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概要と使いどころ
Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.
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 skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code', 'convert this modal/dialog/drawer/panel to Figma'. This is the preferred workflow skill whenever the user wants to build or update a full page, modal, dialog, drawer, sidebar, panel, or any composed multi-section view in Figma from code or a description. Discovers design system components, variables, and styles from Code Connect files, existing screens, and library search, then imports them and assembles views incrementally section-by-section using design system tokens instead of hardcoded values.
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。
Replace arbitrary timeouts with condition polling for reliable async tests
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。
Choose and compare cloud design patterns for distributed systems. Use when reviewing architecture, selecting workload patterns, or mapping reliability, performance, messaging, security, and migration concerns to concrete design options.
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。
Data Engineer IA — Expert en pipelines de données (ETL, data lakes, dbt, Airflow, streaming). Construit des pipelines fiables, scalables et auditable.
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 en négociation de contrats v2 (terms, SLAs, renouvellement, PI, responsabilité, contexte juridique DZ)
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 using MSBuild Server to improve CLI build performance. Only activate in MSBuild/.NET build context. Activate when developers report slow incremental builds from the command line, or when CLI builds are noticeably slower than IDE builds. Covers MSBUILDUSESERVER=1 environment variable for persistent server-based caching. Do not activate for IDE-based builds (Visual Studio already uses a long-lived process).
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 cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, and GCP.
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。
Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design.
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, audit, and improve analytics tracking systems that produce reliable, decision-ready 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。
Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI, Anthropic, and Google APIs.
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 data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.
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 advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.
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。
Validate n8n expression syntax and fix common errors. Use when writing n8n expressions, using {{}} syntax, accessing $json/$node variables, troubleshooting expression errors, or working with webhook data in workflows.
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。
Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI, Anthropic, and Google APIs.
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.
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。
iOS design system tokens for Pencil MCP: SF Pro typography scale, iOS semantic colors (light + dark mode hex values), spacing grid, touch targets, corner radii, and component heights. Use when initializing a .pen file for iOS design or setting up design variables.
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 SwiftUI animations and transitions. Use when adding explicit animations with withAnimation, configuring implicit animations with .animation(_:body:) or .animation(_:value:), configuring spring animations (.smooth, .snappy, .bouncy), building phase or keyframe animations with PhaseAnimator/KeyframeAnimator, creating hero transitions with matchedGeometryEffect or matchedTransitionSource, adding SF Symbol effects (bounce, pulse, variableColor, breathe, rotate, wiggle), implementing custom Transition or CustomAnimation types, or ensuring animations respect accessibilityReduceMotion.
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, refactor, or review macOS menubar apps that use Tuist and SwiftUI. Use when creating or maintaining LSUIElement menubar utilities, defining Tuist targets/manifests, implementing model-client-store-view architecture, adding script-based launch flows, or validating reliable local build/run behavior without Xcode-first workflows.
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。
Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps. Use when the user asks for a review swarm, parallel review, diff review, regression review, security review, or wants high-signal issues plus a prioritized fix path without editing files.
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。
Set up and configure WorkOS AuthKit authentication with Convex backend. Use when integrating AuthKit, configuring JWT providers, setting up environment variables, or implementing sign in and sign out flows with React and Vite. Supports Netlify deployment.
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。
Activate for any ticket that adds or changes a Supabase migration, environment variable, edge function deployment, or runtime configuration. Ensures infrastructure is live in the target QA environment before state:ready-for-qa.
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。
Behavioral guardrails for implementation work. Reduces common LLM coding mistakes: overcomplication, silent assumption-picking, scope drift, and unverifiable success criteria. Load on Builder and software-engineer-mode.
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: analysing a project's debug and reliability health — inline markers, logging hygiene, and error handling.
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。