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Claude Skills by thedixitjain
github.com/thedixitjain12,707 skills283 installs48,721 views
- Gke Cluster Creation>- Plans 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 auditing GKE clusters. Don't use for application onboarding or deployment configuration (use gke-app-onboarding instead).Votes: 0GitHub stars: 3
- Gke Compute Classes>- 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.Votes: 0GitHub stars: 3
- Gke Cost Analysis>- Answer 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 BigQuery (`bq`), checking cluster cost budgets (`gcloud billing`), or diagnosing cost drivers like pod requests vs. actual utilization (`kubectl top`). Don't use for applying cost optimization changes, creating rig...Votes: 0GitHub stars: 3
- Gke Cost Optimization>- Optimizes 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. Don't use for general compute class provisioning or GPU Selection (use gke-compute-classes instead).Votes: 0GitHub stars: 3
- Gke Golden Path>- 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).Votes: 0GitHub stars: 3
- Gke Multitenancy>- 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).Votes: 0GitHub stars: 3
- Gke Networking>- Plans, 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 ranges, or managing VPC- native cluster modes. Don't use for application ingress, load balancing, or service networking (use gke-service-networking instead).Votes: 0GitHub stars: 3
- Gke Observability>- 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.Votes: 0GitHub stars: 3
- 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 workload before going live to production. Don't use for deep-dive single-domain implementation (use specific domain skills like gke-scaling, gke-platform-security, gke-workload-security, gke-service-networking, gke-rel...Votes: 0GitHub stars: 3
- Gke Reliability>- 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).Votes: 0GitHub stars: 3
- Gke Service Networking>- Configures 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 Google-managed SSL certificates on GKE. Don't use for core cluster IP planning, Dataplane V2 network policies, or node NAT egress (use gke-networking instead).Votes: 0GitHub stars: 3
- Gke Storage>- 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.Votes: 0GitHub stars: 3
- Gke Upgrades>- 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 mention...Votes: 0GitHub stars: 3
- Gke Workload Scaling>- Manages 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 cluster sizing, or configuring node-level machine styles directly.Votes: 0GitHub stars: 3
- Glean Observability'Track: documents indexed per run (total + new + updated + deleted), indexing errors and retries, search API latency, zero-result query rate, stale content age distribution. Trigger: \"glean observability\", \"observability\". 'Votes: 0GitHub stars: 3
- Google Cloud Agent Sdk Master'Execute automatic activation for all google cloud agent development kit (adk) Use when appropriate context detected. Trigger with relevant phrases based on skill purpose. 'Votes: 0GitHub stars: 3
- Google Cloud Global Frontend Configuration| 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, Comput...Votes: 0GitHub stars: 3
- Google Cloud Networking Observability>- 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.Votes: 0GitHub stars: 3
- 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.Votes: 0GitHub stars: 3
- Google Cloud Recipe Foundation Builder>- Deploys 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 security controls and architecture. Use when setting up a new Google Cloud Organization or establishing a secure, enterprise-grade landing zone foundation. Don't use for individual project onboarding (use google-cloud-r...Votes: 0GitHub stars: 3
- Google Cloud Recipe Onboarding>- Guides 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 enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.Votes: 0GitHub stars: 3
- Google Cloud Solution Agentic Ai Bidirectional Streaming>- 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...Votes: 0GitHub stars: 3
- Google Cloud Solution Agentic Ai Borderless Data Lakehouse>- 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.Votes: 0GitHub stars: 3
- Google Cloud Solution Agentic Ai Data Science Workflow>- 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.Votes: 0GitHub stars: 3
- Google Cloud Solution Agentic Analytics Spark Knowledge Catalog>- 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 effici...Votes: 0GitHub stars: 3
- Google Cloud Solution Architecture>- Interactively 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 for holistic, end-to-end design recommendations and architectural guidance for complex, multi-product workloads on Google Cloud for specific use cases. Don't use this skill when other specialized skills (e.g., product-specific or google-cloud-recipe-*) directly address the user's workload or use ...Votes: 0GitHub stars: 3
- Google Cloud Solution Build Deploy Agents>- 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.Votes: 0GitHub stars: 3
- Google Cloud Solution Guided Gke Ai Migration>- 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 u...Votes: 0GitHub stars: 3
- Google Cloud Solution N Tier Serverless Web App>- 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.Votes: 0GitHub stars: 3
- Google Cloud Storage Basics>- Stores, 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 URLs, control access (IAM, ACLs, public access prevention), set storage classes and tiering (Standard, Nearline, Coldline, Archive), manage cost and lifecycle, protect data (versioning, encryption/CMEK, retention and Bu...Votes: 0GitHub stars: 3
- Google Cloud Vision AutomationAutomate Google Cloud Vision tasks via Rube MCP (Composio). Always search tools first for current schemas.Votes: 0GitHub stars: 3
- 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 workload cost-efficiently in Google Cloud.Votes: 0GitHub stars: 3
