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Found 337 Skills
Qdrant vector database: collections, points, payload filtering, indexing, quantization, snapshots, and Docker/Kubernetes deployment.
Docusaurus build health validation and deployment safety for Claude Skills showcase. Pre-commit MDX validation (Liquid syntax, angle brackets, prop mismatches), pre-build link checking, post-build health reports. Activate on 'build errors', 'commit hooks', 'deployment safety', 'site health', 'MDX validation'. NOT for general DevOps (use deployment-engineer), Kubernetes/cloud infrastructure (use kubernetes-architect), runtime monitoring (use observability-engineer), or non-Docusaurus projects.
Generate professional draw.io architecture diagrams from text descriptions. The agent generates mxGraph XML directly, validates it, and iterates until correct. Includes 8900+ vendor stencils (AWS, Azure, GCP, Cisco, Kubernetes, etc.). Use when the user asks for draw.io diagrams, architecture diagrams, cloud infrastructure diagrams, or system design visualizations.
Guides developers through Enonic CLI commands for sandbox management, project scaffolding, local development, app deployment, and CI/CD pipeline generation. Use when creating Enonic XP sandboxes, starting or stopping local instances, scaffolding projects from starters, running dev mode with hot-reload, deploying apps, or generating CI/CD workflows for Enonic apps. Don't use for writing XP application code (controllers, content types), querying via Guillotine or lib-content APIs, configuring non-Enonic environments, or Docker/Kubernetes deployment of XP.
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.
Browser automation for Kubernetes dashboards and web UIs. Use when interacting with Kubernetes Dashboard, Grafana, ArgoCD UI, or other web interfaces. Requires MCP_BROWSER_ENABLED=true.
Production-grade Helm 4 chart development, release management, and debugging. This skill should be used when users ask to create Helm charts, deploy with Helm, manage releases (install/upgrade/rollback), push charts to OCI registries, debug failed deployments, configure chart dependencies, create umbrella charts, set up GitOps with ArgoCD/Flux, or troubleshoot Helm issues. Auto-detects from Dockerfile/code, generates production-hardened charts with library patterns. Complements kubernetes skill.
Apply and enforce cloud resource tagging strategies across AWS, Azure, GCP, and Kubernetes for cost allocation, ownership tracking, compliance, and automation. Use when implementing cloud governance, optimizing costs, or automating infrastructure management.
Terraform and OpenTofu infrastructure as code — module design, state management, multi-environment setups, remote backends, secrets management, CI/CD integration. NOT for Pulumi, CDK, Ansible, or Kubernetes manifests.
This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.
Provides comprehensive Google Cloud Platform (GCP) guidance including Compute Engine, Cloud Storage, Cloud SQL, BigQuery, GKE (Google Kubernetes Engine), Cloud Functions, Cloud Run, VPC networking, load balancing, IAM, Cloud Build, infrastructure as code (Terraform, Deployment Manager), security configuration, cost optimization, and multi-region deployment. Produces infrastructure code, deployment scripts, configuration guides, and architecture designs. Use when deploying to Google Cloud, designing GCP infrastructure, migrating to GCP, configuring GCE instances, setting up Cloud Storage, managing Cloud SQL databases, working with BigQuery, deploying to GKE, or when users mention "Google Cloud", "GCP", "Compute Engine", "Cloud Storage", "BigQuery", "GKE", "Cloud Run", "Cloud Functions", "VPC", "Cloud SQL", or "Google Cloud Platform".
Expert knowledge for Azure Virtual Machine Scale Sets development including troubleshooting, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring VMSS autoscale/upgrade modes, zones/PPGs, Spot+standby pools, ADE+Key Vault, or CLI/ARM deployments, and other Azure Virtual Machine Scale Sets related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Container Instances (use azure-container-instances), Azure App Service (use azure-app-service).