Claude Skills by LoopyLuci

**Trigger**: Use when working with GKE Networking — Google Kubernetes Engine configuration and management. This reference covers networking configuration for GKE clusters. The golden path enforces private, VPC-native clusters with Dataplane V2. > **MCP Tools:** `get_cluster`, `update_cluster`, `apply_k8s_manifest`, > `get_k8s_resource`

**Trigger**: Use when working with GKE Observability — Google Kubernetes Engine configuration and management. This reference covers monitoring, logging, and metrics configuration for GKE. The golden path enables comprehensive observability including control-plane metrics. > **MCP Tools:** `gke:get_cluster`, `gke:list_k8s_events`, `gke:get_k8s_logs`, > `gke:get_k8s_cluster_info`, `gke:describe_k8s_resource`. **CLI-only:** `gcloud > container clusters update --monitoring=...`, `gcloud logging r...

**Trigger**: Use when working with GKE Platform Security — Google Kubernetes Engine configuration and management. This reference covers platform-level security hardening and cluster configuration for Google Kubernetes Engine (GKE). For workload-level security controls (such as Workload Identity Service Account bindings, SecretProviderClass volume mounts, Network Policies, and Pod Security Standards), refer to the `gke-workload-security` skill. > **MCP Tools:** `gke:get_cluster`, `k8s:check_k8...

Use when assessing and preparing GKE clusters and workloads for production readiness.

**Trigger**: Use when working with GKE Reliability — Google Kubernetes Engine configuration and management. This reference covers high availability and reliability configuration for GKE clusters and workloads. > **MCP Tools:** `get_cluster`, `get_k8s_resource`, `describe_k8s_resource`, > `apply_k8s_manifest`, `list_k8s_events`

**Trigger**: Use when working with GKE Service Networking — Google Kubernetes Engine configuration and management. This skill provides workflows for exposing applications running on GKE securely to the internet or internal networks.

**Trigger**: Use when working with GKE Storage — Google Kubernetes Engine configuration and management. This reference covers storage configuration for GKE clusters including persistent disks, file storage, and cloud storage integration. > **MCP Tools:** `apply_k8s_manifest`, `get_k8s_resource`, > `describe_k8s_resource`, `get_cluster`

**Trigger**: Use when working with GKE Upgrades — Google Kubernetes Engine configuration and management. Produce clear, actionable documents — upgrade plans, runbooks, or checklists — tailored to the user's environment. Output should be specific to their cluster mode, release channel, version, and workload types rather than generic advice. Always frame guidance around the auto-upgrade model: auto-upgrade with maintenance windows and exclusions is the preferred control mechanism.

**Trigger**: Use when working with GKE Workload Scaling — Google Kubernetes Engine configuration and management. This skill provides workflows and best practices for scaling applications on Google Kubernetes Engine (GKE). It covers manual scaling, Horizontal Pod Autoscaling (HPA), and Vertical Pod Autoscaling (VPA).

**Trigger**: Use when working with GKE Workload Security — Google Kubernetes Engine configuration and management. This skill provides workflows and best practices for securing GKE workloads. It covers security auditing, Identity and Access Management (Workload Identity), Network Security (Network Policies), and Node Security.

Use when implementing Go concurrency patterns.

Use when building HTTP servers in Go.

Use when testing and benchmarking Go code.

Use when planning go-to-market and launch strategies.

Use when developing games with Godot engine.

**Trigger**: Use when implementing Google Api Account Diagnostics — AdMob, Ad Manager, and related ad SDKs. This skill provides instructions on how to use the Google Ads MCP server tools to diagnose common account performance issues.

Use when installing and configuring the Google Ads MCP Server for AI assistants.

**Trigger**: Use when implementing Google Api Quickstart — AdMob, Ad Manager, and related ad SDKs. This skill guides you from absolute zero to running your first successful request to retrieve campaigns.

Onboarding 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 an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle.

Use when setting up Google Analytics 4.

**Trigger**: Use when working with Google Cloud Google Analytics Admin Api — setup, configuration, and best practices. The Google Analytics Admin API provides programmatic access to Google Analytics account and property configuration. It lets you automate account management, manage data streams, configure custom dimensions, and handle product integrations.

**Trigger**: Use when working with Google Cloud Google Analytics Data Api — setup, configuration, and best practices. The Google Analytics Data API v1beta provides programmatic access to Google Analytics report data. It allows you to build customized dashboards, automate reporting workflows, and integrate Google Analytics data into your enterprise applications.

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, Comp...

Investigates 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. Don't use for generic VM management or non-observability tasks.

Use when authenticating and authorizing to Google Cloud services and APIs.

**Trigger**: Use when working with Google Cloud Google Cloud Recipe Foundation Builder — setup, configuration, and best practices. > [!WARNING] This skill is currently in a preview state. It will deploy a secure > foundation, but does not have all advanced features. Users who want more > options should visit > [Google Cloud Setup](https://docs.cloud.google.com/docs/enterprise/cloud-setup). This skill guides the setup of a secure, enterprise-grade Google Cloud landing zone foundation. It estab...

**Trigger**: Use when working with Google Cloud Google Cloud Recipe Onboarding — setup, configuration, and best practices. This skill provides a streamlined, non-interactive "happy path" for a singleton developer to get started with [Google Cloud](https://cloud.google.com/). It covers everything from environment verification and authentication to project selection, billing account linkage, and downstream safety chaining. > [!IMPORTANT] > For autonomous agents executing this skill: > 1. **Chec...

Guides 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 best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads. Don't use for simple te...

Guides 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 and external data sources, including on-premises or other cloud providers. Don't use for simple single-cloud data warehouses or non-AI workloads.

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 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, Salesforce, SAP, or Oracle systems) is accessed through federation mechanisms such as Apache Iceberg, other "zero-copy ETL" methods, or remote query push-down. Use this skill when designing an architecture for efficient a...

**Trigger**: Use when working with Google Cloud Google Cloud Solution Architecture — setup, configuration, and best practices.

Designs, 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. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.

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 ...

Guides 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 designing and creating a multi-product solution in the cloud for Secure n-tier serverless web application. Don't use when designing VM or GKE-based architectures or when not using Google Cloud.

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 databa...

**Trigger**: Use when working with Google Cloud Google Cloud Storage — setup, configuration, and best practices. Google Cloud Storage (GCS) is a managed service for storing data as objects at any scale. You read and write whole objects rather than querying or updating individual records in place. It stores immutable objects in buckets with strong global consistency, offers multiple storage classes and location types to balance cost, performance, and availability, and integrates with IAM for f...

Use when optimizing Google Cloud workload costs following the Well-Architected Framework.

Generates 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 requirements, and provide actionable recommendations for deployment, monitoring, and incident management.

Generates 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 requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.

Generates 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, design, or improve the reliability, resilience, availability, or disaster recovery capabilities of Google Cloud workloads.

Use when evaluating security posture of Google Cloud workloads following Well-Architected Framework.

Generates 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 recommendations to build, deploy, and manage the workload sustainably in Google Cloud.

Use when migrating Android apps from legacy GMA SDK to GMA Next-Gen SDK.

Use when implementing Google Mobile Ads banner ads in Android/iOS apps.

Use when integrating Google Mobile Ads SDK into Android, iOS, or Unity apps.

Use when implementing Google Mobile Ads interstitial ads in Android/iOS apps.

Use when implementing Google Mobile Ads rewarded ads in Android/iOS apps.

Use when deploying Google Tag Manager.

Use when managing GPG keys.