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* chore: upgrade maintenance scripts to robust PyYAML parsing - Replaces fragile regex frontmatter parsing with PyYAML/yaml library - Ensures multi-line descriptions and complex characters are handled safely - Normalizes quoting and field ordering across all maintenance scripts - Updates validator to strictly enforce description quality * fix: restore and refine truncated skill descriptions - Recovered 223+ truncated descriptions from git history (6.5.0 regression) - Refined long descriptions into concise, complete sentences (<200 chars) - Added missing descriptions for brainstorming and orchestration skills - Manually fixed imagen skill description - Resolved dangling links in competitor-alternatives skill * chore: sync generated registry files and document fixes - Regenerated skills index with normalized forward-slash paths - Updated README and CATALOG to reflect restored descriptions - Documented restoration and script improvements in CHANGELOG.md * fix: restore missing skill and align metadata for full 955 count - Renamed SKILL.MD to SKILL.md in andruia-skill-smith to ensure indexing - Fixed risk level and missing section in andruia-skill-smith - Synchronized all registry files for final 955 skill count * chore(scripts): add cross-platform runners and hermetic test orchestration * fix(scripts): harden utf-8 output and clone target writeability * fix(skills): add missing date metadata for strict validation * chore(index): sync generated metadata dates * fix(catalog): normalize skill paths to prevent CI drift * chore: sync generated registry files * fix: enforce LF line endings for generated registry files
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name, description, risk, source, date_added
| name | description | risk | source | date_added |
|---|---|---|---|---|
| imagen | AI image generation skill powered by Google Gemini, enabling seamless visual content creation for UI placeholders, documentation, and design assets. | safe | https://github.com/sanjay3290/ai-skills/tree/main/skills/imagen | 2026-02-27 |
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
- Takes a text prompt describing the desired image
- Calls Google Gemini API with image generation configuration
- Saves the generated image to a specified location (defaults to current directory)
- 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_KEYenvironment 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