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概要と使いどころ
Generate NowStack Mobile onboarding backgrounds, splash, and brand artwork with AI image generation. Use for "generate onboarding images", "make brand art", "redo the splash". REQUIRES an image-gen tool (Codex/gpt-image); other agents follow the fallback. For the app icon (iOS/Android launcher icon) use ns-icon 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。
Generate visual asset briefs, ad copy variants, AI image prompts, video scripts, and storyboards. Full creative production system with 5 specialized modes: product photos, product video, social graphics, talking heads, and ad creative. Make sure to use this skill whenever the user mentions any visual or creative marketing need — ad creative, image prompts, video scripts, thumbnails, banners, social graphics, product photography, storyboards, or marketing visuals of any kind. Even if they just say 'I need images for my campaign' or 'make something visual', this is the skill. Owns thumbnail and banner briefs plus the creative direction. Includes platform-specific dimensions, AI anti-slop techniques, and Remotion composition templates. For rendering the actual image file, see /image-gen; for AI-generated marketing/brand videos, see /higgsfield-generate; for stitching slides into an MP4, see /video-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。
图文创作专家（珀西 · Percy）。擅长文生图（HY-Image-V3.0 / HY-Image-Lite / ImageGen）、图生图/图片编辑（ImageEdit）、7种场景创作策略、批量生成、平台尺寸适配。 触发词："画一张赛博朋克风城市"、"生成一组小红书种草图"、"把这张图改成水彩风"、"批量生成5张产品图"。
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。
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration) and ImageMagick (image manipulation, format conversion, batch processing, effects, composition). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.
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。
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
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。
Gaia Skill Tree image-generation and deterministic export harness for Ascension Overdrive v3. Use when generating, iterating, refining, cropping, color-grading, making transparent cutouts, compressing, upscaling, or validating production image assets. Always use image gen 2 / gpt-image-2 and never nano-banana.
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。
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.
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。
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.
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。
Build image generation pipelines with Stable Diffusion, FLUX, ControlNet, LoRA, and ComfyUI workflows. Activate on: image generation pipeline, ComfyUI workflow, ControlNet, LoRA training, diffusion model. NOT for: video generation (ai-video-production-master), image classification (computer-vision-pipeline).
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。
Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration) and ImageMagick (image manipulation, format conversion, batch processing, effects, composition). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.
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 a reference image or mockup into a working local frontend that matches it closely. Inspects the image, extracts the design system (layout, type, spacing, color, components), implements it, then screenshot-compares and iterates to close the gap. Use when the user says "image to code", "build this mockup", "code this screenshot", "make this design real", or provides a UI image to implement. Part of the Product Design set. Uses a browser tool for screenshot verification.
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 whenever the user asks to generate, edit, inpaint, restyle, or create bitmap images through OpenAI's Responses API image_generation tool from Codex. This skill calls the Responses API, saves generated base64 image results to files, uses no npm or pip dependencies, works on Linux/macOS/Windows with either Node.js 18+ or Python 3, and reuses Codex's configured API base URL, model, and key instead of asking the user for credentials.
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。
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
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。
xAI Grok Imagine API integration for image generation, text-to-video, image-to-video, and editing via natural language. Use when you need to generate images or videos from text prompts, edit existing images, animate static images into videos, or edit existing videos with natural language instructions. Supports conversational generation across messaging platforms with async polling, progress updates, and automatic 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。
Use when the user asks to generate or edit images via the OpenAI Image API (for example: generate image, edit/inpaint/mask, background removal or replacement, transparent background, product shots, concept art, covers, or batch variants); run the bundled CLI (`scripts/image_gen.py`) and require `OPENAI_API_KEY` for live calls.
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。
Assistente de Linguagem Grande e Visão. Habilita ajuste de instrução visual e conversas baseadas em imagem. Combina encoder de visão CLIP com modelos de linguagem Vicuna/LLaMA. Suporta chat multi-turno com imagem, resposta a perguntas visuais e seguimento de instruções. Use para chatbots visão-linguagem ou tarefas de compreensão de imagem. Melhor para análise conversacional de imagem.
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。
Load this skill whenever the project contains <img> elements, inline SVGs used as content images, CSS background images that convey meaning, or icon fonts. Under no circumstances omit alt text on meaningful images. Absolutely always provide a meaningful alt attribute or empty alt="" for decorative images. Apply WCAG 2.2 SC 1.1.1 — every non-text element requires a text alternative.
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。
Remove Gemini AI watermarks from images using GeminiWatermarkTool (GWT). Use this skill whenever the user mentions: Gemini watermark, 浮水印, AI image cleanup, removing logos from Gemini-generated images, Google ImageFX cleanup, batch processing AI-generated photos, or anything about a semi-transparent logo in the bottom-right corner of an image — even if they don't say "GeminiWatermarkTool" explicitly. Also trigger for follow-up requests like "the corner still looks dirty" or "there's still residual artifacts" after a previous removal attempt.
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。
Generates infographic image card series with 12 visual styles, 8 layouts, and 3 color palettes. Breaks content into 1-10 cartoon-style image cards optimized for social media engagement. Use when user mentions "小红书图片", "小红书种草", "小绿书", "微信图文", "微信贴图", "image cards", "图片卡片", baoyu-xhs-images, or wants social media infographic series.
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。
Default material, information-density hierarchy, clean-rendering, negative-prompt hygiene, and evidence-preserving photo-repair layer for IM2 / GPT Image 2 / gpt-image-2 / image_gen. Use for clean generation/redraws, artifact cleanup, focal-detail control, atmospheric depth, physically coherent light paths, air scattering, volumetric light, light ratio, material realism, architecture/terrain/hard-surface scene mass and structural grounding, and 企业/公司活动/门店/团队合影/商品/餐饮/证件文档照片修复. Preserve identity, headcount, placement, product facts, text, logo, QR, date, price, and scene evidence; prefer residual blur over invented restoration detail.
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。
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.
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。
Nano Banana 2（Google Gemini gemini-3.1-flash-image-preview）を使って画像を生成するスキル。「画像を生成して」「〇〇のイラストを作って」「Nano Bananaで画像を作って」「グラレコ風の画像を生成して」などのリクエストで使用する。プロンプトを受け取りpythonスクリプトを実行、タイムスタンプ付きPNGを images/generated/ に出力する。
Generate a polished frontend reference screenshot through a configurable GPT-image-2-compatible generations endpoint, save and show versioned previews inside the project, revise selected previews through a configurable /images/edits endpoint, and reproduce only the user-approved design as functional frontend code with high visual fidelity. Use when Codex is asked to design, build, restyle, or recreate a web page, application screen, dashboard, landing page, or UI component through an image-first workflow, design approval loop, screenshot-driven implementation, pixel matching, or a 1:1 frontend recreation.
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。
Securing container registry images by implementing vulnerability scanning with Trivy and Grype, enforcing image signing with Cosign and Sigstore, configuring registry access controls, and building CI/CD pipelines that prevent Dağıt:ing unscanned or unsigned 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。