1.1万 件 ・ 関連度順
概要と使いどころ
Convert PyTorch AT_DISPATCH macros to AT_DISPATCH_V2 format in ATen C++ code. Use when porting AT_DISPATCH_ALL_TYPES_AND*, AT_DISPATCH_FLOATING_TYPES*, or other dispatch macros to the new v2 API. For ATen kernel files, CUDA kernels, and native operator implementations.
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 aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.
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。
Develop, challenge, and document Chisel processor microarchitecture designs before implementation. Use when discussing or writing design documents for processor pipelines, queues, issue logic, rename, ROB, LSU, caches, MSHRs, forwarding, wakeup, replay, flush, privilege, exceptions, or other cycle-accurate hardware mechanisms; when converting design conversations into stable Markdown specifications; or when reviewing a proposed Chisel CPU design for correctness, timing, area, verification cost, and cross-document consistency.
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 multiple angles and shot types of a single product for ecommerce-ready image sets. Produces a coherent set (hero 3/4, front, side, back, detail macro, scale, packaging, in-hand) keeping product identity consistent across shots. Use when the user says "different angles", "product shots", "ecommerce image set", "shot list", "PDP gallery", or needs a multi-view set of one product. Part of the Creative Production set.
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。
Derive an execution roadmap from a project's vision/spec docs by first principles, then diff that fresh derivation against the existing roadmap to prove the task ORDER is correct. Use this whenever the user wants to review, validate, re-derive, or sanity-check an execution roadmap or delivery plan; asks whether the tasks/epics are "in the right order"; suspects a task is scheduled before its prerequisite (a producer-after-consumer / dependency-inversion error like "OpenAPI after the web client that consumes it", OR a cross-cutting inherited default like observability/auth/tenancy scheduled after the feature work that inherits it — a seam-after-consumer error); wants to find missing tasks, circular dependencies, or over-fragmented epics; or wants to compact a plan to raise velocity. Also trigger on "review the roadmap", "re-derive the plan from the spec", "is this the right build order", "check the dependency graph of our epics", "which task should come first". It reads the vision + spec corpus, decomposes actors → use-cases → modules → epics → typed tasks, identifies cross-cutting inherited-default seams, builds a real dependency graph with hard + soft (seam) edges (deterministic helper), breaks cycles, topologically orders, compacts, and emits a derived roadmap PLUS a delta report against the current one — it never blindly overwrites a hand-crafted roadmap.
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。
Expert security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).
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。
当用户与不同文化背景的人合作、反馈被误解、询问如何给日本/中国/荷兰同事反馈、或管理多元文化团队时触发。基于Netflix跨文化反馈适应框架：4A+第5个A（调整适应）。
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。
Enterprise-specific view across CopilotKit + AG-UI. "Enterprise" here = CopilotKit's COMMERCIAL surfaces (Premium / CopilotKit Enterprise / Intelligence Platform / paid tiers), NOT CopilotKit running inside a big company. Tracks the commercial product surfaces (from product-surface-scan — Enterprise Intelligence, Cloud, self-host license, threads/persistence tier, Inspector, premium UI/Angular SDK, analytics, security bundle, Slack/Teams), applies the free-vs-paid classifier to decide if an issue belongs here, surfaces cross-page product contradictions, and tracks enterprise questions/complaints, community-sourced prospects (with a sales owner), and enterprise reporters with prior-week trend. Elevated to the top of the weekly report. Runs standalone ("who's at enterprise this week") or invoked by weekly-report. Triggers on "enterprise report", "enterprise signals", "enterprise status", "who at enterprise this week".
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。
Generic ad-hoc topic search across CopilotKit + AG-UI Discord/GitHub. "Find all reports about <topic> in the last <N> days." Returns a structured chronological list with reporter handles + 1-line summaries + optional enterprise enrichment. Triggers on "find all reports about", "search across both communities", "look for X in last N days".
