「image」の検索結果

Use when ONE static image needs a full brief for a designer or photographer — visual objective, concept and mood, composition, overlay copy, colors and fonts read from the brand guideline, per-channel dimensions, deliverables, and approval criteria. Trigger on 'image brief', 'banner brief', 'thumbnail brief', 'brief for the designer', 'how should this graphic look', 'the design came back wrong again'. Also use when the user has a post idea and needs to explain the visual. Not for — a multi-slide sequence, see `43-carousel-brief-global`; tool-level production steps in Canva or Figma, see `45-design-tool-brief-global`; generating the image with AI, see `30-design-master-global`; an urgent same-day swap, see `48-quick-visual-brief-global`.

日本語の概要は準備中です。原文の説明を表示しています。

把图片、截图、海报、PPT 页面截图、HTML 或 SVG 设计稿转换成可编辑 PPTX 的 Codex skill。 当用户需要 image2ppt、image2pptx、图片转 PPT、截图转 PPT、PNG/JPEG 转可编辑幻灯片、 HTML/SVG 转 PPTX、把设计图拆成图片组件和文本框再拼成 PowerPoint、 或希望复用 Codex 内置生图能力把平面图重建为多元素可编辑 PPT 时，应该使用此 skill。 在 Codex 中处理二进制图片时，默认结合 imagegen skill：先用 Codex 视觉理解版式， 再用内置图片生成/编辑能力生成或清理多个组件图片，最后用本 skill 的脚本拼装 PPTX。

日本語の概要は準備中です。原文の説明を表示しています。

Generate, derive, optimize, and diagnose structured AI image prompts for luminous cinematic Eastern xianxia environments under one inherited master canon with measurable divine scale, fixed five-layer space, 40–60% content-bearing breathing air, monumental Eastern architecture, railing-free edges, and coherent immortals and costume. Cover one-location scenic landmarks, immense inhabited celestial realms, cloud-borne palace cities, high-key Eastern sky-megastructure imagery, and the explicit `仙界大境原典` creative route. Use for Chinese fantasy scenery, places where immortals live, heavenly capitals, colossal celestial gates, architectural fragments above cloud seas, measurable divine scale, unusual framing, color and lighting direction, style-preserving variants, prompt rewrites, diagnosis, or direct image generation. Support 16:9, 21:9, 4:3, 3:2, 4:5, and 9:16; default to 16:9 for one prompt and never infer a nine-image series from a vertical ratio.

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Brand-consistent asset sets from DESIGN.md — hero, section illustrations, icon sets, OG image — generated through whichever channel the user actually has (grok build image_gen, Codex $imagegen, Gemini, xAI/Recraft/OpenAI keys) as recorded by omd:setup, with a provenance and cost ledger. No channel → prompt pack + manual queue, never stock. Trigger: '이미지 세트 만들어', '에셋 생성', 'generate assets', 'hero image', '아이콘 세트', 'OG 이미지'.

日本語の概要は準備中です。原文の説明を表示しています。

Brand-consistent asset sets from DESIGN.md — hero, section illustrations, icon sets, OG image — generated through whichever channel the user actually has (grok build image_gen, Codex $imagegen, Gemini, xAI/Recraft/OpenAI keys) as recorded by omd:setup, with a provenance and cost ledger. No channel → prompt pack + manual queue, never stock. Trigger: '이미지 세트 만들어', '에셋 생성', 'generate assets', 'hero image', '아이콘 세트', 'OG 이미지'.

