Claude Skills by NVlabs

Provides instructions for integrating the Google Mobile Ads (GMA)

Provides instructions for implementing, integrating, or configuring

Provides instructions for implementing, integrating, or configuring

Use 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 instead).

Manages 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 activeUsers, screenPageViews) and dimensions (like city, date), check metrics and dimensions compatibility, or verify API enablement.

Manages 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 endpoints or for running model evaluations.

Agent 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 models.

Manages 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.

Interact 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.

GenerateSkill automates the *initial* scaffolding of new agent skills by generating standardized documentation (`SKILL.md`) and directory structures based on user requirements. Note: This tool serves strictly as a starting point. It generates a foundational draft and requires human intervention to refine the logic, review the architecture, and ensure the final skill meets production-level quality standards.

Manages 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-endpoint-management`).

Agent 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 `agent-platform-endpoint-management`).

Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB model context protocol (MCP) tools for automated database operations.

Leverages 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, detect outliers, find key drivers, or leverage generative AI capabilities in BigQuery.

Manages 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.

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.

Manages 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).

Automates 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, and generating new YARA-L 2.0 rules to close coverage gaps. Don't use when asked to perform threat hunting actions, and SOC investigative actions.

Use this skill whenever you are working on a project that uses Firebase products or services, especially for mobile or web apps.

Manages 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-basics or gke-upgrades instead).

Configures GKE Backup Plans and restore workflows. Use for backup policies, disaster recovery, or GKE cluster restores. Don't use for database backups.

Core GKE cluster discovery and hub. Use to route to specialized GKE skills. Do not use for specialized tasks (networking, security, etc.) directly.

Runs 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).

Plans and executes GKE cluster creation, provisioning, and production readiness audits. Use when creating GKE clusters, provisioning GKE environments, or auditing GKE clusters. Don't use for application onboarding or deployment configuration (use gke-app-onboarding instead).

Configures, 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 not use for cluster-level Node Auto Provisioning configuration or general GKE cluster creation.

Optimizes GKE costs, rightsizes workloads, and configures Spot VMs and CUDs. Use when optimizing GKE costs, rightsizing GKE workloads, or configuring GKE Spot VMs. Don't use for general compute class provisioning or GPU Selection (use gke-compute-classes instead).

Provides 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 node autoscaling specifically (use gke-scaling instead).

Deploys 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 instead).

Plans 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 teams. Don't use for single-tenant cluster configuration or general deployment instructions (use gke-basics or gke-app-onboarding instead).

Plans, configures, and manages GKE networking. Covers private clusters, VPC- native configurations, Gateway API, DNS, ingress/egress, Dataplane V2, and IP planning. Use when designing GKE networking layouts, configuring private clusters, setting up Gateway API, planning GKE IP ranges, or configuring GKE ingress/egress. Don't use for basic application routing that does not require dedicated network configuration.

Configures 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 APMs outside GKE.

Improves 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 backups (use gke-backup-dr instead).

Configures GKE autoscaling, including HPA, VPA, and Node Auto-Provisioning (NAP). Use when configuring GKE autoscaling, setting up GKE HPA, setting up GKE VPA, or configuring GKE NAP. Don't use for configuring static cluster sizes or setting node-level machine styles directly (use gke-compute-classes instead).

Plans, configures, and hardens Google Kubernetes Engine (GKE) security. Covers Workload Identity Federation, Secret Manager integration, RBAC hardening, Binary Authorization, Network Policies (Dataplane V2), Pod Security Standards, and IAM roles. Use when securing GKE clusters, setting up Workload Identity, hardening RBAC configurations, or configuring GKE secrets. Don't use for general network routing configuration (use gke-networking instead).

Manages 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.

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 G...

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 this skill when building applications with Gemini API hosted models, including Gemini and Gemma 4, working with multimodal content (text, images, audio, video), implementing function calling, using structured outputs, or needing current model specifications. Covers SDK usage (google-genai for Python, @google/genai for JavaScript/TypeScript, com.google.genai:google-genai for Java, google.golang.org/genai for Go), model selection, and API capabilities.

Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. This skill covers the Interactions API, the recommended way to use Gemini models and agents in Python and TypeScript.

Master Alex Hormozi's offer creation framework from \"$100M Offers\" (2021). Build irresistible offers using the Value Equation, stacking, guarantees, and scarcity. Use when: Creating new product or service offers; Restructuring existing offers for higher conversions; Pricing premium products and services; Building offer stacks with bonuses and guarantees; Choosing target markets for maximum leverage

Use when the CTO describes a feature, task, or project goal. Orchestrates the full SDLC pipeline automatically based on project type.

Design and optimize self-reinforcing growth systems using Reforge methodology—shift from linear funnels to compounding loops where outputs become inputs for sustainable, defensible growth. Use when: **Analyze your current growth model** and identify if you have a loop or funnel; **Design a growth loop** for a new product or feature; **Diagnose why growth isn't compounding** despite acquisition efforts; **Identify the right loop type** for your business model; **Optimize loop velocity** to acc...

Understand why customers really buy by uncovering the \"job\" they're hiring your product to do Use when: **Understanding customer motivation** beyond demographics and feature requests; **Finding product-market fit** by identifying the real progress customers seek; **Discovering why customers switch** (or don't) between solutions; **Identifying true competition** that isn't obvious from industry categories; **Creating marketing messages** that resonate with real customer struggles

Getting ROI from hackathon sponsorships for developer tools. Covers evaluating which hackathons to sponsor, booth presence strategies, prizes that actually work, judge involvement, follow-up strategies, and measuring sponsorship ROI. Use when asked about: - Hackathon sponsorship strategy - Developer event sponsorship ROI - Hackathon prizes - Booth presence at hackathons - Post-hackathon follow-up - Hackathon sponsorship evaluation

When the user wants to promote on Hacker News, launch on HN, or understand what works on HN. Trigger phrases include "Hacker News," "HN post," "Show HN," "HN strategy," "getting upvotes on HN," "HN launch," or "why did my HN post die."

Analyze hashtag performance and discover trending tags. Use when: researching hashtags for posts; finding related hashtags; analyzing hashtag reach; planning hashtag strategy; competitor hashtag research

25+ proven headline formulas that stop the scroll, capture attention, and drive clicks. Templates and examples for every situation. Use when: Writing headlines for landing pages, ads, or articles; Creating email subject lines that get opens; Crafting social media hooks; A/B testing headline variations; Overcoming headline writer's block

Design and maintain customer health scoring systems with automated alerts and trending analysis

Use when the user wants to check dataset quality, diagnose eval issues, or before running evolve. Checks size, difficulty distribution, dead examples, coverage, and splits. Auto-corrects issues found.

HIG Doctor audit workflow for scanning app projects against Apple Human Interface Guidelines. Use when the user asks for a HIG audit, Apple UI compliance scan, accessibility/design lint, HIG Doctor, severity report, CI gate, or wants to verify SwiftUI, UIKit, React, Next.js, Vue, Svelte, Angular, React Native, Flutter, Compose, Android XML, CSS, or HTML against Apple HIG rules.