- Google Cloud Waf Operational Excellence>- 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.Votes: 0GitHub stars: 3
- Google Cloud Waf Reliability>- 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.Votes: 0GitHub stars: 3
- 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 a workload, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security.Votes: 0GitHub stars: 3
- Google Cloud Waf Sustainability>- 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.Votes: 0GitHub stars: 3
- Gpu Resource Optimizer'Optimize gpu resource optimizer operations. Auto-activating skill for ML Deployment. Triggers on: gpu resource optimizer, gpu resource optimizer Part of the ML Deployment skill category. Use when working with gpu resource optimizer functionality. Trigger with phrases like \"gpu resource optimizer\", \"gpu optimizer\", \"gpu\". 'Votes: 0GitHub stars: 3
- Grafana Dashboard Creator'Create grafana dashboard creator operations. Auto-activating skill for DevOps Advanced. Triggers on: grafana dashboard creator, grafana dashboard creator Part of the DevOps Advanced skill category. Use when working with grafana dashboard creator functionality. Trigger with phrases like \"grafana dashboard creator\", \"grafana creator\", \"grafana\". 'Votes: 0GitHub stars: 3
- Grafana Dashboards WshobsonCreate and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.Votes: 0GitHub stars: 3
- Grafana DashboardsCreate and manage production-ready Grafana dashboards for comprehensive system observability.Votes: 0GitHub stars: 3
- Grammarly Observability'Implement Grammarly observability with metrics and logging. Use when setting up monitoring, tracking API performance, or implementing alerting for Grammarly integrations. Trigger with phrases like \"grammarly monitoring\", \"grammarly metrics\", \"grammarly observability\", \"grammarly logging\", \"grammarly alerts\". 'Votes: 0GitHub stars: 3
- Granola Multi Env Setup'Configure Granola across multiple workspaces and teams with SSO/SCIM provisioning. Use when setting up department-level workspaces, configuring user provisioning, or managing enterprise-scale Granola deployments. Trigger: \"granola workspaces\", \"granola multi-team\", \"granola SSO\", \"granola SCIM\", \"granola organization setup\". 'Votes: 0GitHub stars: 3
- Granola Observability'Monitor Granola adoption, meeting analytics, and build custom dashboards. Use when tracking team meeting patterns, measuring adoption, building analytics pipelines, or creating executive reports. Trigger: \"granola analytics\", \"granola metrics\", \"granola monitoring\", \"granola adoption\", \"meeting insights\". 'Votes: 0GitHub stars: 3
- Groq Observability'Set up observability for Groq integrations: latency histograms, token throughput, rate limit gauges, cost tracking, and Prometheus alerts. Use when instrumenting Groq API calls, building a metrics dashboard, or wiring latency/cost/rate-limit alerts. Trigger with phrases like \"groq monitoring\", \"groq metrics\", \"groq observability\", \"monitor groq\", \"groq alerts\", \"groq dashboard\". 'Votes: 0GitHub stars: 3
- Guidewire Ci Cd PipelineShip Gosu code and configuration changes through Guidewire Cloud Console deployment slots without breaking running policies — Gosu compile + GUnit + lint gates per PR, config-package promotion dev→UAT→prod, schema-change rollouts with rollback hazards documented, canary deploy for high-risk changes, and the rollback decision tree when a release affects already-bound policies. Use when designing the deploy pipeline for a new InsuranceSuite project, hardening an existing one, or recovering from...Votes: 0GitHub stars: 3
- Guidewire Core Workflow AAutomate the PolicyCenter account→submission→quote→bind→issue→endorse→renew pipeline including the failure paths — underwriting issues blocking bind, quotes expiring before bind, referrals stuck pending approval, and mid-term endorsements that trigger unexpected premium audit recalculation. Use when building outbound integrations against PolicyCenter Cloud API (CRM-driven submission, broker-portal binding, automated renewal jobs). Trigger with \"policycenter automation\", \"submission to bind...Votes: 0GitHub stars: 3
- Guidewire Observability And Incident ResponseOperate a Guidewire Cloud API integration in production — define SLIs/SLOs for token availability, bind success rate, FNOL p99 latency; route alerts so the on-call gets paged for real outages and never for transient noise; triage 401 spikes, 409 storms, 429 saturation, scope drift, and Gosu OOM cascades from signal to recovery in 15 minutes or less. Use when designing a dashboard for a new integration, writing the on-call runbook, or running a post-incident review. Trigger with \"guidewire ob...Votes: 0GitHub stars: 3
- Guidewire Sdk PatternsBuild a production-grade Guidewire Cloud API client that survives the request-side failures — 409 checksum conflicts on PATCH/PUT, 429 quota throttling, offsetToken pagination drift, retry-unsafe POSTs, and unstructured error responses. Use when designing an HTTP client wrapper around PolicyCenter, ClaimCenter, or BillingCenter REST endpoints. Trigger with \"guidewire client\", \"guidewire sdk\", \"checksum 409\", \"guidewire pagination\", \"guidewire rate limit\", \"Retry-After\".Votes: 0GitHub stars: 3
- Hard Predict Future> Activate this agent for any future-oriented question that requires deep quantitative analysis, historical precedents, and structured scenario planning. Triggers include: \"Will [X]?\", \"Who will win [X]?\", \"What happens to [X]?\", prediction requests with high stakes, foresight analysis, STEEEP scenario planning, futures cone, competitive race analysis, technology adoption curves, geopolitical shifts, or any question about a future outcome that deserves rigorous multi-step analysis. This...Votes: 0GitHub stars: 3
- Hardening Docker Daemon ConfigurationHarden the Docker daemon by configuring daemon.json with user namespace remapping, TLS authentication, rootless mode, and CIS benchmark controls.Votes: 0GitHub stars: 3