「interaction」の検索結果

Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI 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。

Systematically improves Largest Contentful Paint (LCP), Interaction to Next Paint (INP), and Cumulative Layout Shift (CLS) with prioritized fixes and verification. Use for "Core Web Vitals", "performance", "LCP", "INP", or "CLS".

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。

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

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。

Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.

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。

Browser automation powers web testing, scraping, and AI agent interactions. The difference between a flaky script and a reliable system comes down to understanding selectors, waiting strategies, and anti-detection patterns. This skill covers Playwright (recommended) and Puppeteer, with patterns for testing, scraping, and agentic browser control. Key insight: Playwright won the framework war. Unless you need Puppeteer's stealth ecosystem or are Chrome-only, Playwright is the better choice in 202

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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm

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。

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

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 product demo videos by automating browser interactions and capturing frames. Use when the user wants to record a demo, walkthrough, product showcase, or interactive video of a web application. Supports Playwright CDP screencast for high-quality capture and FFmpeg for video encoding.

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。

Control and interact with a live browser session on any scraped page — click buttons, fill forms, navigate flows, and extract data using natural language prompts or code. Use when the user needs to interact with a webpage beyond simple scraping: logging into a site, submitting forms, clicking through pagination, handling infinite scroll, navigating multi-step checkout or wizard flows, or when a regular scrape failed because content is behind JavaScript interaction. Also useful for authenticated scraping via profiles. Triggers on "interact", "click", "fill out the form", "log in to", "sign in", "submit", "paginated", "next page", "infinite scroll", "interact with the page", "navigate to", "open a session", or "scrape failed".

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 scraping, search, crawling, and page interaction 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, extract 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 scraping external websites. This provides real-time web search with full page content extraction 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。

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, or extract information from web pages.

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。

Plan and diagnose FIPA-style ontology-service interactions while keeping declared ontology relations, provider capability, and application authorization separate. NOT for treating an ontology mapping as provider authority or guaranteed interoperability.

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Long-running design anthropologist that builds comprehensive visual databases from 500-1000 real-world examples, extracting color palettes, typography patterns, layout systems, and interaction design across any domain (portfolios, e-commerce, SaaS, adult content, technical showcases). This skill should be used when users need exhaustive design research, pattern recognition across large example sets, or systematic visual analysis for competitive positioning.

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Design and build beautiful, accessible graphical interfaces — web, desktop (Electron/Tauri), and native (iOS/macOS/Android). Use for visual hierarchy and layout, color and theming (light/dark, semantic tokens, WCAG contrast), typography systems, motion and micro-interactions, accessibility, component systems and design tokens, responsive/adaptive layout, and platform-native idioms. The GUI counterpart to beautiful-cli-design. NOT for terminal/CLI output (use beautiful-cli-design) or API/data schemas.

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 decisions for when and what sounds to use in web apps, mobile apps, and desktop native apps — plus how to create them with AI. Covers UI sound vocabulary (confirms, alerts, transitions, errors), platform conventions (iOS, macOS, Material), creating sounds with AI tools (ElevenLabs, AudioCraft, Stable Audio), Web Audio API for procedural sounds, haptic-audio pairing, and the psychology of satisfying vs. annoying UI sounds. Activate on 'app sounds', 'UI sounds', 'notification sound', 'sound design app', 'earcons', 'sonic branding', 'interaction sounds', 'feedback sounds', 'app audio', 'satisfying sounds'. NOT for professional audio engineering (use sound-engineer), Windows 3.1 retro sounds specifically (use win31-audio-design), music composition (use sound-engineer).

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。

Declare an agentic application's interaction disclosure, state, context, capabilities, and effect-control boundaries. Use for a reviewable design specification and static consistency audit before implementation. NOT for proving that controls are deployed or enforced, exposing private chain-of-thought, selecting a model/router, or designing a multi-agent protocol.

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。

Frame multi-agent designs through explicit environment, autonomy, information, coordination, commitment, incentive, and verification assumptions. NOT for endorsing multi-agent architecture without need or claiming runtime correctness from conceptual 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。