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Found 173 Skills
Master of LLM Economic Orchestration, specialized in Google GenAI (Gemini 3), Context Caching, and High-Fidelity Token Engineering.
Design and implement Azure cloud architectures using best practices for compute, storage, databases, AI services, networking, and governance. Use when building applications on Microsoft Azure or migrating workloads to Azure cloud platform.
Provides comprehensive Google Cloud Platform (GCP) guidance including Compute Engine, Cloud Storage, Cloud SQL, BigQuery, GKE (Google Kubernetes Engine), Cloud Functions, Cloud Run, VPC networking, load balancing, IAM, Cloud Build, infrastructure as code (Terraform, Deployment Manager), security configuration, cost optimization, and multi-region deployment. Produces infrastructure code, deployment scripts, configuration guides, and architecture designs. Use when deploying to Google Cloud, designing GCP infrastructure, migrating to GCP, configuring GCE instances, setting up Cloud Storage, managing Cloud SQL databases, working with BigQuery, deploying to GKE, or when users mention "Google Cloud", "GCP", "Compute Engine", "Cloud Storage", "BigQuery", "GKE", "Cloud Run", "Cloud Functions", "VPC", "Cloud SQL", or "Google Cloud Platform".
Use when managing Oracle Autonomous Database on OCI, troubleshooting performance issues, optimizing costs, or implementing HA/DR. Covers ADB-specific gotchas, cost traps, SQL_ID debugging workflows, auto-scaling behavior, and version differences (19c/21c/23ai/26ai).
Integrate Azure AI Services, Azure OpenAI, and Cognitive Services.
Show detailed token ROI report across all tracked sessions
Apply Porter's Value Chain Analysis to identify competitive advantage sources within an organization's activities. Use this skill when the user needs to find where value is created or lost in their operations, analyze cost structure by activity, optimize internal processes, or identify outsourcing candidates — even if they say 'where do we make money' or 'which activities should we keep in-house'.
Tracks cumulative LLM costs across DAG execution and makes real-time decisions to stay within budget. Downgrades models, skips optional nodes, or stops early when cost exceeds thresholds. Use when managing execution budgets, analyzing cost breakdowns, or optimizing model routing for cost. Activate on "cost budget", "too expensive", "reduce cost", "cost optimization", "model downgrade", "budget exceeded". NOT for LLM model selection logic (use llm-router), pricing comparisons across providers, or billing/invoicing.
Use when designing cloud deployments, Dockerising applications, laying out AWS or GCP environments, choosing a deployment pattern, or moving a workload from a single VM to a resilient multi-AZ topology.
Find substitute materials using CWICR data. Identify equivalent alternatives based on function, cost, and availability.
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 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.