1.7万 件 ・ 関連度順
概要と使いどころ
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。
Framework PyTorch de alto nível com classe Trainer, treinamento distribuído automático (DDP/FSDP/DeepSpeed), sistema de callbacks e boilerplate mínimo. Escala de laptop para supercomputador com o mesmo código. Use quando quiser loops de treinamento limpos com boas práticas integradas.
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CLI do Datadog para buscar logs, consultar métricas, rastrear requisições e gerenciar dashboards. Use isso ao depurar problemas em produção ou trabalhar com observabilidade do Datadog.
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Avalia LLMs em 100+ benchmarks de 18+ harnesses (MMLU, HumanEval, GSM8K, segurança, VLM) com execução multi-backend. Use quando precisar de avaliação escalável em Docker local, HPC Slurm ou plataformas cloud. Plataforma enterprise-grade da NVIDIA com arquitetura container-first para benchmarking reproduzível.
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Use this Canvas-owned clean-room skill for creating, reading, editing, reviewing, redlining, commenting, or repairing Word `.docx` documents. Trigger for Word documents, DOCX files, memos, reports, letters, templates, tracked changes, comments, table of contents, headers, footers, page numbers, and Google Docs-targeted documents that should be authored as DOCX first.
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。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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Create and edit editable Excalidraw diagrams in Canvas Notebook through the Scene-Service tools. Use for diagrams, flows, sketches, architecture maps, visual explanations, or requested .excalidraw documents.
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 you are planning, executing, or reviewing manual accessibility testing. Manual testing with real assistive technologies is essential — automated tools catch only ~30–40 % of WCAG issues. Absolutely always include keyboard-only testing and at least one screen reader test before marking a feature accessible. Under no circumstances skip forced colors mode testing for UI components.
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 before implementing a fix for a barrier that may originate in a shared component, design system, renderer, or external dependency rather than this project's own code. Decide whether the responsible fix is local, an existing installed capability, or an upstream contribution before writing a workaround. Absolutely always record any temporary local divergence with an owner and removal condition. Under no circumstances open, comment on, or submit anything in an external project without explicit human approval.
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 for every project containing interactive UI elements — buttons, links, modals, dropdowns, sliders, tabs, carousels, or any custom widget. Under no circumstances create an interactive component that cannot be fully operated by keyboard alone. Absolutely always ensure visible focus indicators, logical tab order, and no keyboard traps. Apply these rules to every interactive element without exception.
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 when writing, reviewing, or interpreting behavioral accessibility automation — tests that manipulate a rendered page (resizing the viewport, pressing real keys, capturing and comparing screenshots) rather than only inspecting static markup or a single computed accessibility tree. Covers Reflow risk (SC 1.4.10) and Focus Visible risk (SC 2.4.7) checks. Absolutely always report indicator results separately from confirmed failures. Under no circumstances treat a clean behavioral scan as WCAG conformance, or collapse `cantTell`/test-error/indicator outcomes into a single pass/fail signal.
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 uses Mermaid diagrams — flowcharts, sequence diagrams, class diagrams, Gantt charts, or any Mermaid-rendered visualization. Under no circumstances render a Mermaid diagram without an accessible title, description, and text-based alternative. Absolutely always add accTitle: and accDescr: (no %% prefix — that is the comment syntax and will be silently ignored) to every diagram.
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 SVG graphics — inline SVGs, external SVG files, SVG icons, SVG illustrations, or SVG-based data visualizations. Under no circumstances use SVG without proper accessible titles, descriptions, and ARIA roles where required. Absolutely always add <title> and <desc> to meaningful SVGs and set role="img" with aria-labelledby pointing to those elements. Also apply this skill whenever the project accepts untrusted or user-uploaded SVG content, which requires sanitization before rendering.
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 navigation components — primary navigation menus, dropdown menus, mega menus, breadcrumbs, pagination, mobile hamburger menus, or in-page jump navigation. Under no circumstances create navigation without proper landmark roles, keyboard support, and accessible labels. Absolutely always wrap navigation in <nav> with a unique aria-label.
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 charts, graphs, data visualizations, infographics, or any visual representation of data (bar charts, line charts, pie charts, scatter plots, dashboards). Under no circumstances render a chart without a text alternative, data table, or summary. Prioritize conveying the same information through non-visual means.
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 tooltip components, hover- triggered informational popups, title attribute tooltips, or any content revealed on hover or focus. Under no circumstances create tooltips that are only triggered by hover without keyboard equivalent access. Absolutely always ensure tooltips are dismissible, persistent enough to read, and not the sole source of essential information.
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 has personalization features, user preference controls, theme selectors, font size adjusters, motion toggles, contrast settings, or any user-configurable accessibility accommodations. Under no circumstances override or ignore user OS-level accessibility preferences without explicit user consent. Absolutely always persist user preferences, apply them immediately, and respect prefers-reduced-motion, prefers-contrast, and similar media queries.
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 when building any web feature, reviewing architecture decisions, or evaluating JavaScript dependencies. Under no circumstances build features that break completely when JavaScript is unavailable or fails. Absolutely always start with semantic HTML, layer CSS enhancements, and add JavaScript as the final, optional layer. Prioritize resilience and universal access over cutting-edge features.
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 you are filing, reviewing, or generating accessibility bug reports — whether from automated tool output, manual testing, user reports, or testing with disabled people. The purpose of this skill is to make accessibility findings easier to report accurately, connect them to real people and tasks, and let developers reproduce, understand, and fix them without unnecessary back-and-forth. Absolutely always describe the barrier and its task impact before citing a WCAG criterion. Under no circumstances guess a disability diagnosis, treat automated tool output as a conformance conclusion, or expose secrets/personal data in a report.
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 deliverable is authored or edited prose whose wording matters (docs, READMEs, release notes, public copy) or when the user asks to tighten, de-AI, or review writing. Not for chat answers, code review, or explanations of current 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。
Use when the user wants to improve architecture, consolidate tightly-coupled modules, or make a codebase more testable.
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 turning approved plans, specs, PRDs, or Epics into trackable GitHub Issues.
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Turns an ICP or research goal into a plan for finding and scraping suitable directories. Use when the user has a target audience but is unsure where to find them, and wants source categories, queries, and an extraction workflow.
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。