VerifiedPlugin
Development
google-agents-cli
The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.
7 skills
@googleDevelopment
Plugin
google-skills
This repository contains Agent Skills for Google products and technologies, including Google Cloud. This repository is under active development.
Plugin Signal92/100Strong
maintained99
capable97
documented75
adopted90
Install on Claude Code
> /plugin marketplace add google/skills
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Python
Language
Apache-2.0
License
2d ago
Last commit
4mo ago
Created
Repo: google/skills
In this plugin
- data-manager-api-audience-ingestion
- data-manager-api-event-ingestion
- data-manager-api-setup
- google-ads-api-account-diagnostics
- google-ads-api-mcp-setup
- google-ads-api-quickstart
- google-mobile-ads-android-migrate-to-next-gen
- google-mobile-ads-banner
- google-mobile-ads-get-started
- google-mobile-ads-interstitial
- google-mobile-ads-rewarded
- ima-sdk-basics
- google-analytics-admin-api-basics
- google-analytics-data-api-basics
- agent-platform-alert-configuration
- agent-platform-deploy
- agent-platform-endpoint-management
- agent-platform-eval-flywheel
- agent-platform-inference
- agent-platform-migrate-from-ai-studio
- agent-platform-model-registry
- agent-platform-prompt-management
- agent-platform-rag-engine-management
- agent-platform-skill-registry
- agent-platform-troubleshooting
- agent-platform-tuning-management
- agent-platform-tuning
- alloydb-basics
- bigquery-ai-ml
- bigquery-basics
- bigquery-bigframes
- bigtable-basics
- cloud-logging-configuration-basics
- cloud-logging-cross-project-configuration
- cloud-logging-query-generation
- cloud-monitoring-chart-generation
- cloud-monitoring-metric-selection
- cloud-run-basics
- cloud-sql-basics
- datalineage-bigquery-asset-impact-analysis
- datalineage-summary
- detection-engineering-coverage-evaluation
- developer-device-platform-basics
- firebase-basics
- gcloud
- gemini-agents-api
- gemini-api
- gemini-interactions-api
- gemini-live-api
- gke-ai-troubleshooting-handle-disruption-gpu-tpu
- gke-ai-troubleshooting-jobset-interruption
- gke-ai-troubleshooting-tpu-vbar-oom
- gke-app-onboarding
- gke-backup-dr
- gke-basics
- gke-batch-hpc
- gke-cluster-autoscaler
- gke-cluster-creation
- gke-compute-classes
- gke-cost-analysis
- gke-cost-optimization
- gke-golden-path
- gke-inference
- gke-manifest-generation
- gke-multitenancy
- gke-networking
- gke-observability
- gke-platform-security
- gke-productionize
- gke-reliability
- gke-service-networking
- gke-storage
- gke-tpu-dynamic-slices-monitoring
- gke-tpu-metrics-monitoring
- gke-upgrades
- gke-workload-scaling
- gke-workload-security
- gke-workload-troubleshooting
- google-agents-cli-onboarding
- google-cloud-global-frontend-configuration
- google-cloud-networking-observability
- google-cloud-recipe-auth
- google-cloud-recipe-foundation-builder
- google-cloud-recipe-onboarding
- google-cloud-slo-alert-configuration
- google-cloud-solution-agentic-ai-bidirectional-streaming
- google-cloud-solution-agentic-ai-borderless-data-lakehouse
- google-cloud-solution-agentic-ai-data-science-workflow
- google-cloud-solution-agentic-analytics-spark-knowledge-catalog
- google-cloud-solution-architecture
- google-cloud-solution-build-deploy-agents
- google-cloud-solution-guided-gke-ai-migration
- google-cloud-solution-n-tier-serverless-web-app
- google-cloud-solution-rag-enterprise-search-gke-sqldb
- google-cloud-storage-basics
- google-cloud-waf-cost-optimization
- google-cloud-waf-operational-excellence
- google-cloud-waf-performance-optimization
- google-cloud-waf-reliability
- google-cloud-waf-security
- google-cloud-waf-sustainability
- managed-airflow-migrations
- spanner-basics
- workload-manager-basics
What's inside
Skills
104/data-manager-api-audience-ingestionGuides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an/data-manager-api-event-ingestionGuides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads,/data-manager-api-setupGuides developers through client library installation and authentication setup steps for the Data Manager API. Use this skill when a user is getting started with the Data Manager API and needs to setup their local environment, install the client library, or setup access to the/google-ads-api-account-diagnosticsDiagnoses Google Ads account performance issues such as conversion loss (value or volume), low lead flow/volume, and lost impression share (opportunities) due to ad rank, bids, or budgets. Use when troubleshooting sudden performance drops, analyzing campaign impression share/google-ads-api-mcp-setupGuides 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/google-ads-api-quickstartGuides developers through Google Ads API quickstart: credential setup, choosing from 6 client libraries/REST, configuring environments, and running a "retrieve campaigns" script. Troubleshoots common setup errors: USER_PERMISSION_DENIED, login_customer_id issues, and
