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Use this skill to classify tabular data end-to-end in MATLAB — load a dataset, prepare and clean it, select promising classifiers, train them, and compare accuracies with cross-validation, holdout, or hyperparameter optimization plus statistical tests. TRIGGER when: user asks to classify tabular data, pick classifiers for a dataset, compare classifier accuracy, run cross-validation or a holdout evaluation, or find the best model with statistical uncertainty. DO NOT TRIGGER when: user has non-tabular inputs (images, sequences, time series), wants a regression model, is training a specific neural network architecture (use matlab-train-network), or wants cost-sensitive learning or an arbitrary class-prior vector (this skill only supports the built-in uniform-prior toggle for imbalanced data).

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。

Programmatically author RoadRunner scenarios from MATLAB using roadrunnerAPI. Use when adding actors, creating routes, building scenario logic (phases, conditions, actions), placing vehicles/pedestrians, defining cut-in/crossing/ follow scenarios, or any programmatic scenario creation in RoadRunner. Triggers on: roadrunnerAPI, scenario authoring, add actor, create route, phase logic, cut-in scenario, pedestrian crossing, scenario from MATLAB.

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。

Exchange data between Excel and MATLAB using Spreadsheet Link VBA macros and worksheet functions. Use when writing Excel VBA macros that call MLPutMatrix, MLGetMatrix, MLPutVar, MLGetVar, MLPutRanges, MLEvalString, MLGetFigure, or MatlabRequest.

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 and harden your SaaS tool stack — enforce SSO, review OAuth grants, manage shadow IT, and secure admin accounts across Slack, GitHub, Google Workspace, and AWS. Use when tightening security across company SaaS tools.

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。

Upsell and cross-sell strategy — product recommendations, cart upsells, post-purchase offers, bundles

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。

Cross-border e-commerce expansion advisor. Scores target markets on 8 weighted dimensions (market size, ecommerce penetration, competition, regulatory complexity, logistics infrastructure, payment ecosystem, cultural distance, IP protection), compares 5 fulfillment models with cost and transit data, provides country-by-country tax/duty compliance guides (EU VAT/IOSS, UK VAT, US sales tax, CA GST, AU GST, JP consumption tax), maps local payment preferences by market, and builds a phased expansion roadmap. No API key required.

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。

Cross-platform keyword research for e-commerce. Discover high-converting keywords across Amazon, Shopify, Etsy, Google Shopping, TikTok Shop, and Walmart. Analyzes search volume signals, competition indicators, commercial intent, and long-tail opportunities.

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。

Cross-platform ecommerce competitor analysis and strategic intelligence. Multi-channel presence evaluation, strategy assessment, positioning analysis, and competitive benchmarking. Use when the user asks about competitor analysis, competitive research, market analysis, or competitive intelligence across platforms.

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 images for web development — resize, crop, trim whitespace, convert formats (PNG/WebP/JPG), optimise file size, generate thumbnails, create OG card images. Uses Pillow (Python) — no ImageMagick needed. Trigger with 'resize image', 'convert to webp', 'trim logo', 'optimise images', 'make thumbnail', 'create OG image', 'crop whitespace', 'process image', or 'image too large'.

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。

Modern animation library for React and JavaScript. Create smooth, production-ready animations with motion components, variants, gestures (hover/tap/drag), layout animations, AnimatePresence exit animations, spring physics, and scroll-based effects. Use when building interactive UI components, micro-interactions, page transitions, or complex animation sequences.

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。

Modern web design trends, principles, and implementation patterns for 2024-2025. Use this skill when designing websites, creating interactive experiences, implementing design systems, ensuring accessibility, or building performance-first interfaces. Triggers on tasks involving modern design trends, micro-interactions, scrollytelling, bold minimalism, cursor UX, glassmorphism, accessibility compliance, performance optimization, or design system architecture. References animation skills (GSAP, Framer Motion, React Spring), 3D skills (Three.js, R3F, Babylon.js), and component libraries for implementation guidance.

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。

Trace relationships between semantic models and downstream reports across Fabric workspaces. Automatically invoke when the user asks to "find downstream reports", "show report lineage", "impact analysis", "what depends on this dataset", "cross-workspace lineage", "which reports are connected", "get model dependencies", or mentions model-to-report dependency tracing.

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 and build complete web experiences from scratch — award-level product and marketing pages, cinematic scroll-directed sites where the page is directed like a film, and multi-screen products (app, dashboard, admin, settings, onboarding, docs site) built as one design system with every component, state and route in one style. Use whenever the user wants to create or redesign a landing page, website, hero section, portfolio, promo or product page; wants scroll animations, storytelling pages, or a site that feels like a movie; or says "make it beautiful", "make it wow", "cinematic", or "design system" — even if they name no technique. Generates its own assets via local CLIs (images, video frames, depth maps, 3D), and gates every ship with an executable anti-slop linter and a screenshot verification loop. Not for polishing a UI someone else built, and not for backend-only work.

