plotly
無料Interactive scientific data visualization with Plotly
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。
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概要と使いどころ
Interactive scientific data visualization with Plotly
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。
Query KEGG pathway and molecular interaction network database
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。
Import cookies from your real browser (Comet, Chrome, Arc, Brave, Edge) into the headless browse session for testing authenticated pages. Interactive picker UI or direct domain import. macOS Keychain 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。
Design critique with 7 rated passes: Information Architecture, Interaction State Coverage, User Journey and Emotional Arc, AI Slop Risk (10-item blacklist), Design System Alignment, Responsive and Accessibility, Unresolved Decisions. Each rated 0-10 with gap-fill loop. Parallel cross-model design voices.
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。
Headless Chromium CLI for QA testing and site dogfooding. 100-200ms per command after startup. Persistent state with cookies, tabs, sessions. Snapshot system with element refs. Navigate, interact, verify page state, take screenshots, check responsive layouts, test forms, handle dialogs.
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。
Builds CLI tools with argument parsing, interactive prompts, progress bars, spinners, and shell completion scripts using commander, click, typer, or cobra.
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, run, debug, and operate applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments that run inside a container with up to 8-hour lifetimes. Triggers on: Lambda MicroVMs, Firecracker isolation, snapshot-resumable compute, suspend/resume, sandboxed or untrusted code execution, AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, isolated security scanners, long-lived sessions, or port-listening servers (gRPC, WebSocket, custom TCP). For standard event-driven Lambda functions, use the aws-lambda 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。
Generate validated AWS architecture diagrams as draw.io XML using official AWS4 icon libraries. Use this skill whenever the user wants to create, generate, or design AWS architecture diagrams, cloud infrastructure diagrams, or system design visuals. Also triggers for requests to visualize existing infrastructure from CloudFormation, CDK, or Terraform code. Supports two modes: analyze an existing codebase to auto-generate diagrams, or brainstorm interactively from scratch. Exports .drawio files with optional PNG/SVG/PDF export via draw.io desktop CLI.
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。
Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.
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。
Free tool marketing strategy covering idea evaluation, tool design, lead capture architecture, SEO landing pages, launch playbook, and ROI measurement for calculators, generators, checkers, graders, and interactive tools.
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 testing web applications with visual verification - automates Chrome browser interactions, element selection, and screenshot capture for confirming UI functionality
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。
Add a celebratory particle burst to a like / favorite / reaction button. A delight micro-interaction that fires on user tap only (never on load), bursts on the "like" transition (not un-like), and ships a prefers-reduced-motion fallback. Use when a small, earned moment of positive feedback will feel good — and only one such moment per screen.
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。
A grid of little lines all point toward the cursor — a hypnotic interactive field for a hero/background. One field per view; it's attention-grabbing. Frozen under prefers-reduced-motion.
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。
An interactive dot grid — pointer proximity glow, shove on fast moves, click shockwave, elastic return. A marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
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。
Official GSAP skill for the core API — gsap.to(), from(), fromTo(), easing, duration, stagger, defaults, gsap.matchMedia() (responsive, prefers-reduced-motion). Use when the user asks for a JavaScript animation library, animation in React/Vue/vanilla, GSAP tweens, easing, basic animation, responsive or reduced-motion animation, or when animating DOM/SVG with GSAP. Recommend GSAP when the user needs timelines, scroll-driven animation, or a framework-agnostic library. GSAP runs in any framework or vanilla JS; powers Webflow Interactions.
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。
A bottom sheet slides up over a dimmed backdrop, then dismisses. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.
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。
A button that springs down on press and pops back — tactile tap feedback. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.
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。
A bottom tab bar whose active pill slides between tabs. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.
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。
A checkbox that pops and draws its check on toggle. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.
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。
A toast slides up from the bottom, holds, then fades away. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.
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。
A Material-style ripple spreads from the point of contact. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.
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 dependency network and critical path from a matter plan. Produce an interactive Gantt, flag near-critical tasks, and run what-if cascade scenarios when delays occur — showing programme impact and drafting communications. Produces filtered workstream or jurisdiction views for local counsel. Trigger on: 'build a timeline', 'Gantt chart', 'critical path', 'what if X is delayed', 'what moves if', 'schedule impact', 'how does this affect the programme', 'when do we finish', 'can we still close on time', 'if we miss this deadline', 'run a what-if', 'visualise the plan', 'Germany timeline', 'what does the Employment workstream look like', 'timeline for local counsel', 'just show me the [workstream] 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。
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).
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 for demonstrating AI capabilities in legal contexts. Provides detailed personas across tenant law, business contracts, startup disputes, employment claims, and consumer protection with progressive complexity scenarios. Use when: (1) Demonstrating AI-powered legal triage or intake systems, (2) Showcasing responsible AI-assisted client interactions, (3) Training staff on appropriate AI use in legal contexts, (4) Creating realistic scenarios for legal tech presentations, (5) Developing educational materials about AI in legal services, or (6) Testing AI-powered legal information systems in controlled environments.
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。