Show all 104 skillsShow fewer
/google-mobile-ads-android-migrate-to-next-genMigrates Android applications from the old, legacy Google Mobile/google-mobile-ads-bannerProvides instructions to implement, integrate, or configure Google Mobile Ads (GMA) banner ads in Android, iOS, or Unity mobile applications. Use when the task involves setting up banner ads in a mobile application. Don't use for other ad formats like interstitial or rewarded/google-mobile-ads-get-startedProvides instructions for integrating the Google Mobile Ads (GMA)/google-mobile-ads-interstitialProvides instructions for implementing, integrating, or configuring/google-mobile-ads-rewardedProvides instructions for implementing, integrating, or configuring/ima-sdk-basicsUse this skill for Interactive Media Ads (IMA) SDK client-side ad insertion when you are requesting video ads client-side into websites, apps, TVs or other platforms with VAST or VMAP. Do not use for Dynamic Ad Insertion (DAI), SSAI, or SGAI (use the `ima-sdk-dai-basics` skill/google-analytics-admin-api-basicsManages 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/google-analytics-data-api-basicsManages Google Analytics reporting data, enables the Analytics Data API via the Cloud CLI, and creates reports using the Google Analytics Data API (v1beta). Use when you need to interact with Google Analytics properties, run customized analytics reports, query metrics (like/agent-platform-alert-configurationConfigures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. NOTE: Reliability, Cost, Safety, and Security alerts/agent-platform-deployDeploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden/agent-platform-endpoint-managementManages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to/agent-platform-eval-flywheelMeasures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a/agent-platform-inferenceConnects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when you need to generate code for calling Gemini or OpenMaaS models, authenticate with GenAI/agent-platform-migrate-from-ai-studioGuides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI). Use this skill when moving applications to Google Cloud, to leverage Cloud credits, or to unify inferencing with other Cloud infrastructure/agent-platform-model-registryAgent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform/agent-platform-prompt-managementManages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts./agent-platform-rag-engine-managementManage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries/agent-platform-skill-registryInteract with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities./agent-platform-troubleshootingTroubleshoots Google Cloud Gemini Enterprise Agent Platform issues (Agent Gateway, Registry, Identity, Policies, Model Armor, Identity-Aware Proxy (IAP)). Use when agent requests fail with 403 (especially unauthorized egress), Agent Runtime queries return 500, or gateway/IAP/agent-platform-tuning-managementManages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use `agent-platform-tuning`), deploying models to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use/agent-platform-tuningAgent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use/alloydb-basicsManages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances/bigquery-ai-mlLeverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector/bigquery-basicsManages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis./bigquery-bigframesGenerates Python code using BigQuery DataFrames (BigFrames), the pandas/scikit-learn-style API over BigQuery. Use when writing BigFrames code or doing pandas-style dataframe/ML work against BigQuery (e.g. in a notebook). Don't use for SQL-first workflows or the/bigtable-basicsAssists 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/cloud-logging-configuration-basicsConfigure single-project Google Cloud Logging: regional log buckets, log sinks, log views, restricting or hiding sensitive logs in the default view (_Default) filter, IAM permissions for views (Logs View Accessor, IAM conditions), logs-based metrics, log exclusions, and/cloud-logging-cross-project-configurationConfigure and troubleshoot Google Cloud cross-project centralized logging and read-time aggregation. Use when: - Setting up log routing from multiple projects/folders/organizations to a central log bucket. - Creating cross-project log sinks and configuring central log