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Set up Google's agents-cli and find the right workflow for building AI agents. Connects requirements planning, project creation, implementation, evaluation, deployment, publishing, and monitoring through specialized skills for the Gemini Enterprise Agent Platform.

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• Set up agents-cli and its specialized skills
• Document agent requirements before writing code
• Find the workflow for creating and evaluating an ADK agent

Retrieve security findings from Google Cloud Security Command Center for initial assessment. Filter active vulnerabilities, threats, and external exposures, inspect one finding’s full details, or group counts by category to understand the reported risks.

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• Retrieving full details for a named security finding
• Listing active vulnerabilities or external exposures
• Summarizing active finding counts by category

Guides authentication and access permissions for Google Cloud users and applications. It helps choose credentials for local development, production services, or external clouds, with guidance on short-lived credentials and avoiding downloaded service account keys.

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• Set up credentials for local Python development
• Configure Cloud Run access to Cloud SQL
• Connect workloads on AWS or Azure to Google Cloud

Manage temporary access in Google Cloud with Privileged Access Manager. Configure who can request which roles and for how long, maintain access configurations, and handle access requests and approval decisions through guided workflows.

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• Request temporary access to Google Cloud resources
• Configure eligible requesters and approvers
• Review and approve or deny pending access requests

Reviews Google Cloud spending and resource usage to identify waste, recommend suitable resource sizes, compare discount options, and establish ongoing cost management using the cost optimization guidance in the Google Cloud Well-Architected Framework.

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• Reviewing Google Cloud spending by team or project
• Finding idle resources and oversized instances
• Comparing CUDs, SUDs, and Spot VMs

Evaluate Google Cloud workloads against built-in best practices or custom organizational rules using Workload Manager. Use public client libraries or the REST API to run checks, review violations and scanned resources, and export results to BigQuery.

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• Evaluate workloads against Google Cloud best practices
• Inspect rules for SAP and SQL Server workloads
• Run evaluations using custom organizational rules

Investigate Google Cloud access denials and choose a resolution path based on the caller’s permissions. Supports temporary access activation, structured escalation tickets, policy analysis, and administrator selection of roles that grant only the permissions needed.

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• Investigating Google Cloud access denials
• Activating temporary access for development
• Preparing access issue tickets for administrators

Evaluate Google Cloud workloads and develop reliability recommendations covering user experience goals, redundancy, monitoring, and recovery. The skill applies the Google Cloud Well-Architected Framework to help identify gaps and plan improvements suited to business requirements.

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• Reviewing a Google Cloud architecture for reliability gaps
• Setting reliability targets based on user experience
• Planning redundancy and behavior during partial failures

Browse and search files on Google Cloud Filestore, read selected log lines, and inspect permissions and timestamps. Uses a Cloud Run bridge or an existing virtual machine without requiring local NFS client packages or root access.

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• Explore the folder structure of a Filestore share
• Find backup files by filename pattern
• Search remote logs for errors and read selected lines

Manage files in Google Cloud's Cloud Storage buckets, the containers that hold stored data. Upload, download, and organize content, configure access and time-limited sharing links, and manage storage lifecycle, costs, and data protection.

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• Upload, download, and organize stored files
• Share files through time-limited signed URLs
• Review storage classes and lifecycle rules

Design and implement Google Cloud serverless web apps with separate presentation, application, and data layers. Produces architecture diagrams, Terraform infrastructure code, deployment instructions, and validation scripts for private networking and controlled access between layers.

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• Design a serverless web app with separate application layers
• Generate Terraform for private Cloud Run and Cloud SQL connections
• Plan regional data residency requirements

Design a Google Cloud system for data analysis or machine learning with AI agents. Turn requirements into product choices, an architecture diagram, infrastructure configuration, deployment instructions, and validation steps, with user reviews between phases.

