Google Cloud Skills skills

Guides developers through downloading, configuring, and installing the official open-source Google Ads MCP Server. Use this skill when a user wants to connect their AI assistant (such as Gemini, Claude Code, or Cursor) to their Google Ads account to query campaigns or retrieve reporting metrics using natural language.

Assists in provisioning instances and databases, designing performant schemas, and querying data in Cloud Spanner on Google Cloud. Use when designing primary keys, writing SQL queries or client library code, or diagnosing performance issues.

Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (`audit_cluster.sh`), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (`gVisor`), enforcing Pod Security Standards (`restricted` labeling) and pod securityContext, and mounting Secret Manager secrets via CSI (`SecretProviderClass`). Use when auditing workload security posture, isolating namespaces, applying pod security standards, or configuring network policies and secret volume mounts. Don't use for Workload Identity (use gke-workload-identity), cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead).

Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).

Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool upgrade strategies (surge, blue-green), version compatibility, PDB management, and workload-specific concerns (stateful, GPU, operators). Use this skill whenever the user mentions GKE upgrades, Kubernetes version bumps, node pool maintenance, GKE patching, cluster version management, release channel selection, maintenance windows, surge upgrades, stuck upgrades, or any GKE lifecycle management task — even casual mentions like "we need to upgrade our clusters" or "plan our next GKE maintenance" or "our upgrade is stuck." Don't use for GKE cluster creation, application onboarding, general networking/routing setup, or security policy configurations (use gke-basics or relevant GK

Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs, NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics.

Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.

Manages Google Analytics account and property settings, enables the Analytics Admin API via the Cloud CLI, lists accounts and properties, and manages data streams, custom dimensions, conversion events, and integrations. Use when you need to programmatically configure Google Analytics accounts, provision properties, manage data retention, configure Measurement Protocol secrets, or manage Firebase and Google Ads links.

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.

Creates Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.

Provides foundational Firebase CLI setup, CLI installation, version checks (`firebase-tools@latest --version`), CLI login (including --no-localhost), project creation, project selection (`firebase use`), and app config file downloads (`google-services.json`, `GoogleService-Info.plist`). Use ONLY for CLI login, project creation/switching, or downloading app config files. Don't use for Firebase Hosting deploy, Firestore, Auth, App Hosting, Data Connect, Crashlytics, or Remote Config.

Answer natural language questions and perform analysis on GKE cluster and workload costs using BigQuery billing exports, cost allocation data, and live cluster monitoring metrics. Use when querying GKE costs across projects, namespaces, or workloads, analyzing billing reports in BigQuery (`bq`), checking cluster cost budgets (`gcloud billing`), or diagnosing cost drivers like pod requests vs. actual utilization (`kubectl top`). Don't use for applying cost optimization changes, creating rightsizing manifests (VPA/MPA), or selecting ComputeClasses (use gke-cost-optimization instead).

Provides guidance for migrating Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers migration to Airflow 2.11.1 (MSAA Gen 2 and 3) and Airflow 3 (MSAA Gen 3), including environment inspection, GCS download/upload and scanning patterns for breaking changes. Use when migrating the DAG code to newer Airflow version. Don't use when checking DAG run failures unrelated to code migration.

Inspects, searches, and reads files and POSIX metadata on Filestore (NFS) instances on Google Cloud without local NFS client packages or root privileges. Use when browsing Filestore shares, searching files, reading remote logs, or inspecting file attributes; don't use for Cloud Storage buckets, Cloud NetApp Volumes, Persistent Disks, or modifying/deleting files.

Diagnoses GKE persistent-storage failures — volume attach/mount errors (Regional PD on optimized VMs, fsGroup mount timeouts), disk-performance and node storage-pressure issues, slow-disk Pod-creation failures, volume-expansion problems, Local SSD / Hyperdisk Storage Pool creation errors, and Cloud Storage FUSE OOM. Use when Pods are stuck in ContainerCreating, volumes fail to attach or mount, or nodes report storage pressure. Don't use for routine storage provisioning or StorageClass/PVC authoring (see the gke-storage skill).

Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't use for general non-TPU GKE workload monitoring or non-metric TPU debugging.

Provides guidance for authoring Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers environment context discovery, Airflow 2 vs 3 compatibility, authoring best practices, and local/remote validation processes. Use when creating or extending an Airflow DAG. Don't use when authoring Python code unrelated to Airflow DAGs.

Manages the end-to-end lifecycle of on-demand, temporary access using Privileged Access Manager (PAM). Use when a user asks to create, read, update, or delete PAM entitlements, request temporary access, or approve/deny pending PAM grants. Do NOT use for permanent IAM policy bindings, troubleshooting IAM permission errors, or general Google Cloud resource provisioning.

Authors custom cloud controls and customized frameworks for Assured Workloads when built-in resources cannot satisfy core requirements. Use when creating or synthesizing custom data boundary resources. Don't use for browsing or mapping existing built-in frameworks (use assuredworkloads-frameworks-navigator instead).

Validates a project's Google Mobile Ads (GMA) SDK integration for iOS, Android, or Unity projects. Use when conducting a full pre-launch audit of an app that integrates GMA SDK or when validating any individual GMA SDK integration checks, such as when validating ad unit IDs and ad formats, SKAdNetwork IDs, mediation adapter SDK version compatibility, or ad preloading.

Inspects Filestore capacity and utilization on Google Cloud, 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 (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.

Designs a tailored multi-product agentic data science architecture on Google Cloud that incorporates opinionated best practices. Use when architecting multi-product solutions for agent-based data analytics or ML workloads. Don't use for simple queries, non-agentic pipelines, general cloud reviews, or writing agent code.

Discovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.

Implement and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com/token. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM / service account authentication.