Individual skill
diffusion-pro
Generate and edit images with diffusion models: prompting, seeds, CFG, img2img, inpainting, conditioning, and API integration. Use when adding AI image generation to apps or workflows.
skills/diffusion-pro/SKILL.md
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# Diffusion Pro
A practical guide to working with diffusion image models in products and creative workflows: prompt craft, reproducibility, image-to-image, inpainting, conditioned generation, and integrating generation APIs reliably.
## Overview
Diffusion models generate images by iteratively denoising random noise, guided by a text prompt (and optionally reference images or spatial controls). Three knobs dominate output quality: the **prompt** (what), the **seed** (which random starting point), and **guidance strength** (how literally to follow the prompt). Master those, add negative prompts and img2img, and you can produce consistent, art-directable results instead of slot-machine outputs.
## When to use
- Adding text-to-image generation to an app (avatars, illustrations, marketing creatives, thumbnails).
- Editing images: inpainting (replace a region), outpainting (extend), img2img (restyle).
- Building consistent character/style sets with seeds and reference images.
- Choosing between hosted APIs and local inference.