Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ratnesh-maurya/cursor-claude-personasnpx agentmods add skills/ratnesh-maurya/cursor-claude-personas/imagenWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ratnesh-maurya/cursor-claude-personas/imagen)<a href="https://agentmods.dev/skills/ratnesh-maurya/cursor-claude-personas/imagen"><img src="https://agentmods.dev/badge/skills/ratnesh-maurya/cursor-claude-personas/imagen/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ratnesh-maurya/cursor-claude-personas/imagen"><img src="https://agentmods.dev/badge/skills/ratnesh-maurya/cursor-claude-personas/imagen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.00547 |
| Opus 5 | $0.00013 | $0.00273 |
| Sonnet 5 | $0.00005 | $0.00109 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
imagen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 79 lines · 26 tokens per session scan A 2df938b0affb
imagen is a skill published in the GitHub repository ratnesh-maurya/cursor-claude-personas (8 stars, last pushed 5mo ago), licensed MIT. It adds 26 tokens to every session and 547 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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