buckets. -/cloud-logging-query-generationGenerates Logging Query Language (LQL) queries for Google Cloud Logging from natural language. Use this skill when you need to query log data or when you are debugging issues. You can filter log data by Google Cloud service. Don't use this skill to query other databases, such as/cloud-monitoring-chart-generationGenerates 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/cloud-monitoring-metric-selectionRetrieve, query, and identify relevant Google Cloud Monitoring metric descriptors for a GCP service or resource (such as Compute Engine, Spanner, BigQuery, Cloud Run, Cloud SQL, Pub/Sub, Cloud Storage, etc.). Use when asked to find, list, search, or discover GCP metric types,/cloud-run-basicsManages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools)./cloud-sql-basicsThis file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For/datalineage-bigquery-asset-impact-analysisAnalyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. -/datalineage-summarySummarizes Google Cloud Data Lineage graphs to help users debug data quality issues and understand data provenance for BQ/GCS. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic/detection-engineering-coverage-evaluationAutomates the end-to-end detection engineering workflow in Google SecOps using MCP tools. Use when fetching threat intelligence from blogs, generating Threat Detection Opportunities (TDOs), simulating attacker behavior with synthetic UDM events, evaluating rule coverage,/developer-device-platform-basicsProvides guidance and instructions on managing remote devices on Developer Device Platform (DDP). Use when reserving remote Android devices, establishing connection tunnels, checking session status, or extending/cancelling leases. Don't use for iOS or local device/hardware/firebase-basicsProvides 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`,/gcloudProvides safety-critical validation, guardrails, and data reduction for gcloud CLI operations across Google Cloud Platform (GCP) services and infrastructure. Use when planning, generating, constructing, proposing, describing, or executing any gcloud CLI commands - including when/gemini-agents-apiManages custom Agent resources on Gemini Enterprise Agent Platform. Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations./gemini-apiUse when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities/gemini-interactions-apiGuides the usage of Gemini Interactions API on Gemini Enterprise Agent Platform. Use when the user wants to use the stateful, server-managed Interactions API for multi-turn conversations, background execution, streaming, structured output, and function calling on the Agent/gemini-live-apiGenerates a Gemini LiveAPI client service class in the user's chosen programming language. Use when the user wants to build, scaffold, or integrate a client that connects to the Gemini Enterprise LiveAPI websocket endpoint, handles session setup/resumption, bearer token refresh,/gke-ai-troubleshooting-handle-disruption-gpu-tpuDiagnoses, predicts, and mitigates node disruptions during Compute Engine host maintenance and hardware or software maintenance events for GPU and TPU workloads on GKE. Use when diagnosing node disruptions, predicting host maintenance events on GPU/TPU nodepools, inspecting node/gke-ai-troubleshooting-jobset-interruptionDiagnoses GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster/gke-ai-troubleshooting-tpu-vbar-oomDiagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent/gke-app-onboardingManages GKE application onboarding, covering containerization, deployment manifests, and migration. Use when onboarding or deploying an application to GKE for the first time, or containerizing an app for GKE. Don't use for general GKE cluster administration or upgrades (use/gke-backup-drConfigures GKE Backup Plans and restore workflows. Use for backup policies, disaster recovery, or GKE cluster restores. Don't use for database backups./gke-basicsManages core GKE cluster provisioning, credentials, Autopilot vs Standard selection, and workload deployment. Use when creating GKE clusters, fetching kubectl credentials, configuring Workload Identity, or deciding between Autopilot and Standard modes. Don't use for specialized/gke-batch-hpcRuns batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding instead)./gke-cluster-autoscalerTrigger on mention of GKE cluster autoscaler, node autoscaling, node pool auto-creation / node auto-provisioning. Provides guidance on enabling and optimizing cluster autoscaler, best practices, and troubleshooting issues such as nodes not scaling up or down, zonal stockouts, or/gke-cluster-creationPlans and executes GKE cluster