「aria」の検索結果

Execute per-layer adversarial audit/remediation loop, persist fixes metadata, and manage fresh-run advancement

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。

Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.

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 Kanpeki component library in React projects. Activate when user wants to add, use, customize, or compose accessible UI components from Kanpeki (@kanpeki/*). Covers installation, component patterns, forms, theming, and dark mode with React Aria Components + Tailwind CSS 4.1 + CVA.

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 working with Convex — convex backend platform management covering project inventory, table schemas, function deployments, scheduled job status, index configuration, environment variable auditing, and usage metrics. Use for comprehensive Convex project health and resource optimization.

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 working with Deno Deploy Deep — deep Deno Deploy analysis covering project inventory, deployment history, KV database usage, cron job schedules, custom domain mappings, analytics metrics, and environment variable auditing. Use for comprehensive Deno Deploy platform management.

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 working with Caprover — capRover self-hosted PaaS management covering app inventory, container status, custom domain mappings, persistent directory mounts, environment variable auditing, cluster node status, Docker registry integration, and Nginx configuration review. Use for managing CapRover infrastructure.

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 working with Chamber — chamber secrets management using AWS Systems Manager Parameter Store, service-scoped secret organization, environment variable export, and parameter auditing. Covers reading and writing secrets by service, comparing environments, listing services, version tracking, and IAM permission validation. Use when managing AWS SSM-based secrets with Chamber, auditing parameter changes, or comparing configs across services.

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 working with Balena — balena IoT fleet management including applications, devices, releases, services, environment variables, and device diagnostics. Covers fleet deployment status, device connectivity, container health, update progress, and resource utilization across edge devices.

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 working with Apache Airflow Deep — apache Airflow deep management covering DAG inventory, task instance monitoring, scheduler health, executor status, pool and variable management, connection auditing, and SLA miss tracking. Use when investigating DAG failures, analyzing task duration trends, monitoring scheduler performance, or auditing Airflow configurations.

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 working with Airflow — apache Airflow workflow orchestration management. Covers DAG management, task instance monitoring, executor health, pool status, variable management, connection audit, and scheduler diagnostics. Use when checking DAG run status, investigating task failures, managing Airflow resources, or auditing configurations.

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 working with Mysql — mySQL and MariaDB database analysis, performance tuning, query optimization, and health monitoring. Covers slow query investigation, index analysis, table statistics, replication health, InnoDB status, connection pool analysis, and schema inspection.

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。

Roleplay a hostile user to find and triage UX pain points.

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。

Throwaway HTML mockups: 2-3 design variants to compare.

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 ARCHS4 REST API for uniformly processed RNA-seq expression, tissue patterns, co-expression across 1M+ human/mouse samples. Retrieve z-scores, co-expressed genes, samples by metadata, HDF5 matrices. For variant population genetics use gnomad-database; for pathway enrichment use gget-genomic-databases (Enrichr).

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。

scikit-learn compatible Python toolkit for time series ML: classify, cluster, regress, segment, transform with 30+ algorithms (ROCKET, InceptionTime, KNN-DTW, HIVE-COTE, WEASEL). Handles panel, multivariate, and unequal-length series. Maintained successor to sktime. Alternatives: sktime (larger ecosystem), tslearn (fewer algorithms), catch22 (features only).

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。

Deploy and manage projects on Vercel using token-based authentication. Use when working with Vercel CLI using access tokens rather than interactive login — e.g. "deploy to vercel", "set up vercel", "add environment variables to vercel".

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 WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.

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。

Prepare Stitch screen-generation, edit, image-to-design, and variant prompts with verified tool checks and design-system-aware wording.

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 users through configuring key MongoDB MCP server options. Use this skill when a user has the MongoDB MCP server installed but hasn't configured the required environment variables, or when they ask about connecting to MongoDB/Atlas and don't have the credentials set up.

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。

Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.

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。

PHP 8.0+ development — XAMPP, RESTful APIs, PDO/MySQL/MariaDB, and authentication. Use when building PHP backends, creating API endpoints, configuring XAMPP, or integrating PHP with databases.

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。

Write, configure, and deploy Netlify serverless functions in TypeScript, JavaScript, or Go. Use this when adding an API endpoint or backend route, adding a contact form handler, wiring auth or Identity signup/login hooks, building streaming or AI-proxy responses, scheduling cron jobs, running long background jobs (batch processing/scraping), reacting to deploy or form events, setting up rate limiting or region/memory config, or reading environment variables and secrets inside a function. Covers file locations, the Request/Context/Response handler shape, path routing, config options, and local testing with netlify dev.

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。

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。