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Found 33 Skills
Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.
Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.
Deploy containerised applications to Google Cloud Run from source using gcloud CLI. Use when the user asks to "deploy to GCP", "deploy to Cloud Run", "ship to Google Cloud", "gcloud run deploy", or needs to set up, redeploy, configure env vars/secrets, view logs, or troubleshoot a Cloud Run service.
Manages Google Cloud Pub/Sub topics, subscriptions, schemas, and messages safely and efficiently. Use when building or managing event-driven, decoupled systems, streaming data pipelines, or integrating push/pull asynchronous message consumers. Don't use when writing or debugging Google Cloud client library code or raw REST/gRPC API interactions directly.
Fetches raw IAM recommendations and associated security insights from Google Cloud for a specified target scope (Organization, Folder, or Project). Use when you need to retrieve security recommendations before analyzing or applying them. Don't use for applying/acting on recommendations (use the recommendation applier skill) or for general allow policy querying (use the allow policy viewer skill).
Inspects Google Cloud Filestore capacity and utilization, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds, or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.
Google Cloud Platform CLI - manage GCP resources including Compute Engine, Cloud Run, GKE, Cloud Functions, Storage, BigQuery, and more.
Expert-level Google Cloud Platform, services, and cloud architecture
Interacts with Google Cloud services using the gcloud CLI safely and efficiently. Covers command validation, data reduction, safety guardrails with a denylist, and workflows for discovery and investigation. You MUST read this skill before invoking any gcloud command. Use when managing cloud resources, querying configurations, or troubleshooting issues via gcloud. Don't use when writing or debugging Google Cloud client library code or raw REST/gRPC API interactions.
Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for Bigtable, or diagnosing performance/hotspotting issues. Also use when provisioning Bigtable clusters using gcloud or cbt CLIs. Don't use for generic Cloud SQL administration.
Deploy containerized applications on Google Cloud Run with automatic scaling, traffic management, and service mesh integration. Use for container-based serverless computing.
Guides agents through a structured 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to opinionated best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage buckets, Compute Engine MIGs, GKE, Cloud Run) to use as load balancer backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancer configurations. - Actuating deployments via Infrastructure Manager or bash scripts, including performing IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).