日本語の概要は準備中です。原文の説明を表示しています。

Use when you need framework-agnostic Docker and container image guidance for Java projects - Dockerfile design, multi-stage Maven builds, jlink custom runtimes, micro runtime distributions such as Alpaquita, JVM container ergonomics, non-root execution, image metadata, .dockerignore, reproducible builds, vulnerability scanning, SBOM awareness, and production-safe container defaults. This should trigger for requests such as Review Java Dockerfile; Improve Docker image security; Add jlink runtime to a Java container; Add containerization to a Java project; Optimize Java container image size; Review Docker build reproducibility. Part of Plinth Toolkit

日本語の概要は準備中です。原文の説明を表示しています。

AI product photography with studio lighting, lifestyle shots, and packshot conventions. Covers angles, backgrounds, shadow types, hero shots, and e-commerce image requirements. Use for: product photos, e-commerce images, Amazon listings, packshots, lifestyle photography. Triggers: product photography, product photo, packshot, e-commerce photography, product shot, product image, studio photography, lifestyle product, amazon product photo, product listing image, hero shot, product mockup, commercial photography

日本語の概要は準備中です。原文の説明を表示しています。

Generate AI videos with Google Veo, Seedance 2.0, HappyHorse, Wan, Grok and 40+ models via inference.sh CLI. Models: Veo 3.1, Veo 3, Seedance 2.0, HappyHorse 1.0, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Capabilities: text-to-video, image-to-video, reference-to-video, video editing, lipsync, avatar animation, video upscaling, foley sound. Use for: social media videos, marketing content, explainer videos, product demos, AI avatars. Triggers: video generation, ai video, text to video, image to video, veo, animate image, video from image, ai animation, video generator, generate video, t2v, i2v, ai video maker, create video with ai, runway alternative, pika alternative, sora alternative, kling alternative, seedance, happyhorse

日本語の概要は準備中です。原文の説明を表示しています。

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.

日本語の概要は準備中です。原文の説明を表示しています。

Interactive viewer for microscopy. Displays 2D/3D/4D arrays as Image, Labels, Points, Shapes, Tracks layers; supports annotation, plugin analysis, headless screenshots. Core visualization for Python bioimage workflows. Use ImageJ/FIJI for macro processing; napari for Python-native interactive visualization and DL segmentation review.

日本語の概要は準備中です。原文の説明を表示しています。

Python image processing for microscopy and bioimage analysis. Read/write images, filter (Gaussian, median, LoG), segment (thresholding, watershed, active contours), measure region properties, detect features. SciPy/NumPy ecosystem. Use OpenCV for real-time video; CellPose for DL cell segmentation; napari for visualization.

日本語の概要は準備中です。原文の説明を表示しています。

Download, resize, and remove backgrounds from product images at scale. Use when the user asks to "process product images", batch-download images from the schedule, strip backgrounds, or standardize product photos.

日本語の概要は準備中です。原文の説明を表示しています。

Batch-resize or convert a folder of images for web, social media, slides, or ARCH-size print output while preserving originals. Use for image resizing, format presets, or photo batches; not for product-image background removal.

日本語の概要は準備中です。原文の説明を表示しています。

Provides expert guidance for building GraalVM Native Image executables from Java applications. Use when converting JVM applications to native binaries, optimizing cold start times, reducing memory footprint, configuring native build tools for Maven or Gradle, resolving reflection and resource issues in native builds, or implementing framework-specific native support for Spring Boot, Quarkus, and Micronaut. Triggers include "graalvm native image", "native executable java", "java cold start optimization", "native build tools", "ahead of time compilation java", "reflection config graalvm", "native image build failure".

日本語の概要は準備中です。原文の説明を表示しています。

Use when a user wants step-by-step help making an audio-first image-story, AI narration, slideshow, illustrated story, AI 讲书, 图片联播, 有声故事, or 静态图叙事视频 with Codex or WorkBuddy; not for a standalone script, single image, or ordinary video editing.

日本語の概要は準備中です。原文の説明を表示しています。

像素级 750px 图片转代码与高清切图工作流。当 Codex 需要把当前选中的 UI 图片、截图、App/Web 设计稿、Figma 图片导出稿或设计长图转换为代码，并输出独立透明 PNG 切图资源时使用。适用于严格 1:1 等比例还原、画板宽度精确 750px、高清放大切图、防模糊和背景抠除、必要时用 image2/imagegen 抠透明 PNG、文本可编辑、简单图形原生矢量/代码化，最终代码需要自适应适配，或需要把完成稿导出/导入 Figma 为可编辑图层的任务。

日本語の概要は準備中です。原文の説明を表示しています。

Install and use the official AI Image Generator package, pinned by digest, for paid hosted work on the Beatra service.

