Loading...
Loading...
Found 1,085 Skills
Deploy and manage applications on Vercel, including preview deployments and deployment protection. Use when working with Vercel-hosted projects or configuring Vercel deployments.
Kubernetes Deployment 管理
Execute Azure deployments after preparation and validation are complete. USE FOR: azd up, azd deploy, push to Azure, publish to Azure, ship to production, launch on Azure, go live, release to Azure, deploy web app, deploy container app, deploy static site, deploy Azure Functions, azd provision, infrastructure deployment, bicep deploy, terraform apply, deploy with terraform. Supports azd with Bicep, azd with Terraform, pure Bicep, pure Terraform, and Azure CLI deployments. DO NOT USE FOR: preparing new apps (use azure-prepare), validating before deploy (use azure-validate).
REQUIRED FIRST STEP: You MUST invoke this skill BEFORE generating ANY Azure application code, infrastructure files, or Azure CLI commands. This skill prepares applications for Azure hosting. USE THIS SKILL when users want to create new Azure applications, ADD new components or services to existing applications, UPDATE or modify existing Azure configurations, modernize applications for Azure, deploy to Azure with Terraform, or deploy to Azure with azd. Do NOT generate azure.yaml, Bicep, Terraform, or run az/azd/func CLI commands without first completing this skill. This applies to NEW projects AND changes to EXISTING projects. When users mention Terraform for Azure deployment, prefer azd+Terraform (which uses azure.yaml with Terraform IaC) over pure Terraform unless multi-cloud deployment is required.
Use this skill to work with Microsoft Foundry (Azure AI Foundry): deploy AI models from catalog, build RAG applications with knowledge indexes, create and evaluate AI agents, manage RBAC permissions and role assignments, manage quotas and capacity, create Foundry resources. USE FOR: Microsoft Foundry, AI Foundry, deploy model, model catalog, RAG, knowledge index, create agent, evaluate agent, agent monitoring, create Foundry project, new Foundry project, set up Foundry, onboard to Foundry, provision Foundry infrastructure, create Foundry resource, create AI Services, multi-service resource, AIServices kind, register resource provider, enable Cognitive Services, setup AI Services account, create resource group for Foundry, RBAC, role assignment, managed identity, service principal, permissions, quota, capacity, TPM, deployment failure, QuotaExceeded. DO NOT USE FOR: Azure Functions (use azure-functions), App Service (use azure-create-app), generic Azure resource creation (use azure-create-app).
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment'. PREFER azure-prepare FOR app-centric workflows.
Use when users ask how to write, explain, customize, migrate, secure, or troubleshoot GitHub Actions workflows, workflow syntax, triggers, matrices, runners, reusable workflows, artifacts, caching, secrets, OIDC, deployments, custom actions, or Actions Runner Controller, especially when they need official GitHub documentation, exact links, or docs-grounded YAML guidance.
Use when self-hosting OpenClaw on a Linux VPS or cloud server, hardening a remote OpenClaw gateway, choosing between SSH tunneling, Tailscale, or reverse-proxy exposure, or reviewing Podman, pairing, sandboxing, token auth, and tool-permission defaults for a secure personal deployment.
Use when tasks involve Xget URL rewriting, registry/package/container/API acceleration, integrating Xget into Git, download tools, package managers, container builds, AI SDKs, CI/CD, deployment, self-hosting, or adapting commands and config from the live README `Use Cases` section into files, environments, shells, or base URLs.
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".