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。
Expert-level applied electromagnetics covering transmission lines, waveguides, antennas, microwave circuits, EMC, and computational EM methods.
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。
Expert-level embedded systems covering microcontrollers, RTOS, peripheral interfaces, low-power design, bare-metal programming, and embedded Linux.
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。
Run a Codex prompt on a cron schedule or at a specific future time. Codex app Automations is the official, always-on surface for durable recurring schedules — recommend it FIRST; this local skill is a terminal fallback that only fires while its daemon runs. Triggers include "/schedule", "cron", "every Monday 9am", "run this at 3pm", "schedule a codex prompt", "recurring codex task", and one-time future runs ("run once at 3pm", "remind me to check X tomorrow"). For fixed-interval repeats ("every N minutes"), use the separate `loop` skill 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。
Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.
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 designing account-expansion mechanics — upsell vs cross-sell, expansion-trigger signals, NRR cognition. Triggers on 'lift NRR', 'when do we upsell vs cross-sell'.
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。
Comprehensive quality control for U.S. patent application filing documents. Use when the user asks to QC, check, validate, or review patent filing documents before submission to the USPTO. Performs 70+ automated and manual checks across specification, drawings, ADS, declaration, assignment, and power of attorney documents. Detects cross-document inconsistencies, formatting issues, missing required fields, and common errors.
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。
Review a feature and enhance it with purposeful animations, micro-interactions, and motion effects that improve usability and delight. Use when the user mentions adding animation, transitions, micro-interactions, motion design, hover effects, or making the UI feel more alive.
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。
Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.
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。
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task 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。
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task 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。
Build React animations with Motion (Framer Motion) - gestures (drag, hover, tap), scroll effects, spring physics, layout animations, SVG. Bundle: 2.3 KB (mini) to 34 KB (full). Use when: drag-and-drop, scroll animations, modals, carousels, parallax. Troubleshoot: AnimatePresence exit, list performance, Tailwind conflicts, Next.js "use client".
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。
Zotero ローカル API + REST API (Web API v3) 連携スキル。DOI からの文献一括インポート、コレクション管理、アイテム検索・一覧表示を行う。 REST API 経由でコレクション作成・アイテム CRUD・タグ管理・添付ファイルアップロード・グループライブラリ操作も可能。 Use when: (1) DOI リストから Zotero に文献を登録する, (2) Zotero のコレクション一覧・アイテム一覧を取得する, (3) BibTeX/RIS データを Zotero にインポートする, (4) CrossRef API で文献の DOI を検索する, (5) REST API でコレクション作成・アイテム追加・タグ管理を行う, (6) グループライブラリを操作する。 Triggers: "zotero", "文献登録", "DOI インポート", "コレクション", "論文追加", "文献管理"
Use when you need blast-radius analysis, dependency graphs, cross-repo impact, breaking-change diff, or architectural overview of .NET workspaces. Keywords: blast radius, dependency graph, impact analysis, cross-repo, call graph, endpoint map, EF Core lineage, breaking change, daemon, reindex.
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。
Guia completo de desenvolvimento backend para microserviços Node.js/Express/TypeScript. Use ao criar routes, controllers, services, repositories, middleware ou trabalhar com Express APIs, acesso a banco de dados com Prisma, rastreamento de erros com Sentry, validação com Zod, unifiedConfig, injeção de dependências ou padrões assíncronos. Cobre arquitetura em camadas (routes → controllers → services → repositories), padrão BaseController, tratamento de erros, monitoramento de performance, estratégias de testes e migração de padrões legados.
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。
Quando o usuário quer otimizar onboarding pós-signup, ativação de usuários, experiência de primeira execução ou time-to-value. Use também quando o usuário menciona "fluxo de onboarding", "taxa de ativação", "ativação de usuários", "experiência de primeira execução", "empty states", "checklist de onboarding", "aha moment" ou "experiência do novo usuário". Para otimização de signup/registro, veja signup-flow-cro. Para sequências de email contínuas, veja email-sequence.
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。