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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.

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Generate, edit, composite, stream, and production-review still images with OpenAI GPT Image models. Use when an agent must choose between GPT Image 2 and legacy GPT Image/DALL-E integrations, select the Image API or Responses API, build prompts and reference-image workflows, use masks or multiple inputs, preserve identity or brand details, render in-image text, handle output files and partial images, estimate cost and rate limits, migrate deprecated image code, or apply OpenAI image safety, consent, privacy, provenance, and rights requirements. Do not use for OpenAI video or audio generation.

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通过Venice.ai的API，请代理编辑现有图片、放大图片或移除背景。适合修改已有图片，并根据用途调整和准备图片素材。

• 编辑现有图片
• 放大图片
• 移除图片背景

将落地页或产品网站的设计方案按区块生成为独立横向参考图，统一配色、字体与图片处理方式，同时变化构图、留白和按钮呈现，供开发人员或编程代理参考。

• 逐区块讨论落地页设计
• 研究首屏构图
• 向开发人员分享参考图

以实物商品照片为参考，按保留形状、颜色、材质和标志位置等特征的原则，生成电商主图、特点图、使用场景图及预览图库。

• 根据参考照片制作商品主图
• 用一张图展示商品特点
• 制作商品使用场景图

使用fal.ai托管的AI模型编辑现有图片，可转换画风、移除背景或多余物体，也可通过局部重绘修改指定区域。

• 转换图片画风
• 移除图片背景
• 消除图片中的多余物体

Audit website image file sizes against guidelines for photos, graphics, hero images, and thumbnails. Report oversized assets with target sizes, distinguish compression issues from dimension mismatches, and guide format conversion and delivery of smaller variants to mobile devices.

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• Listing oversized images and target file sizes
• Reviewing uploaded images managed by a CMS
• Reducing hero image and thumbnail file sizes

Generate images from written instructions and edit saved or uploaded images using them as references. Continue refining the latest image in a conversation, adjusting details such as brightness, background, or colors while specifying what to preserve.

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• Creating an image from a written description
• Editing an uploaded image
• Refining the latest generated image

Manage container images in Azure Container Registry using Python. Inspect repositories, tags, and image metadata, protect images from deletion, download image data, and identify older untagged images for cleanup.

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• Inspect image tags and metadata
• Protect production images from deletion
• Clean up older untagged images

Build image captioning, visual question answering, and text-based image search with BLIP-2. The skill explains model selection, batch processing, and memory-saving settings, with Python examples for connecting image understanding to language models.

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• Generating captions for multiple images
• Building a question-answering system for images
• Searching an image collection with text

Generate photos, illustrations, product mockups, and other bitmap images, or edit existing pictures with background changes, object removal, and transparent cutouts. Use reference images to guide variations and save selected assets for the project.

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• Create a website hero image or illustration
• Replace a product photo background or remove objects
• Make a transparent cutout

Generate text and images through a reverse-engineered Gemini Web API, an interface reconstructed from the web service. Use reference images for descriptions or variations, and continue conversations across requests with saved sessions.

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• Generating images from written prompts
• Describing the contents of reference images
• Creating variations from an existing image

Create artwork, product visuals, diagrams, and other images using the desktop's configured image provider. It also edits or combines supplied images and generates variations, turning requests into detailed instructions for composition, style, colors, and text.

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• Create illustrations or product visuals
• Generate diagrams with labels and connections
• Edit or combine supplied images

Build image captioning, visual question answering, and text-based image search with BLIP-2. The skill guides model selection, batch processing, and memory optimization, with examples for understanding images without training for each specific task.

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• Generate captions for multiple images
• Build a question-answering system for images
• Search an image collection using text

Create paid-ad images from a validated creative brief and brand profile using a configured image provider. Check dimensions, text consistency, and platform requirements, then save approved variants with a manifest recording generation details and costs.

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• Generate ad images from an approved campaign brief
• Create approved visual variants within a cost limit
• Check image dimensions and text placement

Describe photos, screenshots, and charts in text, generate images from written prompts, or edit existing images. Supports background replacement, transparent output, and edits limited to an area defined by a mask.

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• Get a text description of a photo or screenshot
• Generate a landscape image from a written prompt
• Replace a photo background or change its style

Upload local photos, images, or screenshots to Vercel Blob and receive public URLs for sharing or embedding in pull request comments and documents. Supports multiple files, custom path prefixes, and deterministic URLs.

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• Sharing screenshots in pull request comments
• Embedding local images in documents
• Uploading several images at once

Turn reference images into prompts for AI image generation by describing composition, lighting, colors, and materials. Receive a main prompt and a negative prompt that specifies unwanted features, tailored to the image’s visual medium.

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• Recreating a reference photo’s composition and lighting
• Turning an illustration’s visual style into a prompt
• Describing materials and backgrounds in product images

Generate a new image with different content while preserving a reference image’s style and layout. The skill describes the reference, rewrites that description, and can review generated layouts and retry within a set attempt limit.

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• Creating an image with new content in a reference style
• Replacing infographic content while preserving its layout
• Generating an image at a specified aspect ratio and size

Generate a single photoreal or designed image with OpenAI gpt-image via fal.ai. Supports gpt-image-1 (default, fixed sizes — the FAL fallback for Higgsfield's `gpt_image_2`) and gpt-image-2 (`openai/gpt-image-2`, custom output sizes up to 3840px). Routes to text-to-image or the edit variant depending on whether a reference image is provided. Use for photoreal character anchors, scene keyframes, and designed sheets (e.g. storyboards) where precise layout and legible text matter.

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Generate and download images through APIMart's asynchronous GPT-Image-2 API. Use when Codex needs APIMart image generation, GPT-Image-2 text-to-image, image-to-image with reference URLs or local image files, 1k/2k/4k output, aspect-ratio control, task polling, or saving APIMart image results locally.

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Backend-neutral image generation: create new raster images and looping GIF/WebP animations through the local one-file image-use CLI (formerly chatgpt-imagegen), using the user's ChatGPT subscription by default, the Codex backend as fallback, or an optional Gemini subscription — no API key or daemon. Triggers: image generation, generate an image, draw a picture, 画图, 画一张, 生成图片, 生图, 配图. Use for photos, illustrations, icons, hero banners, mockups, sprites, concept art, animation loops, and figures for documents, proposals, blog posts, or READMEs; save outputs in the workspace. Auto mode uses the logged-in ChatGPT browser via chrome-use. Gemini users can pass --backend gemini or agy. Proactively propose useful figures while authoring long-form content. Do not use for editing existing images, SVG/vector work, code-native graphics, established icon systems, explicit high-quality or transparent API output, or end-user image-generation services.

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Expert patterns for AI-powered image editing including inpainting, outpainting, ControlNet, image-to-image, and API integration with Replicate, Stability AI, and FalUse when "ai image editing, inpainting, outpainting, controlnet, image to image, remove object from image, extend image, flux inpaint, sdxl editing, image-editing, inpainting, outpainting, controlnet, stable-diffusion, flux, replicate, stability-ai, comfyui" mentioned.

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Perform image-based product search on the 1688 platform. Use an image URL to find visually similar supplier products, returning title, price, minimum order quantity, monthly sales, repurchase rate, trade score, and seller identity. Triggered when users mention 1688 image search, 1688 visual search, find supplier by image, reverse image search 1688, 1688 product sourcing by image, or Alibaba 1688 image search. Even if the user does not explicitly mention "image search," this skill should be triggered whenever a user provides an image URL and wants to find matching or similar products on the 1688 wholesale platform.

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