creation, provisioning, and production readiness audits using pre-defined templates (Autopilot, Standard Regional, GPU/AI Inference, AI Hypercompute). Use when creating GKE clusters, provisioning GKE environments, selecting cluster modes, or/gke-compute-classesConfigures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do/gke-cost-analysisAnswer 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/gke-cost-optimizationOptimizes GKE costs, rightsizes workloads, and configures Spot VMs, CUDs, cost allocation, and resource quotas. Use when optimizing GKE cluster or workload costs, configuring GKE cost allocation or quotas, rightsizing CPU/memory requests, or selecting Spot VMs and machine types./gke-golden-pathProvides GKE golden path configuration defaults, production readiness checklists, and cluster default patterns. Use when designing GKE clusters, verifying GKE production readiness, or checking configurations against GKE defaults. Don't use for setting up workload autoscaling/gke-inferenceDeploys and optimizes AI/ML inference workloads on GKE, using GPUs, TPUs, and model servers. Use when deploying GKE inference servers, configuring GKE GPU resources for inference, or deploying LLMs on GKE. Don't use for generic batch jobs or HPC task queues (use gke-batch-hpc/gke-manifest-generationGenerates 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/gke-multitenancyPlans and configures multi-tenancy on GKE. Covers namespace isolation, RBAC planning for teams, resource quotas, LimitRanges, network isolation, and cost allocation. Use when designing GKE multi-tenancy, configuring GKE namespaces, setting up resource quotas, or isolating GKE/gke-networkingPlans, configures, and manages core GKE cluster networking. Covers private clusters, VPC-native configurations, DNS, node egress, Dataplane V2, and IP planning. Use when designing GKE networking layouts, configuring private clusters, setting up Dataplane V2, planning GKE IP/gke-observabilityConfigures GKE observability, including Cloud Logging, Cloud Monitoring, and managed Prometheus. Use when configuring GKE monitoring, setting up GKE logging, or configuring Prometheus metrics collection. Don't use to configure local application logging frameworks or external/gke-platform-securityPlans, configures, and hardens platform-level Google Kubernetes Engine (GKE) cluster security. Covers cluster add-ons (Secret Manager enablement), RBAC hardening (disabling insecure bindings, audit tools), Binary Authorization, enabling Shielded Nodes, GKE Sandbox cluster/gke-productionizeOrchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or/gke-reliabilityImproves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster/gke-service-networkingConfigures GKE edge networking, traffic routing, load balancing, and private service endpoints. Use when configuring Gateway API manifests, standard Ingress, Cloud Armor WAF security policies, Container-Native Load Balancing (NEGs), Private Service Connect (PSC), or/gke-storageManages GKE storage, including PVCs, PersistentVolumes, Filestore, and GCS FUSE. Use when configuring GKE storage, creating PVCs, or setting up GCS FUSE on GKE. Don't use for database administration or replication strategies outside volume provisioning context./gke-tpu-dynamic-slices-monitoringMonitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and/gke-tpu-metrics-monitoringMonitors 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/gke-upgradesPlans, 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/gke-workload-scalingManages scaling for GKE workloads using HPA and VPA. Use when configuring Horizontal Pod Autoscaler (HPA), configuring Vertical Pod Autoscaler (VPA), or applying best practices for GKE workload autoscaling. Do not use for cluster-level autoscaling (Cluster Autoscaler), static/gke-workload-securityAudits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (`audit_cluster.sh`), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup),/gke-workload-troubleshootingDiagnoses GKE workload failures (CrashLoopBackOff, OOMKilled, ImagePullBackOff, Pending, etc.) via logs and events. Use when pods fail to start or crash repeatedly. Don't use for GKE cluster infrastructure provisioning, node pool creation, or non-Kubernetes Google Cloud services./google-agents-cli-onboardingOnboarding entrypoint for agents-cli in Agent Platform. It should be used when the user wants to "create a new agent", "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "evaluate an agent", "deploy an agent", "publish/google-cloud-global-frontend-configurationGuides agents through a 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 best-practice configurations. Use when: - Designing, configuring,/google-cloud-networking-observabilityInvestigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs (including cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics./google-cloud-recipe-authProvides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access./google-cloud-recipe-foundation-builderDeploys a baseline landing zone foundation for a Google Cloud Organization, establishing security guardrails using Organization Policies, resource hierarchy folders and projects, billing association, and centralized logging and monitoring. Deploys Google Cloud's recommended/google-cloud-recipe-onboardingGuides a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for/google-cloud-slo-alert-configurationConfigures PromQL-based Service Level Objective (SLO) alerting policies for Google Cloud resources registered in App Hub or individually specified. Generates Terraform output. Use when the user asks to configure an SLO or Service Level Objective. Don't use for standard alerting/google-cloud-solution-agentic-ai-bidirectional-streamingGuides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated/google-cloud-solution-agentic-ai-borderless-data-lakehouseGuides agents to discover requirements and design a governed, secure borderless open data lakehouse with agentic AI integration. Use when designing a multi-product architecture that connects data silos to AI agents, joining data across clouds, or running federated queries across/google-cloud-solution-agentic-ai-data-science-workflowDesigns 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,/google-cloud-solution-agentic-analytics-spark-knowledge-catalogDiscovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake,/google-cloud-solution-architectureInteractively discovers requirements for a specific cloud workload and generates design recommendations and architectural guidance to build a multi-product solution in Google Cloud. Use this skill to generate holistic, end-to-end design recommendations and architectural guidance/google-cloud-solution-build-deploy-agentsDesigns, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud./google-cloud-solution-guided-gke-ai-migrationGuides 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,/google-cloud-solution-n-tier-serverless-web-appGuides agents to interactively discover customer requirements for a Secure n-tier serverless web application and generate a tailored cloud multi-product solution that incorporates opinionated best practices and architecture guidance. Use when users need agentic assistance with/google-cloud-solution-rag-enterprise-search-gke-sqldbDiscovers 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,/google-cloud-storage-basicsStores, retrieves, and manages data as objects in Cloud Storage (Google Cloud Storage, or GCS) buckets. Use when you need to interact with Cloud Storage — create or configure buckets, upload, download, stream, or transfer data, organize objects with folders, generate signed/google-cloud-waf-cost-optimizationGenerates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the/google-cloud-waf-operational-excellenceGenerates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational/google-cloud-waf-performance-optimizationGenerates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance/google-cloud-waf-reliabilityGenerates guidance for reliability, resilience, availability, redundancy, fault-tolerance, and disaster recovery (DR) for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use when the user asks to evaluate,/google-cloud-waf-securityGenerates security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate workloads, identify security requirements, and provide actionable recommendations/google-cloud-waf-sustainabilityGenerates sustainability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify environmental impact requirements, and provide actionable/managed-airflow-migrationsProvides 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/spanner-basicsAssists in provisioning instances and databases, designing performant schemas, and querying data in Spanner. Use when designing primary keys, writing SQL queries or client library code, or diagnosing performance issues./workload-manager-basicsUse this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general
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README
1Agent Skills
This repository contains Agent Skills for Google products and technologies, including Google Cloud.
[!NOTE] This repository is under active development.
Installation
npx skills add google/skills
From the npx install command, you can select the specific skills from this
repo to install.
Available Skills
- Getting started with Google Cloud
