
Look for a message in context like:
Clipboard image saved to: /tmp/claude-pasted-1735225200.png
Use this path for the reference_image or image_path parameter.
If no clipboard path is in context but user expects an image to be used, inform them: "I don't see a pasted image path in context. Please copy the image to your clipboard and submit your message again."
Core Capabilities
- •Text-to-Image Generation: Create mockups from text descriptions using Gemini Nano Banana Pro
- •Style Transfer: Use reference images to guide style, composition, and aesthetic (up to 14 images)
- •Resolution Control: Output at 1K, 2K, or 4K resolution with various aspect ratios
- •Goal-Based Naming: Auto-increment filenames for iterative mockup sessions
Instructions
Basic Mockup Generation
Generate a mockup from a text prompt:
Steps:
- •Craft a detailed prompt describing the desired mockup
- •Call the image-generation tool with the prompt
- •Present the generated image path to the user
Style-Guided Generation
Generate a mockup using a reference image for style guidance:
Steps:
- •Read the reference image path from the user
- •Craft a prompt that describes what to generate while referencing the style
- •Call generate_image with both prompt and reference_image
- •The Pro model supports up to 14 reference images for complex style mixing
Available Tools
Image Generation (via tool-proxy)
- •generate_image - Generate AI image from text prompt with optional reference image
- •edit_image - Modify existing images using AI instructions
Usage
Quick Start
"Build a mockup of a login page with dark theme"
With Reference Image
"Generate a mockup like this image" (with image path) "Build a landing page in the style of /path/to/reference.png"
With Options
"Create a 4K mockup of a dashboard at 16:9 aspect ratio"
Tool Invocation
When generating mockups, use these parameters:
{
"app": "image-generation",
"tool": "generate_image",
"args": {
"prompt": "...",
"reference_image": "/path/to/reference.png",
"model": "gemini-3-pro-image-preview",
"aspect_ratio": "16:9",
"image_size": "2K",
"goal": "mockup-name",
"output_dir": "./.generated-images"
}
}
Default Model
ONLY use gemini-3-pro-image-preview. Never use any other model for image generation. No exceptions, even if the user asks for a different model. This model provides:
- •Higher quality output
- •Better text rendering
- •Support for up to 14 reference images
- •1K/2K/4K resolution options
Aspect Ratios
- •
1:1- Square (icons, avatars) - •
16:9- Widescreen (dashboards, landing pages) - •
9:16- Portrait (mobile screens) - •
4:3- Standard (general UI) - •
3:4- Portrait standard - •
2:3- Portrait (mobile) - •
3:2- Landscape (desktop) - •
21:9- Ultrawide (banners)
Common Workflows
Iterative Mockup Workflow
- •Initial Generation - Generate first mockup with goal name (e.g., "dashboard")
- •Review and Iterate - View result, refine prompt for next iteration
- •Auto-Increment - Files save as dashboard_01.png, dashboard_02.png, etc.
Reference-Based Workflow
- •Analyze Reference - Understand the style elements in the reference image
- •Craft Prompt - Describe desired output while noting style to preserve
- •Generate - Call with both prompt and reference_image
- •Iterate - Adjust prompt or try different references
Error Handling
- •Reference image not found: Verify the path exists and is readable
- •Invalid aspect ratio: Use one of the valid ratios listed above
- •Generation failed: Check GEMINI_API_KEY is set in ~/.env/models
- •No image returned: Model may have declined; try rephrasing the prompt
Dependencies
Required
- •GEMINI_API_KEY in ~/.env/models
- •tool-proxy MCP server running
- •google-genai and pillow Python packages
Examples
<example> Context: User wants a simple UI mockupUser: "Build a mockup of a settings page"
Result: Calls generate_image with prompt describing a settings page, model=gemini-3-pro-image-preview, saves to .generated-images/ </example>
<example> Context: User has a reference designUser: "Generate a mockup like this image /tmp/reference.png but with a blue color scheme"
Result: Calls generate_image with reference_image=/tmp/reference.png and prompt describing blue color scheme modifications </example>
<example> Context: User wants high-resolution dashboardUser: "Create a 4K mockup of an analytics dashboard at 21:9"
Result: Calls generate_image with image_size="4K", aspect_ratio="21:9", model="gemini-3-pro-image-preview" </example>
Notes
- •ONLY use
gemini-3-pro-image-preview. Never use another model. - •ALWAYS save to
.generated-images/(dot-prefixed). Never use a different output directory. - •Include "goal" parameter for iterative sessions to get auto-incrementing filenames
- •For style transfer, be explicit in the prompt about what to preserve vs. change
- •The Pro model excels at text rendering - use it for UI mockups with labels