「image generation」の検索結果

Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.

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 this skill when planning, redesigning, or reviewing Xiaohongshu carousel visuals, covers, 3:4 image posts, page-by-page visual direction, image-generation prompts, style selection, layout critique, or XHS captions. It acts as a senior visual director for 小红书图文, not a generic copywriting assistant.

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。

Luma Dream Machine video generation: text-to-video and image-to-video, status polling, cancel, image upload. Trigger phrases: luma, dream machine, luma video, ray video.

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。

Ideogram text-to-image generation with the strongest text rendering in the catalog: generate, edit, remix, upscale, describe, balance. Trigger phrases: ideogram, text in image, thumbnail with words, ideogram generate, magic fill.

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。

Explore UI and visual design with image generation, then iterate the real implementation against the user-selected concept. Use when brainstorming visual directions, offering mockup variants, or implementing an approved generated design; do not stop at the mockups or the first code approximation.

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。

Render a 'brand identity reveal' video from a config — a single poster frame in a real, softly-lit space (real wall, soft-focus plant in the corner, dappled leaf shadow, illuminated poster) whose artwork HARD-CUTS through ~10 on-brand poster mockups (hero product, IG post, hanging banners, sticker sheet, logo lockup, poster, two lifestyle stills, packaging, big icon) then holds on a brand end card. The environment plate is one create-image-fal generation; the mockups are real-DOM HTML frame-stepped via Playwright, perspective-composited into the detected frame quad with the plate's real leaf-shadow multiplied back onto each poster (reads as behind glass), sequenced by FFmpeg. Deterministic assembly, FREE (the plate comes from create-image-fal, the bed from create-music-elevenlabs), music bed only and approved brand copy only. Use for the brand-identity-reveal format.

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。

Public entry point for native device capabilities and native controls — camera, image picker, barcode/QR scanner, document picker, file picker, secure storage, file system, sharing, haptic feedback, PDF generation/viewing, pen/signature capture, background GPS/geolocation tracking, or supported local file workflows — in a Power Apps mobile app. Also owns routing to internal camera/PDF/pen/geolocation implementation helpers and the guidance boundary between native wrappers and Dataverse File/Image host controls.

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 generating navigable 3D worlds or Gaussian splat scenes on Scenario via MCP: text-to-world, image-to-world, a 360 panorama or skybox turned into a walkable splat, multi-view photos or a video walkthrough reconstructed as a splat, or one object photo to splat. Keywords: World Labs Marble 1.1, 1.1 Plus, 1.0 Draft, Hunyuan World, HY World, image-to-skybox, skybox-to-splat, multiview-to-splat, TripoSplat, gaussian splatting, 3DGS, spz, world generation, explorable scene, VR.

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 editing an existing image on Scenario through MCP with a tool model, not a new generation: upscale or enhance to 2x, 4K, 8K, super resolution, 3D LUT color grade, color correction, posterize, solarize, vignette, film grain, blur, sharpen, glow, chromatic aberration, oilify, cubism, crystallize, dodge and burn, tint, desaturate, expand or uncrop, reframe an aspect ratio, resize to exact pixels, slice tiles, contact sheet, split into layers, remove a background or watermark, vectorize.

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 scientific illustrations and diagrams using AI image generation

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。

Design, evaluate, implement, or review image and video generation connectors for Timeline Studio. Use when adding a provider plugin, extracting the generation plugin host or registry, or checking a connector against Timeline Studio's authentication, output, localization, and My assets contract. Do not use for ordinary video editing or Codex plugin packaging.

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。

Seedance 2.5 prompt director — the omni-reference dialect. Routes the four generation modes (t2v / omni_reference / video_edit / video_extension), writes explicit @Image/@Video/@Audio reference roles with exclusions, stages 30-second videos into end-state beats, and covers video editing, forward/backward extension, first-last-frame and multi-keyframe control, storyboard grids, blockout rendering, and seamless transitions. Use whenever the user asks for a Seedance 2.5 prompt, mentions Seedance 2.5 / Dreamina / Jimeng, wants a clip longer than 15s on Seedance, wants to EDIT or EXTEND an existing video rather than generate a new one, or supplies more than a handful of image/video/audio references. For Seedance 2.0 (4K, `mode=fast`, or a genre hint) use higgsfield-seedance instead.