- Multi-product solution skills
- Google Cloud solution-architecture workflow
- Agentic analytics across cloud providers and data types
- Borderless open data lakehouse agentic AI system
- Build and deploy AI agents on Google Cloud
- Data science workflow with AI agents solution
- Live bidirectional multimodal streaming agentic AI solution
- Migrate AI Workloads to GKE Inference
- RAG for enterprise search using GKE and AlloyDB
- Secure n-tier serverless web application with strict private application tiers
- AI/ML
- Agent Platform Alert Configuration
- Agent Platform Endpoint Management
- Agent Platform Eval Flywheel Skill
- Agent Platform GenAI Inference Skill
- Agent Platform Model Garden Deploy Skill
- Agent Platform Model Registry Management
- Agent Platform Model Tuning
- Agent Platform Prompt Management
- Agent Platform RAG Engine Management
- Agent Platform Troubleshooting
- Agent Platform Tuning Management
- BigQuery AI & ML
- Gemini API in Agent Platform
- Gemini Enterprise Agent Platform - Managed Agents API Skill
- Gemini Interactions API Skill
- LiveAPI Service Skill
- Migrating from Gemini API in AI Studio to Agent Platform
- Skill Registry
- Infrastructure
- GKE AI/ML Inference
- GKE App Onboarding
- GKE Backup & Disaster Recovery
- GKE Basics & Critical Gotchas
- GKE Batch & HPC Workloads
- GKE Cluster Autoscaler
- GKE Cluster Creation
- GKE ComputeClasses
- GKE Golden Path Configuration
- GKE JobSet Interruption Troubleshooting
- GKE Manifest Generation Skill
- GKE Multi-Tenancy
- GKE Networking
- GKE Productionize Skill
- GKE Reliability
- GKE Service Networking Skill
- GKE Storage
- GKE TPU Dynamic Slices Monitoring & Management
- GKE Upgrades & Maintenance
- GKE Workload Scaling
- GKE Workload Troubleshooting Skill
- Google Cloud global external Application Load Balancer Configuration Skill
- Google Cloud Networking Observability Expert
- Google Cloud Storage Basics
- Databases and analytics
- Developer tools
- Management tools
- Cloud Monitoring Chart Generation Skill (
cloud-monitoring-chart-generation) - Configuring Cloud Logging
- Configuring Cross-Project Logging
- Generate Logging Query Language queries
- GKE Cost Analysis
- GKE Cost Optimization
- GKE Observability
- GKE TPU Metrics Monitoring Guide
- Handle Disruption on GPUs and TPUs Troubleshooting
- Metric Selection (Service Query & Local Keyword Filtering)
- SLO Alert Configuration Setup Wizard
- TPU Connection Failure and VBAR OOM Troubleshooting
- Workload Manager Basics
- Cloud Monitoring Chart Generation Skill (
- Well-Architected Framework
- Google Cloud Well-Architected Framework skill for the Cost Optimization pillar
- Google Cloud Well-Architected Framework skill for the Operational Excellence pillar
- Google Cloud Well-Architected Framework skill for the Performance Optimization pillar
- Google Cloud Well-Architected Framework skill for the Reliability pillar
- Google Cloud Well-Architected Framework skill for the Security pillar
- Google Cloud Well-Architected Framework skill for the Sustainability pillar
- Security and identity
- Web and app hosting
- Advertising
- AI Migration Agent Instructions for the Google Mobile Ads SDK
- Data Manager API Audience Ingestion
- Data Manager API Event Ingestion
- Data Manager API Setup
- Google Ads API Account Performance Diagnostics Skill
- Google Ads API MCP Server Installation
- Google Ads API Quickstart
- Google Mobile Ads SDK - Banner Ads
- Google Mobile Ads SDK - Install
- Google Mobile Ads SDK - Interstitial Ads
- Google Mobile Ads SDK - Rewarded Ads
- IMA SDK basics
- Others
Additional Google skills
- Flutter Skills
- Dart Skills
- Advanced Google Cloud Storage Skills
- Agent Development Kit (ADK) Skills
- Firestore Skills
- Genkit Skills
Plugins
This repo also bundles Google product plugins (Skills + MCP servers) for agent harnesses.
| Agent harness | Install |
|---|---|
| Claude Code | claude plugin marketplace add google/skills, then claude plugin install <plugin>@google-plugins |
| Codex | codex plugin marketplace add google/skills, then install from the /plugins browser |
| Antigravity CLI | agy plugin install https://github.com/google/skills/<plugin-path> |
Support
If you need help or encounter issues with these skills, search for existing issues or open a new one in the GitHub Issue Tracker.
Contributing
We welcome contributions to improve our skills. You can help by:
- Reporting bugs or inaccuracies in the skill Markdown files.
- Suggesting new skills to add to this repository (for example, Google technologies or recipes) by filing a feature request.
License
You are free to copy, modify, and distribute these skills under the terms of the
Apache 2.0 license. See the LICENSE file for details.
