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Expert guidance for simulating RoadRunner scenarios via the MATLAB programmatic API and Simulink co-simulation. Use when the user wants to run a simulation, step through a simulation, control actors during co-simulation, add observers, attach sensors, retrieve simulation logs, or read/write scenario variables. Covers simulateScenario, createSimulation, ScenarioSimulation set/get, ActorSimulation getAttribute/setAttribute, addObserver, SensorSimulation, Simulink co-sim blocks, and publishActorBehavior. NOT for project setup, scene building, scenario authoring, or trajectory export.

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。

Programmatically author RoadRunner scenarios from MATLAB using roadrunnerAPI. Use when adding actors, creating routes, building scenario logic (phases, conditions, actions), placing vehicles/pedestrians, defining cut-in/crossing/ follow scenarios, or any programmatic scenario creation in RoadRunner. Triggers on: roadrunnerAPI, scenario authoring, add actor, create route, phase logic, cut-in scenario, pedestrian crossing, scenario from MATLAB.

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。

Display images and annotations for image processing, computer vision, and visual inspection. Use when displaying images with imageshow, creating image viewers with viewer2d, adding Regions of Interest (ROI) or annotations, overlaying masks or segmentations, streaming video frames, or building apps with image display.

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。

Writes turn-level tests for a LiveKit agent in the user's normal test suite: pytest (Python) or Vitest (Node.js). Use when the user asks to "write tests for my agent", "add a test for this tool", "test the handoff", "pin this bug", "why does my agent test fail", or after building or changing agent behavior that needs regression coverage. Covers the SDK's test session harness, assertions on messages, tool calls and handoffs, LLM judging of a reply against an intent, mocking tools, multi-turn tests, and judging whole conversations with the built-in judges. For interactive poking use debugging-livekit-agents. For grading whole conversations at scale use running-livekit-simulations.

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 Metronome usage-based billing integration decisions — event ingestion (single and batch, idempotency, billable metrics), contract design (rate cards, overrides, dimensional pricing, products), invoicing lifecycle (grace periods, finalization, Stripe sync), credit and commit management (prepaid, postpaid, thresholds, auto-recharge), and Stripe integration (arrears invoicing, tax providers, line item limits). Use when building, modifying, or reviewing any Metronome integration — including ingesting usage events, creating customers, contracts, or rate cards, designing billable metric group keys, managing credits and commits, configuring invoicing, syncing invoices with Stripe Billing, billing AI applications for token usage, setting up self-serve (PLG) pricing, reviewing customer health, commit burn, portfolios, or renewals, or migrating from Stripe Billing Meters to Metronome.

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 and edit presentation slide decks (`.pptx`) with PptxGenJS, bundled layout helpers, and render/validation utilities. Use when tasks involve building a new PowerPoint deck, recreating slides from screenshots/PDFs/reference decks, modifying slide content while preserving editable output, adding charts/diagrams/visuals, or diagnosing layout issues such as overflow, overlaps, and font substitution.

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。

React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

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 when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform, multi-vendor store, gig platform, or subscription platform, needs to pay out sellers, vendors, or providers, mentions split payments, revenue sharing, multi-party payments, or similar payment distribution concepts, provides a company URL or business description for a recommendation, builds SaaS that routes money between parties (for example, POS, booking, invoicing — not operational SaaS without payment routing), asks about onboarding or KYC for merchants, sellers, and vendors, mentions connected account Dashboard or responsibility configurations, or asks about payment flows, white-label payments, or embedded payments.

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 building, modifying, or reviewing a Stripe App — or when the user describes something that implies one (e.g. "add a panel to the customer page", "customize my Stripe Dashboard", "react to Stripe events from my app", "connect my service to Stripe without sharing API keys"). Covers the full app development workflow (scaffold, preview, upload, versioning), UI extension architecture (sandboxed iframe, Stripe UI toolkit, viewports), extension types (UI extensions, backend-only, extension interfaces, embedded apps), authentication (platform keys, OAuth, restricted API keys), stripe-app.yaml manifest setup (permissions, viewports, CSP), webhook configuration for apps, Secret Store API, `fetchStripeSignature` auth, and marketplace publishing, plus submitting one agentic feedback report after a build. Use when the user mentions Stripe Apps, UI extensions, @stripe/ui-extension-sdk, @stripe/extensibility-sdk, script extensions, stripe-app.yaml, Dashboard extensions, or customizing the Stripe Dashboard.

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。

Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.

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 voice and chat AI agents with LiveKit Agents on LiveKit Cloud or a self-hosted server. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI to my app", "implement handoffs", "structure an agent workflow", "my agent is slow / too chatty", "it says it booked but nothing was saved", "make it confirm before committing", "it keeps re-asking things the caller already said", or is writing code against the LiveKit Agents SDK. Covers architecture: designing for latency, keeping context small, splitting a monolithic agent into handoffs and tasks, and designing for voice. Also covers keeping the model in charge of meaning while code owns state, approvals, and effects. For API specifics use reading-livekit-docs. To check behavior use debugging-livekit-agents and testing-livekit-agents.

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。

Deploys and operates a LiveKit agent in production: shipping a version to LiveKit Cloud and rolling it back, secrets and configuration, the worker process model and prewarming, safe async inside worker processes, provider timeouts and degradation, graceful shutdown, SDK upgrades, and observability. Use when the user says "deploy my agent", "roll back the deployment", "tail the agent logs", "the first call after a restart is slow", "attached to a different loop / event loop is closed", "prewarm the VAD", "shut down without dropping calls", "upgrade livekit-agents safely", "correlate logs by session", or is changing an agent codebase that is already live. Not for designing the agent (building-livekit-agents) or reproducing one bad conversation locally (debugging-livekit-agents).

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。

Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.

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。

Scan container images for vulnerabilities using Trivy, Grype, and cloud-native tools. Identify security issues in base images, packages, and configurations. Use when implementing container security, building secure images, or meeting compliance requirements.

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。

Handle security incidents with IR playbooks and procedures. Implement detection, containment, eradication, and recovery processes. Use when responding to security events or building incident response 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。

Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production 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。

Secure Docker images and container runtime configurations. Implement non-root users, read-only filesystems, and security contexts. Use when building secure container images or hardening container deployments.

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 and operate apps on Firebase using Auth, Firestore, Cloud Functions, and Hosting. Use when building mobile/web backends with managed services, real-time data sync, or serverless 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。

Configure a Mac mini as a reliable local LLM server with remote access, observability, and power-safe operation. Use when building an always-on private AI inference server on Apple Silicon.

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 reactive backends with Convex functions, schema validation, auth integration, and deployment workflows. Use when building real-time apps with type-safe server functions and automatic caching.

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 and operationalize SRE dashboards that surface reliability, latency, error, saturation, and capacity signals across services. Use when building observability views for SLOs, incident response, and executive reliability reporting.

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 the ELK Stack (Elasticsearch, Logstash, Kibana) for log aggregation and analysis. Configure log pipelines, create visualizations, and implement log-based monitoring. Use when centralizing logs, implementing search functionality, or building log analytics platforms.

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。

Develop business continuity plans and impact analysis. Implement BCP testing and communication procedures. Use when building organizational resilience.

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。

Configure GitLab CI/CD pipelines and runners for automated building, testing, and deployment. Create .gitlab-ci.yml configurations, manage runners, and implement DevOps workflows. Use when working with GitLab repositories or self-hosted GitLab instances.

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。