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• Design a data analysis system with multiple AI agents
• Choose Google Cloud products for analytical requirements
• Prepare an architecture diagram and deployment guide

Implement and debug Google OAuth 2.0 refresh tokens bound to a client key. Covers key generation, signed DPoP proofs that demonstrate key possession, and nonce challenge retries in WebCrypto and JavaScript environments.

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• Bind Google OAuth refresh tokens to a client key
• Debug DPoP proof signatures and nonce retries
• Plan a backend for a browser application using DPoP

Investigate Google Cloud network problems using traffic logs, performance metrics, and connection path tests. Identify blocked traffic, packet loss, and latency, summarize traffic volumes, or estimate VPC Flow Logs costs.

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• Investigate blocked traffic and packet loss
• Check latency and throughput trends
• Analyze Cloud NAT port exhaustion

Design security controls for Google Cloud Agent Gateway, covering incoming client requests and outgoing agent tool calls. Produce architecture diagrams, configuration files, deployment commands, and validation scripts using Model Armor, IAP, and Agent Registry.

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• Design incoming and outgoing agent communication controls
• Prepare Model Armor filters and tool access policies
• Generate scripts to check authentication and allowed tool calls

Guides migration of existing AI inference workloads to self-hosted GKE, Google’s managed Kubernetes service. Covers requirements, GPU sizing, deployment configuration, model storage, validation, and traffic cutover using gcloud and kubectl.

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• Migrating an existing Cloud Run AI service to GKE
• Planning a self-hosted replacement for Gemini API inference
• Sizing GPUs and preparing deployment configuration

Define reliability goals for Google Cloud services and generate Terraform files for Cloud Monitoring SLO alerts. A guided conversation gathers service scope, measurement metrics, targets, and alert conditions, then explains the PromQL queries used to evaluate them.

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• Create availability SLO alerts for a service
• Define latency targets and measurement windows
• Configure SLO alerts for App Hub resources

Design a Google Cloud system that combines multiple services, starting with a discussion of business and technical requirements. The skill produces service recommendations, architecture diagrams, deployment guidance, and validation plans, with user approval at each stage.

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• Gather requirements for a new cloud workload
• Compare and select services for a cloud migration
• Create a diagram and explain system data flows

Audits Google Cloud Filestore instances for missing or outdated backups, overly broad file share access, and zone isolation requirements. Produces a health scorecard, prioritized findings, an instance inventory, and proposed backup remediation.

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• Finding file shares without recent backups
• Auditing NFS access ranges and root privileges
• Checking physical zone isolation and separation

Helps choose and tune Cloud Storage FUSE mounts, which expose bucket objects through file paths. It covers cache sizing, training performance, checkpoint write safety, and cost diagnosis on GKE, Compute Engine, and Cloud Run.

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• Access training data through file paths
• Choose between FUSE, native reads, and shared file systems
• Check checkpoint and concurrent write safety

Review Google Cloud operations and develop guidance for monitoring, incident response, resource sizing, and automated deployments. Use framework-based questions and checklists to identify gaps in production readiness and plan ongoing operational improvements.

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• Reviewing production readiness
• Planning monitoring and logging
• Improving incident response procedures

Plan and manage Cloud Spanner databases on Google Cloud, design tables and primary keys, write SQL and client code, and investigate slow queries using database statistics to identify resource-intensive operations.

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• Create Cloud Spanner instances and databases
• Design primary keys and related tables
• Write SQL queries and client library code

Diagnoses applications that fail to start or repeatedly crash on GKE, Google's managed Kubernetes service. It examines logs, events, memory use, image pulls, and connectivity, then proposes configuration patches or commands without applying live changes.

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• Investigate repeated container restarts
• Diagnose memory exhaustion
• Find causes of image pull or scheduling failures

Set up an organization-wide Google Cloud foundation with 17 baseline security policies, environment folders and projects, billing links, and centralized audit logging and monitoring. Check the resulting setup against a defined validation checklist.

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• Set up the initial foundation for a Google Cloud organization
• Organize production, non-production, and development resources
• Apply baseline security policies across an organization