File tree
507google/skillsView on GitHub
.agents/
plugins/
marketplace.json
.claude-plugin/
marketplace.json
.gitignore
.gitmodules
CONTRIBUTING.md
LICENSE
plugins/
cloud/
data-agent-kit/
README.md
README.md
skills/
ads/
data-manager-api-audience-ingestion/
references/
create-audience.md
formatting.md
SKILL.md
data-manager-api-event-ingestion/
SKILL.md
data-manager-api-setup/
references/
dotnet.md
java.md
node.md
php.md
python.md
SKILL.md
google-ads-api-account-diagnostics/
SKILL.md
google-ads-api-mcp-setup/
SKILL.md
google-ads-api-quickstart/
references/
dotnet.md
java.md
perl.md
php.md
python.md
rest.md
ruby.md
SKILL.md
google-mobile-ads-android-migrate-to-next-gen/
SKILL.md
google-mobile-ads-banner/
references/
android-banner.md
ios-banner.md
unity-banner.md
SKILL.md
google-mobile-ads-get-started/
assets/
skadnetwork-identifiers.xml
references/
android-get-started.md
ios-get-started.md
unity-get-started.md
SKILL.md
google-mobile-ads-interstitial/
references/
android-interstitial.md
ios-interstitial.md
SKILL.md
google-mobile-ads-rewarded/
references/
android-rewarded.md
ios-rewarded.md
SKILL.md
ima-sdk-basics/
references/
ima-sdk-android-guide.md
ima-sdk-ios-guide.md
ima-sdk-tvos-guide.md
ima-sdk-web-guide.md
ima-sdk-web-iframe-mode.md
ima-sdk-web-mobile-safari.md
SKILL.md
analytics/
google-analytics-admin-api-basics/
references/
dotnet.md
go.md
java.md
nodejs.md
php.md
python.md
ruby.md
SKILL.md
google-analytics-data-api-basics/
references/
dotnet.md
go.md
java.md
nodejs.md
php.md
python.md
ruby.md
SKILL.md
cloud/
agent-platform-alert-configuration/
references/
cost_alert_policies.md
has_historical_traffic_data.md
no_historical_traffic_data.md
quality_alert_policies.md
reliability_alert_policies.md
safety_alert_policies.md
security_alert_policies.md
telemetry_enablement.md
scripts/
analyze_traffic_test.py
analyze_traffic.py
check_telemetry_test.py
check_telemetry.py
config_utils_test.py
config_utils.py
create_online_monitor_test.py
create_online_monitor.py
gather_agent_info_test.py
gather_agent_info.py
lint_syntax.py
list_log_scope_table_names_test.py
list_log_scope_table_names.py
list_trace_scope_table_names_test.py
list_trace_scope_table_names.py
requirements.txt
scan_duplicates_test.py
scan_duplicates.py
SKILL.md
agent-platform-deploy/
references/
copy_deploy_guide.md
usage.md
scripts/
config_gcloud_cli.sh
SKILL.md
agent-platform-endpoint-management/
SKILL.md
agent-platform-eval-flywheel/
references/
dataset_schema.md
deployment.md
failure_patterns.md
metric_registry.md
sdk_patterns.md
scripts/
compare_results.py
endpoint_evaluation.py
inspect_results.py
maas_evaluation.py
parse_adk_traces.py
render_html_report.py
validate_dataset.py
SKILL.md
agent-platform-inference/
scripts/
gemini_genai_sdk.py
gemini_openai_sdk.py
gemini_vertexai_sdk.py
openmaas_genai_sdk.py
openmaas_openai_sdk.py
openmaas_vertexai_sdk.py
requirements.txt
verify_all.sh
SKILL.md
agent-platform-migrate-from-ai-studio/
SKILL.md
agent-platform-model-registry/
SKILL.md
agent-platform-prompt-management/
references/
create.md
SKILL.md
agent-platform-rag-engine-management/
SKILL.md
agent-platform-skill-registry/
references/
generate-skill.md
manage-skills.md
monitor-operations.md
query-skills.md
scripts/
requirements.txt
skill_registry_ops.py
validate_env.py
SKILL.md
agent-platform-troubleshooting/
references/
agent-gateway.md
agent-identity.md
agent-registry.md
field-manual.md
known-issues.md
policies.md
SKILL.md
agent-platform-tuning/
agent-platform-tuning-management/
SKILL.md
references/
data_prep.md
hf_datasets.md
models.md
requirements.txt
tuning_guide.md
scripts/
calculate_cost.py
cancel_tuning_job.py
list_models.py
monitor_tuning_job.py
prepare_dataset.py
tune_open_model.py
SKILL.md
alloydb-basics/
references/
cli-usage.md
core-concepts.md
iac-usage.md
iam-security.md
mcp-usage.md
SKILL.md
bigquery-ai-ml/
references/
ai_agg.md
ai_classify.md
