agentleFS
rm2thaddeusrm2thaddeus/Aitor_Skills/imagen/SKILL.md

imagen

Skill4 starsChanged 10 months agoMITView on GitHub

Generate images using Google Gemini's image generation capabilities. Use this skill when the user needs to create, generate, or produce images for any purpose including UI mockups, icons, illustrations, diagrams, concept art, placeholder images, or visual representations.

  • Reads credentials
  • Installs packages

8 other projects use a version of this, 3 of them edited.

Adopted by

Most recently taken up by

The file

Files
SKILL.md

Imagen - AI Image Generation Skill

Overview

This skill generates images using Google Gemini's image generation model (gemini-3-pro-image-preview). It enables seamless image creation during any Claude Code session - whether you're building frontend UIs, creating documentation, or need visual representations of concepts.

Cross-Platform: Works on Windows, macOS, and Linux.

When to Use This Skill

Automatically activate this skill when:

  • User requests image generation (e.g., "generate an image of...", "create a picture...")
  • Frontend development requires placeholder or actual images
  • Documentation needs illustrations or diagrams
  • Visualizing concepts, architectures, or ideas
  • Creating icons, logos, or UI assets
  • Any task where an AI-generated image would be helpful

How It Works

  1. Takes a text prompt describing the desired image
  2. Calls Google Gemini API with image generation configuration
  3. Saves the generated image to a specified location (defaults to current directory)
  4. Returns the file path for use in your project

Usage

Python (Cross-Platform - Recommended)

# Basic usage
python scripts/generate_image.py "A futuristic city skyline at sunset"

# With custom output path
python scripts/generate_image.py "A minimalist app icon for a music player" "./assets/icons/music-icon.png"

# With custom size
python scripts/generate_image.py --size 2K "High resolution landscape" "./wallpaper.png"

Requirements

  • GEMINI_API_KEY environment variable must be set
  • Python 3.6+ (uses standard library only, no pip install needed)

Output

Generated images are saved as PNG files. The script returns:

  • Success: Path to the generated image
  • Failure: Error message with details

Examples

Frontend Development

User: "I need a hero image for my landing page - something abstract and tech-focused"
-> Generates and saves image, provides path for use in HTML/CSS

Documentation

User: "Create a diagram showing microservices architecture"
-> Generates visual representation, ready for README or docs

UI Assets

User: "Generate a placeholder avatar image for the user profile component"
-> Creates image in appropriate size for component use

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.