「components」の検索結果

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

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 whenever the user asks to "create a module", "scaffold a feature", "add a Vue domain", "new module called X", or starts work on a brand-new vertical (views + components + store + router entry + tests). Duplicates the canonical `src/modules/tasks` template, applies kebab/Pascal/camel/ UPPER renames, and wires config-driven values. Module stays self-contained.

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 system reference for the Devkit Vue stack (Vuetify 4 + custom theme helpers). Use when asked about styling, theming, layout, design system, Vuetify components, visual verification, or UI patterns. Automatically consumed by /feature when the task has a visual component. Can also be invoked directly for design-only tasks (restyle, theme change, layout fix).

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。

Migrate Terraform projects to Pulumi. Use when users need to move infrastructure from Terraform to Pulumi, translate HCL configurations, or convert Terraform modules to Pulumi 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。

Creates Pulumi infrastructure-as-code projects in Go, configures OIDC authentication, integrates with Pulumi ESC for centralized secrets and configuration management, and builds multi-language component resources. Use when setting up Pulumi Go projects, writing infrastructure code with Go, configuring OIDC for Pulumi, using Pulumi ESC with Go, automating cloud infrastructure with Golang, creating reusable Pulumi components in Go, or working with pulumi-go-provider. Also use when the user mentions Pulumi with Go/Golang, AWS/Azure/GCP infrastructure in Go, or Go-based ComponentResource patterns.

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 Pulumi infrastructure-as-code projects in Python, defines cloud resources (AWS, Azure, GCP), configures ESC environments for secrets management, sets up OIDC authentication for secure deployments, and builds multi-language component resources. Use when creating Pulumi Python projects, writing infrastructure code, configuring cloud providers, managing secrets with Pulumi ESC, setting up OIDC for Pulumi, automating infrastructure deployments with Python, creating reusable Pulumi components in Python, or configuring Python toolchains (pip, poetry, uv) for Pulumi. Also use when the user mentions pyproject.toml with Pulumi, component_provider_host, or Python virtual environments for infrastructure 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。

Guide for authoring Pulumi ComponentResource classes. Use when creating reusable infrastructure components, designing component interfaces, setting up multi-language support, or distributing component packages.

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 building C# applications with .NET 8+, ASP.NET Core APIs, or Blazor web apps. Builds REST APIs using minimal or controller-based routing, configures database access with Entity Framework Core, implements async patterns and cancellation, structures applications with CQRS via MediatR, and scaffolds Blazor components with state management. Invoke for C#, .NET, ASP.NET Core, Blazor, Entity Framework, EF Core, Minimal API, MAUI, SignalR.

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。

Search LCSC Electronics for electronic components — find parts by LCSC number (Cxxxxx) or MPN, check stock/pricing, download datasheets, analyze specifications. Sister company to JLCPCB, same parts library. Sync and maintain a local datasheets directory for a KiCad project. No API key needed — uses the free jlcsearch community API. Use this skill when the user mentions LCSC, JLCPCB parts library, JLCPCB assembly parts, production sourcing, Cxxxxx part numbers, needs to find LCSC equivalents for parts, is preparing a BOM for JLCPCB assembly, or wants to download datasheets and LCSC is available. For package cross-reference tables and BOM workflow, see the `bom` 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。

PCBWay PCB fabrication and assembly — turnkey/consigned assembly, design rules, ordering workflow. Alternative to JLCPCB for manufacturing. Use with KiCad. Use this skill when the user mentions PCBWay, needs turnkey assembly (PCBWay sources parts by MPN), has parts not available on LCSC, needs assembled boards with non-LCSC components, wants to compare PCBWay vs JLCPCB, or needs assembly with parts sourced globally rather than from LCSC only. For gerber/CPL export, stencil ordering, and BOM management, see the `bom` 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。

Search Mouser Electronics for electronic components — secondary source for prototype orders. Find parts, check pricing/stock, download datasheets, analyze specifications. Use with KiCad for BOM creation and part selection. Use this skill when the user specifically mentions Mouser, when DigiKey is out of stock or has worse pricing, when comparing prices across distributors, or when searching for parts that DigiKey doesn't carry. For package cross-reference tables and BOM workflow, see the `bom` 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。

Master Figma workflows with auto layout, components, variables, prototyping, and team collaboration.

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 and govern scalable design systems with tokens, components, documentation, and adoption 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。

Battery science fundamentals — cell components, electrochemistry metrics, testing protocols, and degradation analysis.

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。

Idiomatic Angular: standalone components, signals, RxJS patterns, DI, and enterprise structure. Use when writing, reviewing, or structuring Angular applications.

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。

Turn a design into production-quality frontend code: extract a design system with tokens and components, make layouts responsive across breakpoints, add dark mode with WCAG-compliant theming, then run a UX audit to validate everything..

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 custom components and layouts against shadcn design patterns, visual style conventions (Vega, Nova, Maia, Lyra, Mira), composition rules, design token usage, and Radix/Base UI composition patterns. Use PROACTIVELY after writing or modifying any custom UI component, page layout, or variant of a shadcn component. Use when the user says "review this component", "check my spacing", "does this follow shadcn patterns", "audit this layout", "is this shadcn-idiomatic", or shares a component for feedback. Catches spacing drift, hardcoded colors, missing data-slot attributes, inconsistent theme application, and composition anti-patterns that shipping-fast-with-AI tools often miss.

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。

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

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。

Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX 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。

Suite of tools for creating elaborate, multi-component Codex.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX 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。

Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is 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。

Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX 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。

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

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。

Find one insight that eliminates multiple components - "if this is true, we don't need X, Y, or Z"

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。