ai_detect_anomalies.md
ai_evaluate.md
ai_forecast.md
ai_generate_embedding.md
ai_generate_table.md
ai_generate.md
ai_if.md
ai_key_drivers.md
ai_score.md
ai_search.md
ai_similarity.md
ml_contribution_analysis.md
remote_models.md
vector_search.md
SKILL.md
bigquery-basics/
references/
change-history.md
cli-usage.md
client-library-usage.md
continuous-queries.md
core-concepts.md
iac-usage.md
iam-security.md
mcp-usage.md
SKILL.md
bigquery-bigframes/
references/
linear_regression.md
logistic_regression.md
SKILL.md
bigtable-basics/
assets/
row_key_schema.yaml
references/
cli_data_access.md
client_libraries.md
dataplex.md
infrastructure_management.md
schema_design.md
sql_guide.md
SKILL.md
cloud-logging-configuration-basics/
SKILL.md
cloud-logging-cross-project-configuration/
SKILL.md
cloud-logging-query-generation/
references/
api_reference.md
query_app_engine.md
query_audit_logs.md
query_bigquery.md
query_cloud_functions.md
query_cloud_observability.md
query_cloud_run.md
query_cloud_source_repositories.md
query_cloud_sql.md
query_cloud_storage.md
query_cloud_tasks.md
query_compute_engine.md
query_dataflow.md
query_dataproc.md
query_deployment_manager.md
query_gke.md
query_iam.md
query_networking.md
query_security.md
query_service_usage.md
query_spanner.md
query_third_party.md
SKILL.md
cloud-monitoring-chart-generation/
scripts/
assemble_widget_proto_test.py
assemble_widget_proto.py
compute_labels_test.py
compute_labels.py
requirements.txt
textproto_util_test.py
textproto_util.py
validate_chart_test.py
validate_chart.py
SKILL.md
cloud-monitoring-metric-selection/
SKILL.md
cloud-run-basics/
references/
cli-usage.md
client-library-usage.md
core-concepts.md
iac-usage.md
iam-security.md
mcp-usage.md
networking.md
SKILL.md
cloud-sql-basics/
references/
cli-usage.md
client-library-usage.md
core-concepts.md
dr-backups.md
iac-usage.md
iam-security.md
mcp-usage.md
SKILL.md
datalineage-bigquery-asset-impact-analysis/
references/
mcp-usage.md
SKILL.md
datalineage-summary/
references/
mcp-usage.md
SKILL.md
detection-engineering-coverage-evaluation/
SKILL.md
developer-device-platform-basics/
references/
cancel_session.md
describe_device.md
list_sessions.md
reserve_device.md
session_status.md
start_adb_forwarder.md
update_session_expiration.md
view_device.md
scripts/
demo_adb_forwarder.py
requirements.txt
SKILL.md
firebase-basics/
references/
android_setup.md
firebase-cli-guide.md
firebase-service-init.md
flutter_setup.md
ios_setup.md
local-env-setup.md
refresh/
android_studio.md
antigravity.md
claude.md
gemini-cli.md
other-agents.md
setup/
android_studio.md
antigravity.md
claude_code.md
cursor.md
gemini_cli.md
github_copilot.md
other_agents.md
web_setup.md
SKILL.md
gcloud/
SKILL.md
gemini-agents-api/
SKILL.md
gemini-api/
references/
advanced_features.md
bounding_box.md
embeddings.md
live_api.md
media_generation.md
model_tuning.md
safety.md
structured_and_tools.md
text_and_multimodal.md
SKILL.md
gemini-interactions-api/
SKILL.md
gemini-live-api/
references/
... 309 moreMore Flows by @google.
@googleFAQ
google-skills is a Claude Code plugin with 104 hand-picked skills for development work, indexed on Flowy. Install it with the command on its page. It includes data-manager-api-audience-ingestion, data-manager-api-event-ingestion, data-manager-api-setup. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
- What is google-skills?
- This repository contains Agent Skills for Google products and technologies, including Google Cloud. This repository is under active development.
- How do I install google-skills?
- Run these in Claude Code: /plugin marketplace add google/skills. Then prompt normally.
- Does google-skills auto-invoke its skills?
- Not yet. It is indexed on Flowy as a plain plugin. Request auto-invocation on its page and Flowy will route its skills for you as you prompt.
- Is google-skills free?
- Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.