日本語の概要は準備中です。原文の説明を表示しています。

REQUIRED for all image generation requests. Generate and edit images using Nano Banana (Gemini CLI). Handles blog featured images, YouTube thumbnails, icons, diagrams, patterns, illustrations, photos, visual assets, graphics, artwork, pictures. Use this skill whenever the user asks to create, generate, make, draw, design, or edit any image or visual content.

日本語の概要は準備中です。原文の説明を表示しています。

Develop art direction for image generation with curated style cards distilled from Open Image Prompts. Use when choosing or comparing visual directions, improving an existing generation prompt, or translating a subject, use case, or supplied image into a compact creative spec. Use img-gen-prompts for real archive examples, exact source prompts, or gallery browsing.

日本語の概要は準備中です。原文の説明を表示しています。

Generate or edit images on the user's own GPU through Guaardvark: single images, instruction edits, background cut-outs, inpaint and outpaint, consistent characters from the Cast Library, and batch runs of many prompts. Use when the user asks to create, draw, render, visualize, edit, or batch-generate images locally.

日本語の概要は準備中です。原文の説明を表示しています。

Generate diagrams, flowcharts, and conceptual illustrations using OpenAI gpt-image-2 (default) or gpt-image-1. Use for: algorithm/code flow diagrams, system architecture sketches, conceptual illustrations, and any figure that does NOT represent actual code execution output (data plots, model results, etc. must still be generated by running Python code). Requires OPENAI_API_KEY and OpenAI organization verification when used from Claude Code / API path. OpenAI Codex subscribers can use built-in $imagegen without an API key.

日本語の概要は準備中です。原文の説明を表示しています。

Generate Guizang-style social card image sets, Live Photo motion cards, material-first Live Photo puzzle layouts, triple Live Photo collages, long-video-to-Live-Photo treatments, and WeChat official account cover pairs from articles, scripts, screenshots, product notes, subtitles, photos, or user-supplied videos. Use when the user asks for 小红书图文, Rednote/Xiaohongshu images, social cards, carousel images, 3:4 covers, Live Photo, 实况照片, 单视频实况拼图, 二宫格实况拼图, 三连实况拼图, 四宫格实况拼图, 微信公众号封面, WeChat 21:9 + 1:1 covers, Swiss Style, or magazine-style social images.

日本語の概要は準備中です。原文の説明を表示しています。

Generate Xiaohongshu (XHS / RedNote) cover images using GPT Image 2 / Codex image generation first, with the legacy Gemini CLI as fallback. Triggers for cover generation: "生成封面", "小红书封面", "xhs封面", "制作封面", "帮我做张图", "XHS cover", "RedNote cover". Triggers for cover editing: "修改封面", "改一下封面", "上一张图基础上", "基于这张图调整", "不要重新做", "edit this cover". Triggers for style learning: "学习这个风格", "提取风格", "我想自定义风格", "这张图的风格", "learn this style", "extract style". Always trigger this skill when user mentions 小红书/XHS/RedNote together with 封面/cover/图片, OR when user uploads a reference image and asks about creating a similar style.

日本語の概要は準備中です。原文の説明を表示しています。

Generate Xiaohongshu (XHS / RedNote) cover images using GPT Image 2 / Codex image generation first, with the legacy Gemini CLI as fallback. Triggers for cover generation: "生成封面", "小红书封面", "xhs封面", "制作封面", "帮我做张图", "XHS cover", "RedNote cover". Triggers for cover editing: "修改封面", "改一下封面", "上一张图基础上", "基于这张图调整", "不要重新做", "edit this cover". Triggers for style learning: "学习这个风格", "提取风格", "我想自定义风格", "这张图的风格", "learn this style", "extract style". Always trigger this skill when user mentions 小红书/XHS/RedNote together with 封面/cover/图片, OR when user uploads a reference image and asks about creating a similar style.

日本語の概要は準備中です。原文の説明を表示しています。