13 skills · sorted by relevance
Create Python workflows for generating images from text, restyling existing pictures, and filling selected regions. Using HuggingFace Diffusers, the skill explains composition controls, style adapters, generation settings, and ways to reduce memory use.
Feature-rich Stable Diffusion Web UI for image generation. Supports txt2img, img2img, inpainting, outpainting, LoRA, extensions, upscaling, and batch processing. Widely used desktop interface with an extensive extension ecosystem and API access.
The English summary is being prepared. Showing the original description.
Use when generating or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters, packaging, magazine covers, ads, key art, or instruction-based editing such as text swaps, recoloring, object removal or replacement, background swaps, lighting changes, and full restyles. Keywords: MAI Image 2.5, 2.5 Pro, 2.5 Edit, 2.5 Pro Edit, Microsoft, txt2img, img2img, typography, text rendering, image edit.
The English summary is being prepared. Showing the original description.
Use when generating or editing images with Luma Uni-1 models on Scenario via MCP: text-to-image, prompt-based editing of an existing image, style or character reference images with named roles, web search grounding for real-world subjects, rendering exact title text into posters, aspect ratio control, or choosing between Uni-1 Max and Uni-1. Keywords: Luma Labs, Uni-1, Photon, txt2img, img2img, image edit, reference images, webSearch, reasoning image model.
The English summary is being prepared. Showing the original description.
Use when generating or editing images with Scenario through MCP: text-to-image, image-to-image, instruction editing, inpainting or outpainting with a mask, background control, aspect ratio or resolution sizing, several outputs per run, or choosing between Scenario image models. Also when a run fails on prompt length, a plan-restricted model, or a reference image that was silently ignored. Keywords: txt2img, img2img, image edit, inpaint, mask, reference image, aspect ratio.
The English summary is being prepared. Showing the original description.
Use when generating or editing images with Grok Imagine models on Scenario via MCP: text-to-image, instruction editing with up to three reference images, posters, packaging, ads, or infographics with exact in-image text, photoreal shots from camera and lighting cues, extended aspect ratios up to 20:9 and 9:20, quality and resolution tiers, or batches of variations. Keywords: Grok Imagine Image 2.0, Image Quality, xAI, Aurora, Grok, txt2img, img2img, typography, 2K.
The English summary is being prepared. Showing the original description.
Use when generating or editing images with OpenAI's GPT Image models on Scenario via MCP: text-to-image, edits from reference images, inpainting with an alpha mask, in-image text for logos and infographics, transparent cutouts, pixel sizing up to 4K, quality tiers up to xhigh and max, input fidelity for product or face detail, or choosing between Flare, Sunburst, GPT Image 2 and 1.5. Keywords: GPT Image 2.5, GPT Image 2, OpenAI, DALL-E, gpt-image, ChatGPT image, txt2img, img2img, background.
The English summary is being prepared. Showing the original description.
Use when generating or editing images with Google's Gemini image models (Nano Banana) on Scenario via MCP: text-to-image, natural-language instruction editing, identity locking or style transfer from reference images, multi-image fusion, pulling stills from a video clip, Google Search grounding, thinking level tuning, 512 to 4K output, or choosing between Flash, Pro, and Lite. Keywords: Gemini 3.1 Flash, Gemini 3.0 Pro, Gemini 3.1 Lite, Nano Banana 2, Nano Banana Pro, txt2img, img2img.
The English summary is being prepared. Showing the original description.
Use when generating or editing images with Seedream models on Scenario via MCP: text-to-image, image-to-image editing with reference images, posters or packaging with exact in-image text (non-Latin scripts too), subject-preserving edits, sets of related images in one run, editing a transparent asset without losing its alpha, or splitting an image into transparent PNG layers with Layerize. Keywords: Seedream 5.0 Pro, Lite, Flash, 4.5, Layerize, ByteDance, txt2img, img2img, layer extraction.
The English summary is being prepared. Showing the original description.
Use when generating or editing images with Reve models on Scenario via MCP: text-to-image from a prompt alone, instruction edits (swap poster text, recolor a product, change materials, relight or restyle a scene), merging references with consistent subjects, blending up to 6 images into one composite, or choosing between Reve v2.1 and Reve Remix. Keywords: Reve v2.1, Reve Remix, Reve AI, txt2img, img2img, frame tags, compositing, style blending, text swap.
The English summary is being prepared. Showing the original description.
Swap an OUTFIT or transfer CLOTHING onto a person LOCALLY, keeping their face, pose and background. Use for "put this jacket on her", "change his shirt", "clothes swap", "try on", "outfit transfer", "virtual try-on", "dress her in", "wear this outfit". Prefer this over API/cloud edit nodes and over generic img2img/inpainting. NOT for identity-preserving edits that are not about clothing (background swaps, relighting, age/expression changes, object removal). Use a general image-edit workflow for those.
The English summary is being prepared. Showing the original description.
Build Ideogram 4 (Ideogram Ultra) txt2img and img2img workflows with the local open-weights model, dual conditional/unconditional models with DualModelGuider, Qwen3-VL text encoder, and structured JSON ("compositional deconstruction") prompts for strong text rendering and layout control
The English summary is being prepared. Showing the original description.
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.
The English summary is being prepared. Showing the original description.