Loading...
Loading...
Found 173 Skills
Cloud & AI FinOps advisory skill. Structured cost optimization using the FinOps Foundation framework. Covers AWS, Azure, GCP, OCI, AI inference, and data platforms (Databricks, Snowflake). Use for: cloud costs, cost optimization, cloud spend, AI costs, cloud bill, FinOps assessment, GreenOps, right-sizing, commitment strategy, tagging governance.
Comprehensive context management strategies for cost optimization and infinite-length conversations. Covers server-side clearing (tool results, thinking blocks), client-side SDK compaction (automatic summarization), and memory tool integration. Use when managing long conversations, optimizing token costs, preventing context overflow, or enabling continuous agentic workflows.
Audit token waste across agent systems (Claude Code, OpenClaw, Hermes, OpenCode). Detect idle burns, model misrouting, and config bloat with dollar savings.
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.
Optimize Kubernetes costs through resource right-sizing, unused resource detection, and cluster efficiency analysis. Use for cost optimization, resource analysis, and capacity planning.
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.
OpenRouter unified AI API - Access 200+ LLMs through single interface with intelligent routing, streaming, cost optimization, and model fallbacks
Builds AI-native products using Dan Shipper's 5-product playbook and Brandon Chu's AI product frameworks. Use when implementing prompt engineering, creating AI-native UX, scaling AI products, or optimizing costs. Focuses on 2025+ best practices.
BigQuery Expert Engineer Skill - Comprehensive guide for GoogleSQL queries, data management, performance optimization, and cost management Use when: - Running bq commands (query, load, extract) - Writing GoogleSQL queries (functions, JOINs, CTEs) - Designing partitioned/clustered tables - Using BigQuery ML or external data sources
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 storing credentials in OCI Vault, troubleshooting secret retrieval failures, implementing secret rotation, or setting up application authentication to Vault. Covers vault hierarchy confusion, IAM permission gotchas, cost optimization, temp file security, and audit logging.
When the user wants to build GTM automation with code, design workflow architectures, use AI agents for GTM tasks, or implement the 'architecture over tools' principle. Also use when the user mentions 'GTM engineering,' 'GTM automation,' 'n8n,' 'Make,' 'Zapier,' 'workflow automation,' 'Clay API,' 'instruction stacks,' 'AI agents for GTM,' or 'revenue automation.' This skill covers technical GTM infrastructure from workflow design through agent orchestration.