Results for “image”

OpenStack Glance image service skill for deploying, configuring, operating, and troubleshooting the VM image registry. Covers image upload/download, format management (qcow2, raw, vmdk, vhd, iso), backend storage selection (file, swift, ceph), image import methods (web-download, glance-direct, copy-image), metadata management, property protections, image sharing between projects, snapshot lifecycle, image caching, and storage usage monitoring. Use when deploying Glance via Kolla-Ansible, managing VM images, converting image formats, or troubleshooting image upload failures.

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OpenAI GPT Image generation and editing (gpt-image-2, 1.5, 1, mini). Text-to-image, mask-based inpainting, multi-reference composition, multi-turn conversational editing via Responses API, streaming with partial images. This skill should be used when generating or editing images via OpenAI's image models, when near-perfect text rendering in images is needed, when mask-based region-aware editing is required, when multi-turn conversational image editing is desired, or when streaming progressive image delivery is needed. Complements nano-banana-pro (Gemini) as a parallel image generation backend.

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Generate and edit high-quality images using Google's Nano Banana Pro (Gemini 3 Pro Image) AI model. Use this skill when working with AI image generation or editing tasks including (1) Creating images from text prompts with professional quality, (2) Editing existing images with natural language instructions, (3) Multi-turn iterative image refinement, (4) Product photography and marketing visuals, (5) Creating infographics and diagrams with text, (6) Photorealistic and artistic image generation, (7) Batch image generation workflows, (8) Testing and troubleshooting Gemini image generation API. Supports up to 4K resolution, multiple aspect ratios, reference images, and advanced prompting techniques for cinema-quality results.

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Image optimization analysis for SEO and performance. Checks alt text, file sizes, formats (WebP, AVIF), responsive images, lazy loading, CLS prevention, and Core Web Vitals image impact. Use when user says "image optimization", "alt text", "image SEO", "image size", "image audit", "WebP", "AVIF", "lazy loading", "CLS", "responsive images", or "Core Web Vitals images".

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Optimize web images for performance with Next.js Image, responsive srcset, AVIF/WebP, lazy loading, and blur placeholders. Activate on: image optimization, LCP improvement, responsive images, AVIF, blur placeholder, next/image. NOT for: image generation/editing (use image-gen skills), SVG icon systems (use design-system-creator).

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Generate or edit images using the OpenAI Image API (gpt-image-2). Use when the user asks to generate, create, draw, render, illustrate, mock up, or edit an image, icon, logo, mockup, illustration, OG image, blog hero, marketing asset, or similar visual. Also use when the user supplies a reference image and asks to modify, restyle, or remix it. Triggers on: "generate an image", "create an image", "make a picture of", "edit this image", "restyle this", "make a mockup of", "draw a", "render a", "illustration of".

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OpenAI API (developers.openai.com) の画像生成・画像入力リファレンス。 GPT Image 2.5 (`gpt-image-2.5-sunburst` / `flare`), Images API `images.generate` / `images.edit`, mask, reference images, quality xhigh / max, image prompting, image_generation tool (Responses API), vision (画像入力, detail, image tokens, cost calculator, vision fine-tuning)。 Sora 2 / Videos API は 2026-09-24 終了 (履歴のみ)。

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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Produce a set of product images to choose between — several styles, backgrounds or treatments of one product, for a listing, a store page or an ad — and quote the whole set's cost before any of it is spent. From a real product photo it edits that photo once per style, so the item stays identical across the set; for a fictional or prototype product with no photo it generates from text instead, and says what that costs in accuracy. Delegates to ofox-image-core. Use when a user asks for several product images at once, e.g. "give me 4 main images in different styles for this product", "a few background options for this photo", "some listing images for my shop", or "show this product on white, on wood, and in a lifestyle scene". Do not use for a single change to a single image (see image-edit), for video from a product photo (see seedance-product-video), or for one plain text-to-image render (that is ofox-image-core's `generate`).

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Create images, videos, and audio with fal.ai through MCP, a connection to external tools. Find suitable models, estimate costs, edit source images, generate speech, and create sounds that match video content.

• Creating thumbnails or product images from text
• Changing an existing image's style
• Turning a still image into a video

Classify images using written labels without additional training data, or find images that match a text query. This skill provides CLIP workflows for image-text similarity, batch processing, and storing searchable image representations in vector databases.

