Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add prenats/claude-imagine --skill image-generategit clone --depth 1 https://github.com/prenats/claude-imagineWrote 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/prenats/claude-imagine/image-generate)<a href="https://agentmods.dev/skills/prenats/claude-imagine/image-generate"><img src="https://agentmods.dev/badge/skills/prenats/claude-imagine/image-generate/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/prenats/claude-imagine/image-generate"><img src="https://agentmods.dev/badge/skills/prenats/claude-imagine/image-generate.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 | $0.00040 | $0.02444 |
| Opus 5.5 | $0.00016 | $0.00978 |
| Sonnet 5.5 | $0.00008 | $0.00489 |
| Haiku 4.5 | $0.00004 | $0.00244 |
Grade A, and why
image-generate 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 1mo 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/image-generate — AI-Powered Image Generation
Transform short descriptions into ultra-detailed, unique prompts, then generate real images via the image generation server.
When to Activate
- User asks to generate, create, or make an image
- User needs a hero image, banner, icon, product photo, avatar, logo, or thumbnail
- Working on HTML with
<img>tags needing real images - Building landing pages, blogs, e-commerce, portfolios, or dashboards
- Any project where visuals would improve quality
- User says "generate an image of..." or similar
Usage
/image-generate a cyberpunk cityscape at night
/image-generate a minimalist app icon --type ICON --style vector
/image-generate product photo of leather boots --type PRODUCT --model opus --seed 42
/image-generate hero image for a wellness brand --output images/hero.png
Argument Parsing
Parse $ARGUMENTS for:
- Description — everything that is not a flag (required)
--type TYPE— ICON, THUMBNAIL, BACKGROUND, TEXTURE, AVATAR, CONTENT, BANNER, PRODUCT, LOGO, HERO, FEATURED. Default: infer.--style STYLE— photorealistic, illustration, watercolor, oil_painting, digital_art, vector, pixel_art, sketch, 3d_render, anime, cinematic, minimalist, comic, vintage, abstract. Default: infer.--mood MOOD— energetic, calm, dramatic, playful, mysterious, elegant, warm, cool, professional, whimsical, dark, bright. Default: infer.--lighting LIGHTING— natural, studio, dramatic, soft, golden_hour, neon, backlit, rimlight, ambient, high_key, low_key, volumetric. Default: infer.--composition COMP— centered, rule_of_thirds, symmetrical, diagonal, framing, leading_lines, close_up, wide_angle, birds_eye, low_angle, panoramic, negative_space. Default: infer.--palette PALETTE— warm, cool, monochrome, pastel, vibrant, earth_tones, neon, dark. Default: infer.--quality QUALITY— fast, standard, high. Default: infer from type.--output PATH— output file path. Default:generated/<slugified-description>.png--seed NUMBER— for reproducibility. Default: random.--model MODEL— Claude model for prompt engineering: haiku, sonnet, opus. Default: current session.
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.
- 1mo ago First seen · 223 lines · 40 tokens per session scan A a661229e8d85
image-generate is a skill published in the GitHub repository prenats/claude-imagine (2 stars, last pushed 4mo ago), licensed MIT. It adds 40 tokens to every session and 2,444 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
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