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概要と使いどころ
Python research assistant with Context7 MCP. Use for Python library research, evaluating packages, enforcing strict Python coding standards, or fetching up-to-date library docs via Context7.
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, scrape, and interact with the web via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, get data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference external websites. This provides real-time web search with full page content and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.
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 in TanStack Query (React Query) — asynchronous state management. Covers data fetching, stale time configuration, mutations, optimistic updates, and Next.js App Router (SSR) integration.
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 performance optimization guide for React and Next.js applications, maintained by Vercel. Use when writing new React components or Next.js pages, implementing data fetching (client or server-side), or reviewing code for performance issues.
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。
Next.js App Router principles. Server Components, data fetching, routing 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。
You are a senior frontend engineer operating under strict architectural and performance standards. Use when creating components or pages, adding new features, or fetching or mutating 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。
Web scraper with SPA/JavaScript rendering, page interaction, and JS execution. Two-tier engine (HTTP → Playwright browser). Smart discovery, batch fetch, interactive content extraction, OpenAPI parsing. Use when read_url_content fails, SPA rendering needed, or page interaction 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。
Expert guidance for designing, implementing, migrating, and debugging SwiftData persistence in Swift and SwiftUI apps. Use when working with @Model schemas, @Relationship/@Attribute rules, Query or FetchDescriptor data access, ModelContainer/ModelContext configuration, CloudKit sync, SchemaMigrationPlan/history APIs, ModelActor concurrency isolation, or Core Data to SwiftData adoption/coexistence.
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。
Implement, review, or improve data persistence using SwiftData. Use when defining @Model classes with @Attribute, @Relationship, @Transient, @Unique, or @Index; when querying with @Query, #Predicate, FetchDescriptor, or SortDescriptor; when configuring ModelContainer and ModelContext for SwiftUI or background work with @ModelActor; when planning schema migrations with VersionedSchema and SchemaMigrationPlan; when setting up CloudKit sync with ModelConfiguration; or when coexisting with or migrating from Core 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。
Fetch current, hourly, and daily weather forecasts and display required attribution using WeatherKit. Use when integrating weather data, showing forecasts, handling weather alerts, displaying Apple Weather attribution, or querying historical weather statistics in iOS apps.
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。
Schedule and execute background work on iOS using BGTaskScheduler. Use when registering BGAppRefreshTask for short background fetches, BGProcessingTask for long-running maintenance, BGContinuedProcessingTask (iOS 26+) for foreground-started work that continues in background, background URLSession downloads, or background push notifications. Covers Info.plist configuration, expiration handling, task completion, and debugging with simulated launches.
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, review, or improve networking code in iOS/macOS apps using URLSession with async/await, structured concurrency, and modern Swift patterns. Use when working with REST APIs, downloading files, uploading data, WebSocket connections, pagination, retry logic, request middleware, caching, background transfers, or network reachability monitoring. Also use when handling HTTP requests, API clients, network error handling, or data fetching in Swift apps.
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。
Translate Figma designs into production-ready SwiftUI code with 1:1 visual fidelity using the Figma MCP workflow. Trigger when the user provides Figma URLs or node IDs and wants iOS/SwiftUI implementation, asks to implement a design or component from Figma for an iOS app, or references Figma selections in the context of an Xcode/SwiftUI project. Also trigger when user asks to inspect Figma designs for iOS planning, fetch design tokens for SwiftUI, or convert Figma assets for Xcode. Requires a working Figma MCP server connection. Do NOT trigger for web/React 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。
Combine React's official "You Might Not Need an Effect" guidance with this project's stricter no direct useEffect stance. Use when writing, reviewing, or refactoring React components that might reach for useEffect, derived state, event relays, reset logic, subscriptions, or client fetching.
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。
Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.
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 React UI patterns for loading states, error handling, and data fetching. Use when building UI components, handling async data, or managing UI states.
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。
Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when creating components, pages, features, fetching data, styling, routing, or working with frontend 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。
Next.js App Router principles. Server Components, data fetching, routing 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。
Automatically fetch latest library/framework documentation for Claude Code via Context7 API
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。
Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser 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。
Search the public web and crawl URLs via the Unique AI Platform's `unique-cli web-search` command, with automatic per-turn citation tracking so cited web facts render as clickable external reference chips and `<sup>N</sup>` footnotes on the Unique platform. ALWAYS use this skill when the user asks to search the public web, research a topic online, look up news/articles/regulations, fetch the contents of one or more URLs, or perform any "two-phase" web research (search → review snippets → crawl selected URLs for full content). Routes through the Unique AI Platform's `/web-search-api` endpoints, so the engine (Google, Brave, Tavily, Jina, Firecrawl, …) and crawler are resolved server-side from the current environment — you never need to manage engine API keys yourself. Use this instead of fabricating answers from training data whenever fresh / source-cited information is needed. Do NOT use this skill for the internal knowledge base (`unique-cli search`) or for arbitrary tool execution (`unique-cli mcp`).
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 the RIPE Atlas REST API v2 to find probes, inspect measurements, create and monitor network measurements, and fetch results. Use when the user asks about Atlas probes, measurements, ping, traceroute, DNS, HTTP, TLS, NTP, or globally distributed reachability checks.
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。
Tavily MCPを使用して最新AIニュースを取得し、日英バイリンガルのマークダウン記事を生成。「AIニュースを取得」「最新ニュース」などで使用。
Fetch Airbnb income estimate (ADR, occupancy, monthly revenue) for any area using the official Airbnb GraphQL API — the same data the Airbnb host simulator shows. Input: station/area name. Output: per-night rate, avg nights, monthly estimate for entire_home and private_room.
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。