「deploy」の検索結果

Use when asked to deploy, release, publish, or ship OpenMeld to production — workers, Web, CLI, or local components. Routes to the guarded release lanes; never deploy raw.

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。

Explicit landing-page build and deploy operator. Loads marketing and frontend judgment, scaffolds the smallest suitable site, verifies it rendered, deploys to the configured target.

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。

INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.

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。

Runs the Fabric Git integration lifecycle through fab api or az rest, including connecting a workspace to Azure DevOps or GitHub, committing, updating from Git, reading sync status, resolving conflicts, disconnecting a connected workspace, and automating sync with a service principal. For stage promotion use deployment-pipelines-authoring-cli. Branch switching, fab deploy, fabric-cicd and cross-workspace rebinding are out of scope.

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 Viking web projects, start and verify a local preview, or deploy a generated project to Volcengine IGA Pages when explicitly requested. Includes agent-guided feature, eligible application, dataset, scene, and authentication choices. Use only after confirming the installed CLI exposes `vs project`; otherwise stop without taking action.

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。

This skill should be used when the user asks to "create openship.json", "configure an OpenShip deployment", "make a repo deployable on OpenShip", or fix "openship config validate" errors.

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, migrate, and deploy Next.js apps on Cloudflare Workers with vinext. Use when starting a Next.js project on Cloudflare, moving an existing app to Workers, choosing between vinext and OpenNext, or setting up vinext for Workers. For setup, migration, or deployment, install vinext's upstream skills with `npx skills add cloudflare/vinext` if missing, then read and follow the applicable skill and docs.

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。

This skill should be used when user asks to "deploy to Hetzner", "create Hetzner server", "manage Hetzner Cloud", "hcloud CLI", or works with Hetzner Cloud infrastructure including servers, networks, firewalls, load balancers, DNS zones, and volumes.

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。

Runs LiveKit agent simulations and acts on the results. Use when the user says "run my simulations", "regression test my agent before deploying", "run the scenarios", "use lk agent simulate", "did my agent pass", "why did this scenario fail", "run simulations in CI", "test the audio pipeline", "check turn-taking and interruptions", or wants to check whole-conversation behavior before shipping. Covers text and audio mode and what each catches, running against a local or deployed agent, degraded-audio flags, automating a pre-release run, and triaging failures with list, view and export. For writing the scenarios use writing-livekit-scenarios. Not the default for a bare "test my agent", which goes to debugging-livekit-agents. Use this skill when the user names simulations, scenarios, a run, CI, or shipping.

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 machine vision inspection systems with MATLAB Visual Inspection Toolbox. Covers the full arc from problem selection through deployment: anomaly detection (Student-Teacher, PatchCore, FastFlow, FCDD), object detection (YOLOX), counting (CounTR, shape matching), gauging and measurement (caliper, fitcircle, fitangle), blob analysis (regionprops, calibrated measurement), shape matching for fixturing and localization, synthetic data generation for training augmentation, and deployment to standalone apps, embedded C/C++, NVIDIA GPUs (TensorRT), NPUs (ONNX), and Beckhoff PLCs. Routes to rule-based tools when problems are geometric and deterministic, AI-based tools when defect appearance varies, and hybrid pipelines combining both.

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 MATLAB-generated code to embedded hardware using Embedded Coder. Use when configuring code generation for microcontrollers (STM32, Raspberry Pi, ARM Cortex), setting up PIL/SIL verification, disabling dynamic memory allocation, or configuring hardware-specific code generation settings. Covers ERT-based configurations, processor-in-the-loop testing, memory constraints, and the MEX→SIL→PIL verification progression.

