@google · United States of America
Google ❤️ Open Source
Agent Skills by Google
Showing 237 vetted skills indexed across 10 GitHub repositories.
googlemantis-advise
Queries a SQLite security knowledge base to provide threat models and verified patch guidance for code edits.
googlemantis-configure
Configures sandbox mechanisms, AI models, and credentials for Mantis security review pipelines.
googlemantis-launch
Launches automated vulnerability review campaigns on target files or repositories.
googlegoogle-cloud-recipe-onboarding
Guides first-time Google Cloud setup including authentication, project creation, and billing linkage.
googlefinding-google-skills
Locates and loads Google product skills from a remote catalog index on demand.
googlegoogle-cloud-recipe-auth
Guides authentication and authorization setup for Google Cloud services and APIs.
googleima-dai-sdk
Integrates Google IMA DAI SDK for HLS and DASH ad-inserted streams across web, mobile, and TV platforms.
googlegoogle-ads-api-account-diagnostics
Diagnoses Google Ads account performance issues using GAQL queries via the Google Ads MCP server.
googleima-sdk-client-side
Integrates Google IMA SDK for client-side video ad insertion across web, Android, iOS, and tvOS.
googlegke-alert-configuration
Generates Terraform alerting policies for GKE workloads using PromQL and Managed Service for Prometheus.
googlespanner-basics
Provision Spanner instances, design performant schemas, and query data using gcloud and client libraries.
googlegoogle-cloud-solution-n-tier-serverless-web-app
Designs secure n-tier serverless web applications on Google Cloud with Terraform and validation scripts.
googlegke-service-networking
Configures GKE Gateway API, Ingress, Cloud Armor, NEGs, and Private Service Connect networking.
googlegoogle-cloud-solution-agentic-ai-data-science-workflow
Designs multi-product agentic data science architectures on Google Cloud with deployment and validation plans.
googlegoogle-cloud-solution-guided-gke-ai-migration
Migrates existing AI inference workloads to self-hosted GKE inference using gcloud and kubectl.
googleapplication-design-center-design-deploy
Designs, validates, and deploys GCP infrastructure using Terraform and Application Design Center.
googlegoogle-cloud-slo-alert-configuration
Generates Terraform SLO alerting policies with PromQL burn-rate queries for Google Cloud services.
googlegke-productionize
Orchestrates production readiness assessments for GKE clusters and workloads across security, reliability, and cost domains.
googlecloud-databases-onboarding
Recommends Google Cloud databases from requirements and drafts validated Terraform provisioning code.
googlegke-ai-troubleshooting-jobset-interruption
Diagnoses GKE JobSet interruptions, preemptions, and restarts for AI/ML training workloads.
googlegke-workload-troubleshooting
Diagnoses GKE workload failures via pod status, events, and logs, then proposes GitOps manifest fixes.
googlegke-ai-troubleshooting-handle-disruption-gpu-tpu
Diagnoses and mitigates GKE node disruptions from host maintenance on GPU and TPU workloads.
googlegoogle-cloud-solution-agentic-ai-borderless-data-lakehouse
Designs a governed borderless open data lakehouse architecture on Google Cloud with agentic AI integration.
googlemanaged-airflow-dag-authoring
Author and validate Apache Airflow DAGs for Managed Service for Apache Airflow environments.
Frequently Asked Questions About Google
FAQPage SchemaWhat specific tasks can engineers perform using these resources?▼
Engineers can manage GKE cluster lifecycles, configure secure cloud networking, perform BigQuery data analysis, integrate Gemini multimodal capabilities into applications, and execute automated security threat modeling and incident response procedures.
Which technical personas are these resources designed for?▼
These resources target Cloud Architects, Site Reliability Engineers, Security Researchers, and Full-Stack Developers building on Google Cloud, Kubernetes, or Gemini-based agentic platforms.
What are the primary prerequisites for deploying these solutions?▼
Deployment typically requires an active Google Cloud project, configured IAM permissions, the Google Cloud SDK, and specific environment dependencies like Terraform, Docker, or language-specific runtimes such as Rust or Python.