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。

Creates and manages reusable character profiles (Soul IDs) for consistent facial and stylistic identity across multiple image and video generations. Provides identity-vs-motion prompt separation, character sheet creation workflows, micro-expression direction, and Soul Cast AI actor configuration. Use when the user wants to maintain character consistency across multiple generations, asks about Soul ID, creating reusable characters, or generating consistent people across different scenes and shots.

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 the user mentions Higgsfield Canvas, a node-based or node graph workspace, an infinite board/canvas, chaining generations into a pipeline, or wants to wire prompts → images → videos across models on one surface. Covers what Canvas is, the node categories, the seven models that run inside Canvas, the named canvas patterns (Simple Seedance, Extend Video, Image Edit, StoryBoard With Elements, Long Video fan-out), the build-free / generate-paid cost model, reusable templates, assets-as-nodes, and Shared Canvas live collaboration. Also trigger on 'Higgsfield ComfyUI alternative', 'node workflow', or 'connect nodes to build a scene/campaign'.

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 Codex to directly operate PowerPoint and reconstruct an entire reference image as editable PowerPoint objects while preserving its full layout, labels, connectors, and visual relationships. Do not use for paper-to-deck generation or VBA-only output.

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。

Create character design documentation and character design sheet images for video, storyboard, advertising, animation, or AI video-generation workflows. Use this skill whenever the user asks to design a character, extract a character from a reference image, make a character sheet, create a turnaround sheet, keep a person consistent across scenes, or generate character assets for a video project. This skill first writes a confirmable {character-name}.md design spec, waits for user approval or revision, and only then generates {character-name}.png.

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 image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.

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。

Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib

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。

Turn an object or character reference image into a quality-gated, animation-ready procedural Three.js model built in code. Use for image-to-3D reconstruction, detail-accurate object rebuilds, stylized/likeness-maximized human characters, sculpt specs, and staged code generation.

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 and edit images, create video, audio, 3D assets or material maps through fal.ai MCP or the Python queue client. Use for fal model discovery, reference uploads, generation, recovery and local delivery.

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。

Run registered ComfyUI workflows through the fast comfyui-skill CLI, and use the official local Comfy MCP for live template, node, model, validation, and orchestration capabilities. **Use this Skill when:** (1) The user requests to "generate an image", "draw a picture", or "execute a ComfyUI workflow". (2) The user has specific stylistic, character, or scene requirements for image generation. (3) The user asks you to import, register, sync, or configure saved ComfyUI workflows for later reuse.

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。

把一句话需求转成可复现、可验收视频工程的乔木智能剪辑导演。Use when the user asks to create, plan, edit, remix, explain, narrate, subtitle, animate, composite, or render a video—including one-line requests such as “制作一个科普视频：介绍 LLM 中的 RL”. Builds English-learning movie mixes, person profiles, explainers, code-drawn motion graphics (UI morph loops, showreels, kinetic-type promos, line-art/pixel/Three.js animation, lyric MVs), product launch videos, cinematic shorts, social clips, course/PPT videos, AI image/video/TTS/music-assisted stories, stock-footage stories, or multi-source montage. Routes across 33台词, ClipSeek/open media, local files, ListenHub, image generation, HTML/SVG/Canvas motion graphics with beat-grid storyboards and determinism probes, Manim, ffmpeg-full, captions, sound design, frame-0 video covers with YouTube thumbnails, and release checks.

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。

Routes DreamOmni2 image generation, image editing, and Gradio demo workflows.

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。

Art-direct complete illustrated websites and write project-specific image-generation prompts. Use when the user requests Illustrated Gallery, a gallery-inspired visual style, or $illustrated-gallery. Covers visual direction, original artwork, and page-wide composition; not a fixed website clone, standalone image task, or generic dashboard skill.

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。