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。

When the user wants to plan content marketing across channels, define content types and formats, or create a content repurposing strategy. Also use when the user mentions "content marketing strategy," "content types," "content formats," "content repurposing," "content calendar," "content mix," "owned content," "content distribution," "content funnel," or "content planning across channels." For SEO calendar, use content-strategy.

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 responsive, mobile-first layouts using fluid containers, flexible units, media queries, and touch-friendly design that works across all screen sizes. Use this skill when creating or modifying UI layouts, responsive grids, breakpoint styles, mobile navigation, or any interface that needs to adapt to different screen sizes. Apply when working with responsive CSS, media queries, viewport settings, flexbox/grid layouts, mobile-first styling, breakpoint definitions (mobile, tablet, desktop), touch target sizing, relative units (rem, em, %), image optimization for different screens, or testing layouts across multiple devices. Use for any task involving multi-device support, responsive design patterns, or adaptive layouts.

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。

Compare several Japanese NLP libraries, models, or datasets for a keyword (a specific tool name, or a function/task like '形態素解析') across a handful of criteria chosen for that comparison, rendered as a ○/△/✕ table. Use when the user wants a side-by-side comparison of multiple Japanese NLP tools/libraries/datasets, not just the single best one. Trigger phrases include 'X と Y と Z を比較して', '形態素解析ライブラリを比較', 'MeCab と Sudachi どっちがいい', 'どのツールを使うべき', 'compare japanese tokenizers', 'mecab vs sudachi vs janome', 'which embedding model should I use', '日本語NERライブラリの比較表', 'pros and cons of japanese OCR tools'. For a single ranked list use search; for alternatives to one specific tool (or contribution candidates) without a multi-axis table, use discover.

Given a Japanese NLP GitHub repo/model/dataset (URL / owner/repo / tool name) OR a topic, find what's already in awesome-japanese-nlp-resources and discover related resources NOT yet listed (contribution candidates). Mines the bundled dataset, then expands via web research across GitHub and Hugging Face. Use when the user names a SPECIFIC repository, model, or tool and wants alternatives/equivalents, OR wants to discover Japanese NLP resources for a topic that are NOT yet in the list, OR wants to prepare a contribution. Trigger phrases include 'mecabに似たツール', 'fugashiの代替', 'alternatives to fugashi', 'repos like manga-ocr', 'what else is like sudachi', 'リストに無い新しい日本語NLP', 'awesome-japanese-nlpに追加できそうな', '最近公開された日本語NLPツール', 'find unlisted Japanese NLP repos', 'new Japanese models on Hugging Face', 'contribute a new resource'. For a simple lookup of what already exists, use the search skill instead.

Builds, tests, diagnoses, upgrades, deploys and verifies Power Apps component framework (PCF) code components for model-driven apps and Power Pages — field and dataset controls, standard and virtual (React) — from Microsoft-maintained templates and recipes pinned to a tested version matrix. Runs quality gates (manifest and host lint, source checks, lint, unit tests, production build), deploys with pac pcf push, verifies registration and form bindings, and guides Power Pages enablement, with guided setup for canvas apps. Use when the user wants to build, fix, upgrade, deploy or check a PCF control or code component, or asks why one fails to build, import, update or render. For a whole page use /model-apps:genpage; for a whole app use /model-apps:app-builder.

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 analyzing interacting object types, object-centric processes, leading-object executions or cross-object delay.

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 broad Process Mining business question, observed pattern or competing explanation needs investigation across analytical perspectives.

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 or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters, packaging, magazine covers, ads, key art, or instruction-based editing such as text swaps, recoloring, object removal or replacement, background swaps, lighting changes, and full restyles. Keywords: MAI Image 2.5, 2.5 Pro, 2.5 Edit, 2.5 Pro Edit, Microsoft, txt2img, img2img, typography, text rendering, image edit.

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。

Internal implementation skill invoked by /add-native for pen, signature, ink, drawing, and handwriting capture workflows using @microsoft/power-apps-native-pen-input.

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。

Internal implementation skill invoked by /add-native for native PDF control workflows. Handles HTTPS and file URI PDF viewing with @microsoft/power-apps-native-pdf-viewer 0.2.9+.

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。

Internal implementation skill invoked by /add-native for native background GPS tracking with durable storage and Dataverse sync using @microsoft/power-apps-native-bglocation.

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。