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Found 1,211 Skills
Expert knowledge for Azure Lab Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring lab plans, VM templates/schedules, VNet-integrated labs, GPU/nested virtualization, or Canvas/Teams integration, and other Azure Lab Services related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).
Deploy OpenClaw AI agent platform on Alibaba Cloud ECS and integrate with DingTalk bot. OpenClaw (formerly Clawdbot/Moltbot, 中文名"龙虾") is an open-source AI assistant and automation platform supporting natural language-driven task automation with multi-channel chat integration. This Skill covers the full workflow from ECS instance creation, public network configuration, base environment setup, one-click OpenClaw deployment to DingTalk bot verification. End users can chat with the AI assistant by @mentioning the bot in a DingTalk group. Triggers: "OpenClaw", "龙虾", "Clawdbot", "Moltbot", "DingTalk bot", "DingTalk AI", "deploy OpenClaw on ECS", "AI agent platform", "DingTalk integration", "openclaw dingtalk", "openclaw deploy", "DingTalk AI employee", "Alibaba Cloud OpenClaw", "Bailian + DingTalk", "DingTalk group AI", "DingTalk smart assistant", "部署龙虾", "龙虾机器人", "龙虾钉钉"
Generate enterprise-grade documentation for NetSuite SDF projects. Analyze scripts, object XML files, `manifest.xml`, and SuiteQL queries to produce README.md, architecture diagrams (Mermaid/ASCII), deployment guides, and troubleshooting tables. Can integrate with post-deployment documentation workflows when automation (for example, hooks) is available.
Automates declarative resource creation and provisioning for data pipelines, supporting BigQuery, Dataform, Dataproc, BigQuery Data Transfer Service (DTS), and other resources. It manages environment-specific configurations (dev, staging, prod) through a deployment.yaml file. Use when: - Modifying or creating deployment.yaml for deployment settings. - Resolving environment-specific variables (e.g., Project IDs, Regions) for deployment. - Provisioning supported infrastructure like BigQuery datasets/tables, Dataform resources, or DTS resources via deployment.yaml. Do not use when: - Resources already exist. - Managing resources not supported by `gcloud beta orchestration-pipelines resource-types list`. - Managing general cloud infrastructure (VMs, networks, Kubernetes, IAM policies), which are better suited for Terraform. - Infrastructure spans multiple cloud providers (AWS, Azure, etc.). - Already uses Terraform for the target resources.
Deploy telecine services to GCP Cloud Run via Pulumi, publish elements packages to npm, publish skills docs, rollback, scale resources, manage secrets, and debug failed deployments.
Use this skill first for any SpacetimeDB task; it routes to focused skills for modules, tables, reducers, procedures, views, clients, subscriptions, CLI commands, auth, RLS, HTTP APIs, SQL, deployment, serialization, tutorials, quickstarts, and upgrades. Triggers on: spacetime, spacetimedb, SpacetimeDB, stdb, module, reducer, table, procedure, view, subscription, DbConnection, spacetime generate, spacetime publish, spacetime sql, BSATN, SATS, row-level security, RLS, Maincloud, standalone, Unity, Unreal.
Generate Harness Environment YAML for deployment targets and create via MCP. Supports PreProduction and Production types with environment variables, manifest overrides, and multi-environment setup (dev, staging, prod). Use when asked to create an environment, set up staging, configure production, define deployment targets, or manage environment overrides. Trigger phrases: create environment, deployment environment, setup dev, setup staging, setup production, environment variables, environment overrides.
Best practices for writing reliable Pulumi programs. Covers Output handling, resource dependencies, component structure, secrets management, safe refactoring with aliases, and deployment workflows.
Comprehensive CI/CD pipeline patterns skill covering GitHub Actions, workflows, automation, testing, deployment strategies, and release management for modern software delivery
Unified deployment for multiple platforms. Supports Railway, Cloudflare Pages, and Cloudflare Workers. Use when user says "/deploy", "배포", "deploy all", "railway 배포", "cloudflare 배포", or any deployment-related request. Supports selective deployment targets.
Production readiness checklist covering domains, SEO, security, and deployment. Use when asked to "ship it", "deploy to production", "go live", "launch", or when preparing a project for production deployment.
Scaffold and deploy Cloudflare Workers with Hono routing, Vite plugin, and Static Assets. Workflow: describe project, scaffold structure, configure bindings, deploy. Use when creating Workers projects, setting up Hono/Vite, configuring D1/R2/KV bindings, or troubleshooting export syntax errors, API route conflicts, HMR issues, or deployment failures.