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概要と使いどころ
Reference skill for Zoom Apps SDK. Use after routing to an in-client app workflow when building web apps that run inside Zoom meetings, webinars, the main client, or Zoom Phone.
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。
Reference skill for Zoom Video SDK UI Toolkit. Use after routing to a web video workflow when you want prebuilt React UI instead of building a fully custom Video SDK interface.
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。
Zoom Video SDK for iOS native apps. Use when building custom iOS video sessions with full UI control, token-based session auth, and event-driven media/participant flows.
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。
Zoom Video SDK for Web - JavaScript/TypeScript integration for browser-based video sessions, real-time communication, screen sharing, recording, and live transcription
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。
Zoom Meeting SDK for Web - Embed Zoom meeting capabilities into web applications. Two integration options: Client View (full-page, familiar Zoom UI) and Component View (embeddable, Promise-based API). Includes SharedArrayBuffer setup for HD video, gallery view, and virtual backgrounds.
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。
Zoom Video SDK for Android native apps. Use when building custom Android video experiences with full UI control, session tokens, raw media options, and event-driven participant 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。
Reference skill for Zoom Video SDK. Use after routing to a custom-session workflow when the user needs full control over the video experience rather than an actual Zoom meeting.
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。
Zoom Meeting SDK for Linux - C++ headless meeting bots with raw audio/video access, transcription, recording, and AI integration for server-side automation
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。
Zoom Meeting SDK for Electron desktop applications. Use when embedding Zoom meetings in an Electron app with the Node addon wrapper, JWT auth, join/start flows, settings controllers, and raw data 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。
Zoom Video SDK for macOS native desktop apps. Use when building custom macOS video sessions with native UI control, tokenized join, and desktop-oriented media/device 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。
Zoom Video SDK for Linux - C++ headless bots, raw audio/video capture/injection, Qt/GTK integration, Docker support
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。
Reference skill for Zoom Probe SDK. Use after routing to a preflight workflow when testing browser compatibility, media permissions, audio or video diagnostics, and network readiness before users join.
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。
Reference skill for Zoom Cobrowse SDK. Use after routing to a collaborative-support workflow when implementing browser co-browsing, annotation tools, privacy masking, remote assist, or PIN-based session sharing.
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 a Kubernetes Operator — custom controllers that reconcile CRD state. Triggers on "build an operator", "CRD design", "reconcile loop", "controller-runtime", "kubebuilder", "operator-sdk", "metacontroller", "KOPF", "operator capability levels", or "custom resource". Ships CRD validator, reconcile-loop linter, and OperatorHub capability auditor (all stdlib Python), 4 references on the operator pattern + CRD design + reconcile patterns + tooling landscape, and a /operator-audit slash command. NOT a generic k8s skill — specifically the Operator pattern.
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。
Bootstrap, develop, and design modern WinUI 3 desktop applications with C# and the Windows App SDK using official Microsoft guidance, WinUI Gallery patterns, Windows App SDK samples, and CommunityToolkit components. Use when creating a brand new app, preparing a machine for WinUI, reviewing, refactoring, planning, troubleshooting, environment-checking, or setting up WinUI 3 XAML, controls, navigation, windowing, theming, accessibility, responsiveness, performance, deployment, or related Windows app design and development work.
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, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.
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 the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API.
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 the Google Interactive Media Ads (IMA) Dynamic Ad Insertion (DAI) SDK into websites, web apps, mobile apps, or TV apps. Use when: - A video player needs to load and play HLS or DASH streams in web apps, Android apps, iOS apps, tvOS apps, Cast (CAF) receivers, or Roku channels. - The app needs to make use of a Google DAI livestream event asset key, or content source CMS ID, video ID for video on demand. Don't use this skill to load and play a VAST or VMAP URL.
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。
Supports Interactive Media Ads (IMA) SDK. Use this skill for client-side ad insertion when you are requesting video ads for websites, apps, TVs or other platforms using VAST or VMAP. Do not use for Dynamic Ad Insertion (DAI), SSAI, or SGAI.
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 for every Kortix test task, behavior change, bug fix, refactor, API route change, CLI change, SDK change, browser journey, test failure, coverage question, local benchmark, or testing infrastructure change. Enforce the single local-first runner, black-box flow contracts, package-local SDK tests, browser-only Playwright tests, and real input/output verification.
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 iii SDK APIs across Node.js, browser, Python, or Rust: package installation, worker initialization, function/trigger registration, invocation, channels, logging, OpenTelemetry, and language-specific caveats.
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 iii engine and SDK errors across Node, Python, Rust, and browser workers. Use when interpreting error codes, retryability, RBAC denial, timeouts, handler failures, or SDK-specific exception surfaces.
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。
Export raw OpenTelemetry traces from an AI application to Confident AI's Observatory. TRIGGER when the user wants to send OpenTelemetry or OTLP traces/spans from an LLM app, agent, RAG pipeline, or chatbot to Confident AI; configure the Confident AI OTLP endpoint; set confident.span.* or confident.trace.* attributes; export AI-app traces without the deepeval Python package; wire an OTLPSpanExporter, OpenTelemetry Collector, or vendor-neutral OTel SDK to Confident AI; or pick the US vs EU OTLP endpoint. Language-agnostic: the mechanism is OTLP attribute keys plus an exporter endpoint. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill); for instrumenting with the DeepEval SDK's @observe decorator or framework integrations (use the `deepeval-tracing` skill); or for non-AI software such as web servers, CRUD backends, or infrastructure: the confident.* attributes describe AI components 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。
Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangChain, OpenAI Agents, LlamaIndex, Pydantic AI, CrewAI, and others); choose between a native integration and manual instrumentation; set span types, tags, or metadata; or send DeepEval-SDK traces to Confident AI's Observatory. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill), or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill). This skill is purely DeepEval-SDK instrumentation — producing well-formed traces, not running evals.
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。