• Classify photos using written category labels
• Find images by describing their content
• Compare images with candidate descriptions

Use image generation through the Venice.ai API and explore available styles. This skill helps an agent identify the relevant image generation capabilities when planning an image creation task.

• Generating images through the Venice.ai API
• Checking available image styles
• Planning an image generation task with an agent

Create character, scene, and product images from structured descriptions of style, composition, lighting, and color. Guide generation with reference images and aspect ratio settings, using a Python script connected to a supported image generation service.

• Creating characters with specified clothing, era, and appearance
• Visualizing scenes with a chosen mood, weather, and lighting
• Producing product images with specified materials and viewing angles

Review website images for high-density displays, where standard assets can look blurry. Check higher-resolution versions, HTML and CSS image selection, delivery settings, and loading behavior, then identify specific files or components that need changes.

• Investigating blurry images on high-density displays
• Reviewing srcset for fixed-size and responsive images
• Checking high-resolution CSS background images

Audit web images that are larger than their displayed size and help serve suitable versions for different screens. Review image dimensions, responsive image settings, and Lighthouse findings, then provide updated HTML and steps to verify the changes.

• Finding oversized images on mobile pages
• Reviewing srcset and sizes against the actual layout
• Adding image variants for different screen widths

Audit website images and guide conversion to WebP and AVIF, formats that reduce image transfer size. Identify affected files, add fallback images, and review dimensions and loading behavior alongside the impact on initially visible content.

• Finding JPEG and PNG images to convert
• Adding WebP and AVIF sources with fallback images
• Reviewing CSS background image formats

Review website images and reduce file sizes while limiting visible quality changes. Check compression, formats, display dimensions, loading behavior, and delivery settings, then recommend suitable tools or build automation and verification in browser DevTools.

• Find oversized images on web pages
• Choose compression methods for photos and graphics
• Automate image compression during builds

Review website images for file format, size, dimensions, and loading behavior. Produce improved HTML with image variants for different screen sizes, suitable compression, and deferred loading where appropriate, while addressing loading speed and layout shifts.

• Auditing image sizes and formats on slow-loading pages
• Serving suitable image sizes for mobile and desktop screens
• Preventing layout shifts while images load

Review how a website behaves when images fail to load and add fallback images or meaningful placeholder content. Check loading behavior, consider loading placeholders, and use error logging and browser developer tools to investigate and verify fixes.

• Adding fallback images for broken image links
• Reviewing placeholders shown while images load
• Investigating image loading failures with logs and DevTools

Create and edit bitmap images, such as photos, illustrations, product mockups, and game assets. Use reference images for visual variations, replace backgrounds, remove objects, or make transparent cutouts while preserving specified parts of an existing image.

• Create photos or illustrations for a website
• Replace a product photo background or remove unwanted objects
• Make transparent cutouts

Build Java applications that analyze images with Azure AI Vision. Covers image descriptions, OCR for reading text, object and person detection, content tags, and suggested crop regions, with examples for authentication and handling results.

• Adding image descriptions to a Java application
• Extracting text from document images
• Detecting objects and people with their locations

Add GraalVM Native Image support to Java applications to build native executables. The skill adapts Maven or Gradle configuration, fixes build errors iteratively, and checks application behavior, startup time, and memory use.

• Adding native executable builds to a Java application
• Configuring native builds for Maven or Gradle
• Fixing reflection and resource errors in native builds

Generate or modify images through the Luma AI API using Photon models. The skill gathers image descriptions and options, supports reference images for visual guidance, and uses a bundled Python script to wait for completion and download results.

• Creating a landscape image for a website
• Generating square product images
• Guiding image style or composition with a reference

Turn written content into a series of one to ten illustrated image cards for social media. Choose from twelve visual styles, eight layouts, and three optional palettes, with content analysis and outline planning before image generation.

• Turning an article into social media image cards
• Creating illustrated step-by-step tutorials
• Presenting product comparisons as image cards

Choose a serving container for models deployed on SageMaker. Match the model type to a compatible image, retrieve its address from the AWS catalog, and check regional availability, CPU or GPU variants, and required host settings.

• Choose a container for an LLM deployment
• Select images for embeddings and rerankers
• Check regional image addresses and GPU compatibility