Agent skill · hairyf
imagine
AI image, sticker, icon, and seamless-texture generation for agents. Use when the user asks to create, generate, edit, or iterate on images, photos, illustrations, posters, stickers, icons, logos, sprites, textures, or mockups. Provides a zero-dependency Node.js script that calls GPT Image 2, Nano Banana (Gemini), SiliconFlow Qwen-Image, or other image models and saves the result to disk.
What it needs
About 2k tokens when loaded.
What this skill does
Image Gen Generate images through scripts/imagine.js, a zero-dependency Node.js CLI (Node 18+, no npm install) backed by multiple providers. It saves images to disk and prints the absolute paths. Quick start Model selection Priority for general images: GPT Image 2 (gpt-image-2) → Nano Banana (gemini-2.5-flash-image) → SiliconFlow Qwen-Image (Qwen/Qwen-Image) → OpenAI GPT Image (gpt-image-1). When a provider has no API key, fall back to the next configured one. Asset Recommended models (priority order) ------- ------------------------------------- Images / posters gpt-image-2 → gemini-2.5-flash-image → Qwen/Qwen-Image → gpt-image-1 Stickers / icons / logos Ideogram 3.0 (transparent) → gpt-image-1.5 / gpt-image-2 with --background transparent -f png → FLUX.2 pro Seamless textures Z-Image Turbo Tiling (fal.ai) → FLUX.2 pro → any strong model with a strict tiling prompt Specialist models outside the script's providers (Ideogram, fal tiling) are called through their own APIs; imagine.js covers OpenAI, SiliconFlow, Gemini, and OpenAI-compatible relays. Key workflows Transparent assets: --background transparent -f png (never jpeg); phrase stickers as "die-cut sticker, thick white border, bold clean shapes". Seamless textures: include "seamless, tileable, top-down, flat uniform lighting, no shadows, edges wrap perfectly". Text in images: GPT Image 2 is best for CJK/multilingual text; keep text short and quoted. Aspect ratio: Gemini via --aspect 16:9; OpenAI/SiliconFlow via -s WxH (Qwen native sizes like 1328x1328, 1664x928). Iterate cheaply: draft with Qwen/Qwen-Image / Nano Banana or -q low, render finals on gpt-image-2 with -q high; --seed for reproducible output. References — load on demand When Reference ------ ----------- Full CLI arguments, session details, exit codes core-usage First run with no API key configured (env keys, AGENTS.md merge) core-setup Debugging the pipeline or editing the scripts core-script
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills hairyf/imagine