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 C/C++ or CUDA code from an AI model (PyTorch, LiteRT) using MATLAB Coder or GPU Coder. Use when the user wants to integrate an AI model into an application with code generation as the end goal — generating MEX, CUDA MEX, static library, dynamic library, or executable — or using the model in Simulink for simulation and code generation. Covers PyTorch ExportedProgram (.pt2) via loadPyTorchExportedProgram and LiteRT (.tflite) via loadLiteRTModel (R2026a+). Keywords: PyTorch, torch, .pt2, ExportedProgram, loadPyTorchExportedProgram, invoke, codegen, MEX, CUDA, GPU, C, C++, deploy, AI model, deep learning model, LiteRT, TFLite, TensorFlow Lite, Simulink, slbuild, PyTorch ExportedProgram block, MATLAB Function block, dlosslib, loadLiteRTModel.

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。

AWS CloudFormation infrastructure as code for stack management. Use when writing templates, deploying stacks, managing drift, troubleshooting deployments, or organizing infrastructure with nested stacks.

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 frontend and full-stack apps on Vercel with previews, edge functions, environment promotion, and production guardrails. Use when shipping Next.js, SvelteKit, or static sites with zero-config CI/CD.

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 ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server. Includes canary deployments, autoscaling, model versioning, A/B testing, and GPU resource management for production model serving.

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。

Manage Red Hat OpenShift clusters and deployments. Configure projects, routes, builds, and deploy applications using OpenShift-specific features. Use when working with OpenShift Container Platform or OKD for enterprise Kubernetes.

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 AWS resources with CloudFormation templates. Create stacks, use nested stacks, and implement drift detection. Use when deploying AWS-native IaC.

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 serverless functions on Google Cloud Functions. Configure triggers and manage deployments. Use when implementing serverless workloads on 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。

Build, test, and deploy applications using GitHub Actions workflows. Create CI/CD pipelines, configure runners, manage secrets, and automate software delivery. Use when working with GitHub repositories, automating builds, running tests, or deploying applications.

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, manage, and deploy Helm charts for Kubernetes package management. Build reusable chart templates, manage releases, configure values, and use Helm repositories. Use when packaging Kubernetes applications or managing K8s deployments with Helm.

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 deploy AI agents with CloudBase Agent SDK (TypeScript & Python). Implements the AG-UI protocol for streaming agent-UI communication. Use when deploying agent servers, using LangGraph/LangChain/CrewAI adapters, building custom adapters, understanding AG-UI protocol events, or building web/mini-program UI clients. Supports both TypeScript (@cloudbase/agent-server) and Python (cloudbase-agent-server via FastAPI).

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 wants to develop, run, preview, save, deploy, or roll back a CloudBase Web app in this conversation as a Lovable/Codex-Sites-like vibe- coding session — i.e. any request that maps to "spin up a React+Vite project, see it live in the browser, iterate, save versions, deploy". Activate ONLY for browser-rendered Web projects based on the CloudBase official React (or Vue) + Vite template. Do NOT activate for: WeChat/Alipay mini-program, React Native / Flutter / Electron, pure cloud functions / CloudRun backends, or Next.js / Nuxt / Astro / Remix / SvelteKit (those frameworks are explicitly out of scope).

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。

CloudBase CLI (tcb, 云开发CLI, Tencent CloudBase命令行) resource management skill. Use when deploying cloud functions, CloudRun, storage, NoSQL/MySQL, static hosting, permissions, CORS/domains via tcb; for CI/CD and batch ops; when the user prefers CLI; or as the first-session fallback when CloudBase MCP tools are not loaded yet (after install/config, before IDE restart). Covers tcb login (device code for Tencent Cloud accounts; --cloudbase-api-key -e for environment API Key without an account; --apiKeyId/--apiKey for CI) and domain commands (fn/hosting/cloudrun/…) as MCP auth/manage parity — do not default to tcb deploy.

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 MCP servers in Python with FastMCP. Define tools / resources / prompts, build the server, test locally, deploy to FastMCP Cloud or Docker. Use whenever the user mentions building an MCP server, exposing tools to LLMs, FastMCP, building a Claude integration, or troubleshooting FastMCP module-level server, storage, lifespan, middleware, OAuth, or deployment errors.

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。