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概要と使いどころ
Load FIRST for anything that carries the Kortix look or voice: product or mobile UI, copy of any kind, decks, social, images, email, CLI output, anything with the logo, and reviews of these. Routes you to the exact files. Triggers: choosing a spacing, color, radius, shadow, duration or word that a user or buyer will read.
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 programmatic video with React via Remotion — compositions, sequences, and motion graphics animated with useCurrentFrame() and rendered to MP4. USE WHEN video, animation, motion graphics, video rendering, React video, render video, animate content, make a short, create animations, video overlay, explainer video, animated explainer, content to video, programmatic video. NOT FOR static images, diagrams, or illustrations (use Art), tight-cut filler removal from raw talking-head recordings (that is video editing, not motion graphics), or audio-only podcast cleaning (use AudioEditor).
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。
Read, create, and edit tldraw .tldr canvas files deterministically — sketch hand-drawn-register diagrams (boxes, arrows, sticky notes, frames, text) directly into a canvas file the user opens in any tldraw surface, and read a rough canvas back as structured data to organize it. USE WHEN tldraw, .tldr file, whiteboard, canvas, sketch a diagram, hand-drawn diagram, draw this on a canvas, put this on the whiteboard, structure my canvas, organize my whiteboard, read my canvas, cluster my sticky notes. NOT FOR polished static images, infographics, or mermaid diagrams (use Art), web UI design (use Webdesign), programmatic video (use Remotion).
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。
Renders the current session's output (analysis, research, red team, report, plan) as an extremely well-designed, self-contained HTML artifact via a deterministic renderer — the model distills content into typed JSON, the tool owns all layout/typography/color. USE WHEN /HTML, HTML artifact, render this as HTML, make this an HTML page, artifact of this analysis, designed HTML output. NOT FOR deployed websites or web apps (build the project directly), web UI design systems (use Webdesign), static images or diagrams (use Art), or writing the underlying analysis itself (run the analysis first, then /HTML renders it).
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。
Detects AI-generated writing four ways — a heuristic audit against a catalog of known AI patterns, deterministic statistical signals (n-gram entropy, burstiness, repetition, stylometry — features never verdicts), an empirical Pangram score calibrated against known-human baselines, and a keyless scan for watermark and steganography signatures (invisible characters, homoglyphs, bidi, odd whitespace) in the bytes. USE WHEN detect AI writing, is this AI, AI detection, AI detector, did an AI write this, does this sound like AI, AI writing score, pangram, scan for AI tells, flag AI patterns, AI-isms, statistical AI signals, burstiness, text entropy, is this watermarked, detect watermark, steganography, zero-width chars, hidden characters, invisible unicode, compare drafts for AI-ness. NOT FOR rewriting prose to strip AI patterns (use a voice/authoring skill), plagiarism detection, detecting AI-generated images/video/code, or judging whether writing is any good.
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。
Analyze one supplied URL across on-page, content, technical metadata, schema, images, and performance. Use only for a single-page 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。
Transfer a blog post from Notion to the Wasp blog. Fetches content, downloads and optimizes images, and creates a properly formatted MDX file.
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 matched 3:4, 16:9, and 4:3 short-video cover images from toBeBetterJavaer video scripts or AI/Java technical topics. Use when the user asks for 视频封面, 封面图, 横版和竖版, 小红书/抖音/B站/快手封面, pure-text covers with 白色大字+黄色小字, reference-image-matched covers, or wants a repeatable cover workflow for Markdown scripts under docs/src/ai/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。
Generate and edit images, vector artwork, photos, audio and video; inspect results and deliver finished artifacts.
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。
Automate Docker Hub tasks via Rube MCP (Composio): repositories, images, tags, and container registry management. Always search tools first for current schemas.
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 wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this 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。
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document 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 original images, artwork, product visuals, diagrams, or other raster assets with the desktop's configured image provider. Use whenever the user asks to create or generate an image.
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。
Records a running CARLA simulation to a .log file via start_recorder/stop_recorder for later deterministic replay — capturing actor spawns, transforms, traffic-light states and animations (optionally velocities/controls). Use when the user asks to "record the simulation", "start/stop the recorder", "capture this run", or "save a scenario to replay later". Does NOT capture sensor 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。
State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.
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。
Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.
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。
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
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 custom images, graphics, and visual content 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。
Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.
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。
Audit paid-ad copy, images, video, hooks, concepts, format coverage, platform-native fit, message match, creative fatigue, accessibility, and policy across supported platforms. Use for creative audit, ad creative, creative fatigue, creative diversity, ad copy review, video review, image review, or production priorities.
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。
Upload local assets (images, mockups, extracted HTML, design markdown) to a Stitch project. ALWAYS use this skill when you need to upload visual assets, HTML pages, or design docs to Stitch, particularly when direct MCP tool calls fail or truncate due to base64 token limits.
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 new screens from text prompts or images, edit existing screens with prompts and design system tokens, and generate design variants using Stitch MCP. Includes prompt enhancement pipeline, design mappings, professional UI/UX terminology, design tokens and theme system capabilities.
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。
Extract self-contained static HTML from a built web application or React components by inlining CSS and images. Use this skill whenever you need to capture a specific UI state, share a static version of a page, or prepare assets for Stitch upload, even if the user just asks to 'save the HTML' or 'mock the view'.
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。
OCR text recognition expert. ALWAYS invoke this skill when you need to extract text from images or PDFs — including invoices, receipts, ID cards, bank cards, business licenses, tables, handwritten documents, or any visual text 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。