Provides AWS CloudFormation patterns for EC2 instances, Security Groups, IAM roles, and load balancers. Use when creating EC2 instances, SPOT instances, Security Groups, IAM roles for EC2, Application Load Balancers (ALB), Target Groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.
Provides AWS SAM bootstrap patterns: generates `template.yaml` and `samconfig.toml` for new projects via `sam init`, creates SAM templates for existing Lambda/CloudFormation code migration, validates build/package/deploy workflows, and configures local testing with `sam local invoke`. Use when the user asks about SAM projects, `sam init`, `sam deploy`, serverless deployments, or needs to bootstrap/migrate Lambda functions with SAM templates.
Guides migration of Terraform resources from Plugin SDK to Plugin Framework. Use when migrating SDK resources to PF, planning SDK-to-PF migrations, or when the user asks to migrate a resource to the Plugin Framework.
Infrastructure-as-Code operations: plan, apply, import, state management, module development, and drift detection using Terraform CLI.
Build reusable Terraform modules for AWS, Azure, and GCP infrastructure following infrastructure-as-code best practices. Use when creating infrastructure modules, standardizing cloud provisioning, or implementing reusable IaC components.
Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
"Comprehensive SAP Business Technology Platform (BTP) reference for cloud development, deployment, and operations. Use when setting up BTP accounts, working with Cloud Foundry environment, deploying to Kyma (Kubernetes, serverless), developing in ABAP environment (RAP, CDS), managing entitlements and quotas, configuring identity providers (XSUAA), using btp CLI or CF CLI, deploying multi-target applications (MTA), setting up connectivity (destinations, Cloud Connector), implementing CI/CD pipelines, extending SAP solutions, or troubleshooting BTP services. Covers all three runtime environments."
Access earth and environmental science datasets via PANGAEA API
Internal — for Boundless team members only. Deploy Boundless infrastructure to a new blockchain. Creates Pulumi stacks, config files, updates ChainId enum, and wires CI/CD pipelines for staging and prod environments. Use when adding a new chain, deploying to a new network, or setting up new chain infrastructure.
Creates Azure Architecture Decision Records with WAF mapping, alternatives, and consequences. USE FOR: ADR creation, architecture decisions, trade-off analysis, WAF pillar justification. DO NOT USE FOR: Bicep/Terraform code generation, diagram creation, cost estimates.
Discover existing Azure resources and bulk import them into Terraform management. USE FOR: import Azure resources, bring unmanaged infra under Terraform, audit Azure resources, migrate to IaC, terraform import, bulk import. WHEN: import existing resources, discover Azure infrastructure, adopt Terraform for existing resources, generate import blocks. DO NOT USE FOR: Bicep code, new resource creation, architecture decisions.
Shared IaC deploy patterns for Bicep and Terraform deploy agents: deployment strategies, circuit breaker, known deploy issues. For preflight validation (auth, governance, stop rules), see azure-validate. USE FOR: Phased deployment, circuit breaker, deploy-specific known issues. DO NOT USE FOR: Preflight validation (use azure-validate), code generation (use azure-bicep-patterns or terraform-patterns).
Deploy, evaluate, and manage Foundry agents end-to-end: Docker build, ACR push, hosted/prompt agent create, container start, batch eval, prompt optimization, agent.yaml, dataset curation from traces. USE FOR: deploy agent to Foundry, hosted agent, create agent, invoke agent, evaluate agent, run batch eval, optimize prompt, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, create dataset from traces, dataset versioning, eval trending, create AI Services, Cognitive Services, create Foundry resource, provision resource, knowledge index, agent monitoring, customize deployment, onboard, availability, standard agent setup, capability host. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics capabilities. Includes access tiers (hot, cool, archive) and lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, lifecycle management. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment.
Recommend Azure VM sizes, VM Scale Sets (VMSS), and configurations based on workload requirements, performance needs, and budget constraints. No Azure account required — uses public documentation and the Azure Retail Prices API. WHEN: recommend VM size, which VM should I use, choose Azure VM, VM for web/database/ML/batch/HPC, GPU VM, compare VM sizes, cheapest VM, best VM for workload, VM pricing, cost estimate, burstable/compute/memory/storage optimized VM, confidential computing, VM trade-offs, VM families, VMSS, scale set recommendation, autoscale VMs, load balanced VMs, VMSS vs VM, scale out, horizontal scaling, flexible orchestration.
Azure infrastructure defaults: regions, tags, naming (CAF), AVM-first policy, security baseline, unique suffix patterns. USE FOR: any agent generating or planning Azure resources. DO NOT USE FOR: artifact template structures (use azure-artifacts), pricing lookups (read references/pricing-guidance.md on demand).
Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.
Reusable Azure Terraform patterns: hub-spoke, private endpoints, diagnostics, AVM-TF modules. USE FOR: Terraform template design, hub-spoke networking, AVM modules, plan interpretation. DO NOT USE FOR: Bicep code, architecture decisions, troubleshooting, diagram generation.
Prepare Azure apps for deployment (infra Bicep/Terraform, azure.yaml, Dockerfiles). Use for create/modernize or create+deploy; not cross-cloud migration (use azure-cloud-migrate). WHEN: "create app", "build web app", "create API", "create serverless HTTP API", "create frontend", "create back end", "build a service", "modernize application", "update application", "add authentication", "add caching", "host on Azure", "create and deploy", "deploy to Azure", "deploy to Azure using Terraform", "deploy to Azure App Service", "deploy to Azure App Service using Terraform", "deploy to Azure Container Apps", "deploy to Azure Container Apps using Terraform", "generate Terraform", "generate Bicep", "function app", "timer trigger", "service bus trigger", "event-driven function", "containerized Node.js app", "social media app", "static portfolio website", "todo list with frontend and API", "prepare my Azure application to use Key Vault", "managed identity".
Create agent skills for Microsoft technologies using Learn MCP tools. USE FOR: generating skills that teach agents about Azure services, .NET libraries, Microsoft 365 APIs, VS Code extensions, Bicep modules, or any Microsoft technology. DO NOT USE FOR: general skill scaffolding without Microsoft tech focus (use make-skill-template), Azure infrastructure deployment, Bicep/Terraform code generation.
Assess and migrate cross-cloud workloads to Azure. Generates assessment reports and converts code from AWS, GCP, or other providers to Azure services. WHEN: migrate Lambda to Azure Functions, migrate AWS to Azure, Lambda migration assessment, convert AWS serverless to Azure, migration readiness report, migrate from AWS, migrate from GCP, cross-cloud migration.
Reusable Azure Bicep patterns: hub-spoke, private endpoints, diagnostics, AVM composition. USE FOR: Bicep template design, hub-spoke networking, private endpoint patterns, AVM modules. DO NOT USE FOR: Terraform code, architecture decisions, troubleshooting, diagram generation.
Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.
