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概要と使いどころ
Use when an idea becomes a Pixar-style animation prompt — character sheet, scene, image, video; emotional beat, want, obstacle. Triggers 'Pixar prompt', 'animated scene'. Live-action → video-director.
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。
Wire up DevContainers / GitHub Codespaces — `devcontainer.json`, container images, secrets, VS Code features, port forwarding. NOT for tuning Copilot itself (use `copilot-config`).
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 brand assets — banners, social cards, CIP elements — with brand-token injection + provider routing. Use when generating a banner / social image / branded asset.
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。
Define a brand identity constraint set from a confirmed strategy — colour story, type story, logo direction, imagery direction. Defines the tokens that token emission and asset generation consume.
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。
Crie slides de apresentação Marp profissionais com 7 temas lindos (padrão, minimalista, colorido, escuro, gradiente, tech, negócios). Use quando usuários solicitarem criação de slides, apresentações ou documentos Marp. Suporta temas personalizados, layouts de imagem e requisitos "deixe bonito" com melhorias de qualidade automática.
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。
Framework para embeddings de última geração em sentenças, textos e imagens. Oferece 5000+ modelos pré-treinados para similaridade semântica, clustering e retrieval. Suporta modelos multilíngues, específicos de domínio e multimodais. Use para gerar embeddings para RAG, busca semântica ou tarefas de similaridade. Melhor para geração de embeddings em produção.
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。
Curação de dados acelerada por GPU para treinamento de LLM. Suporta texto/imagem/vídeo/áudio. Recursos incluem deduplicação fuzzy (16× mais rápida), filtragem de qualidade (30+ heurísticas), deduplicação semântica, redação de PII, detecção NSFW. Escala em GPUs com RAPIDS. Use para preparar datasets de treinamento de alta qualidade, limpar dados web ou deduplicar grandes corpora.
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。
Processamento escalável de dados para workloads de ML. Execução em streaming em CPU/GPU, suporta Parquet/CSV/JSON/imagens. Integra-se com Ray Train, PyTorch, TensorFlow. Escala de uma única máquina para centenas de nós. Use para inferência em lote, pré-processamento de dados, carregamento de dados multi-modal ou pipelines distribuídos de ETL.
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, edit, review, preview, and export polished Marp Markdown slide decks in Canvas Notebook. Use when the user wants Markdown-native presentations, `.marp.md` or `.slides.md` files, version-controlled decks, Marp PDF/image/PPTX/HTML export, speaker notes, dashboard-style slides, data cards, or better looking decks that should remain close to plain text.
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 Canvas-owned clean-room skill for PDF work where layout, extraction, generation, forms, page operations, or visual verification matter. Trigger for reading PDFs beyond plain text, creating PDFs, merging, splitting, rotating, watermarking, extracting tables or images, filling forms, OCR handoff, and final PDF QA.
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。
[Document Processing] Use when you need to convert Microsoft Word ( DOCX) files to Markdown with GFM support (tables, images, code blocks).
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。
国潮/国风视觉生成助手。当用户要"国潮风""中国风插画""国漫风格""水墨风""新中式设计""古风头像""国风配图""汉服插画""传统文化海报"时使用。内置 12 种中国美学画风配方，输出可直接复制到 Midjourney/即梦/可灵/Nano Banana 的提示词。
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。
Project-level WeChat article drafting workflow for turning source materials, repo intakes, product notes, screenshots, or existing markdown into a publishable Chinese公众号 draft. Use for writing, rewriting, evidence-gating, title options, platform adaptation, and image planning before optional publishing.
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 engineering principles for making interfaces feel polished. Use when building UI components, reviewing frontend code, implementing animations, hover states, shadows, borders, typography, micro-interactions, enter/exit animations, or any visual detail work. Triggers on UI polish, design details, "make it feel better", "feels off", stagger animations, border radius, optical alignment, font smoothing, tabular numbers, image outlines, box shadows.
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 managing Alibaba Cloud Simple Application Server (SWAS OpenAPI 2020-06-01) resources end-to-end, including querying instances, starting/stopping/rebooting, executing commands (cloud assistant), managing disks/snapshots/images, firewall rules/templates, key pairs, tags, monitoring, and lightweight database operations.
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) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', 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 or .dotx 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。
Design engineering principles for making interfaces feel polished. Use when building UI components, reviewing frontend code, implementing animations, hover states, shadows, borders, typography, icons, micro-interactions, enter/exit animations, or any visual detail work. Supports quick and full review modes. Triggers on UI polish, design details, "make it feel better", "feels off", stagger animations, border radius, optical alignment, font smoothing, tabular numbers, image outlines, box shadows, icons, icon stroke weight, icon states, motion restraint.
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。
Prepare copy-ready Xiaohongshu/Rednote publish materials from a local XHS article package. Use when the user asks for "输出发布格式", "小红书发布格式", "准备发布", "二次编辑发布格式", or needs title/body/tags/output image directory/checks without browser automation or clicking publish.
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。
Validate Commodore 1540/1541/1541C/1541-II compatible disk-drive behavior in EMULATORS, including IEC serial bus protocol, device numbers, KERNAL traps, CBM DOS commands/status, D64 image parsing, BAM/directory/file chains, PETSCII filenames, 6502 drive CPU/ROM/RAM expectations, 6522 VIA wiring, GCR/track/sector geometry, motor/head timing, and compatibility boundaries for 1541-like devices. Use when Codex reviews or edits C64, VIC-20, C264, COMMODORE disk, serial I/O, D64, CBM DOS, IEC, VIA, GCR, or 1541 drive code.
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 auditing UI code for interface-guideline compliance (accessibility, forms, animation, images, performance, UX copy) and/or validating a deployed page against Lighthouse 95+ targets. Produces evidence-based findings (file:line + Lighthouse JSON) and turns confirmed pendencies into Draft SPECs via write-specs. Do NOT use to design/build UI from scratch (use design) or to fix findings inline — fixes go through the SPEC 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。
Use this skill for any website, web application, frontend UI, component, layout, styling, refactor, or review. It enforces a self-contained editorial output standard: image-first composition, oversized typography, visible hairline grids, hard-edged rectangular framing, restrained copy, and 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。
画像の一部を切り出す。全体から注目したい場所だけを取り出して、そこに集中するための道具。
Design original, scalable logos and production-ready asset sets for a specific usage context. Use when Codex needs to create or refine a logo, symbol, wordmark, app icon, repository identity, CLI mark, website brand, social preview, or Codex skill/plugin icon; adapt concepts, formats, dimensions, variants, and delivery checks to the target platform instead of producing a context-free 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。
Use this skill to process one to 99 local exact 2:1 equirectangular panorama images with Realsee Argus, producing depth maps, a merged GLB point cloud, camera poses, optional intrinsics, and a validated local output index. Trigger for Argus panorama reconstruction, Argus ZIP input, or explicit Argus start/status/collect lifecycle requests. Do not trigger for panorama editing or stitching, arbitrary-photo 3D generation, existing GLB inspection, or research-only questions.
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。