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Found 83 Skills
Use when user needs LLM system architecture, model deployment, optimization strategies, and production serving infrastructure. Designs scalable large language model applications with focus on performance, cost efficiency, and safety.
Use when designing multi-tenant OCI environments, setting up production landing zones, implementing compartment hierarchies, or establishing governance foundations. Covers Landing Zone reference architectures, compartment strategy, network topology patterns (hub-spoke vs multi-VCN), IAM structure, tagging standards, and cost segregation.
Use when "designing AWS architecture", "serverless AWS", "cloud infrastructure", "Lambda", "DynamoDB", or asking about "AWS cost optimization", "CloudFormation", "CDK", "API Gateway", "ECS", "EKS"
Comprehensive Azure cloud expertise covering all major services (App Service, Functions, Container Apps, AKS, databases, storage, monitoring). Use when working with Azure infrastructure, deployments, troubleshooting, cost optimization, IaC (Bicep/ARM), CI/CD pipelines, or any Azure-related development tasks. Provides scripts, templates, and best practices for production-ready Azure solutions.
Comprehensive guide to AWS cloud architecture covering compute, storage, databases, networking, security, serverless, and cost optimization with production-ready patterns
Analyzes Axiom query patterns to find unused data, then builds dashboards and monitors for cost optimization. Use when asked to reduce Axiom costs, find unused columns or field values, identify data waste, or track ingest spend.
Use when reviewing AWS architecture, designing cloud systems, addressing operational issues, security concerns, reliability problems, performance bottlenecks, cost overruns, or sustainability goals
Use when writing Terraform for OCI, troubleshooting provider errors, managing state files, or implementing Resource Manager stacks. Covers terraform-provider-oci gotchas, resource lifecycle anti-patterns, state management mistakes, authentication issues, and OCI Landing Zones.
Full-stack observability with Datadog APM, logs, metrics, synthetics, and RUM. Use when implementing monitoring, tracing, alerting, or cost optimization for production systems.
Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.
Generates 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.
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.