Use this skill to generate Azure architecture diagrams in .drawio format via the simonkurtz-MSFT MCP server (700+ Azure icons, batch creation, transactional mode). Covers architecture diagrams, dependency diagrams, runtime flow diagrams, and as-built diagrams. Do NOT use for WAF/cost charts (use python-diagrams), inline Mermaid (use mermaid), or Excalidraw diagrams (use excalidraw).

Upload files to the cloud and get shareable public URLs using stableupload.dev (x402 micropayments). USE FOR: - Uploading files to get public URLs - Sharing files via download links - Hosting images, documents, or any file type - Making files publicly accessible for 6 months TRIGGERS: - "upload this", "share this file", "get me a link" - "host this file", "make this downloadable" - "public URL", "download link", "put online" - "share file", "file hosting", "upload file" ALWAYS use `npx agentcash fetch` for stableupload.dev endpoints — never curl or WebFetch for the purchase step.

Up-to-date Microsoft Graph API knowledge for AI agents. Search 27,700+ Graph APIs, endpoint docs, resource schemas, and community samples — all locally, no network calls. Use when the agent needs to find, understand, or call Microsoft Graph endpoints.

Generates, formats, and validates technical documentation — including docstrings, OpenAPI/Swagger specs, JSDoc annotations, doc portals, and user guides. Use when adding docstrings to functions or classes, creating API documentation, building documentation sites, or writing tutorials and user guides. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, getting started guides.

Use when fine-tuning LLMs, training custom models, or adapting foundation models for specific tasks. Invoke for configuring LoRA/QLoRA adapters, preparing JSONL training datasets, setting hyperparameters for fine-tuning runs, adapter training, transfer learning, finetuning with Hugging Face PEFT, OpenAI fine-tuning, instruction tuning, RLHF, DPO, or quantizing and deploying fine-tuned models. Trigger terms include: LoRA, QLoRA, PEFT, finetuning, fine-tuning, adapter tuning, LLM training, model training, custom model.

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

Deploy, evaluate, and manage Foundry agents end-to-end: Docker build, ACR push, hosted/prompt agent create, container start, batch eval, continuous eval, prompt optimizer workflows, agent.yaml, dataset curation from traces. USE FOR: deploy agent to Foundry, hosted agent, create agent, invoke agent, evaluate agent, run batch eval, continuous eval, continuous monitoring, continuous eval status, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, improve agent instructions, optimize system prompt, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, create dataset from traces, dataset versioning, eval trending, create AI Services, Cognitive Services, create Foundry resource, provision resource, knowledge index, agent monitoring, customize deployment, onboard, availability. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

List, find, and show Azure resources across subscriptions or resource groups. Handles prompts like "list the websites in my subscription", "list my web apps", "show my app services", "list virtual machines", "list my VMs", "show storage accounts", "find container apps", and "what resources do I have". USE FOR: list websites, list web apps, list app services, show websites in subscription, resource inventory, find resources by tag, tag analysis, orphaned resource discovery (not for cost analysis), unattached disks, count resources by type, cross-subscription lookup, and Azure Resource Graph queries. DO NOT USE FOR: deploying/changing resources (use azure-deploy), cost optimization (use azure-cost), or non-Azure clouds.

Identify Azure cost savings from usage and spending data. USE FOR: optimize Azure costs, reduce Azure spending/expenses, analyze Azure costs, find cost savings, generate cost optimization report, identify orphaned resources to delete, rightsize VMs, reduce waste, optimize Redis costs, optimize storage costs, AKS cost analysis add-on, namespace cost, cost spike, anomaly, budget alert, AKS cost visibility. DO NOT USE FOR: deploying resources (use azure-deploy), general Azure diagnostics (use azure-diagnostics), security issues (use azure-security)

Implements Hotwire patterns with Turbo Frames, Turbo Streams, and Stimulus controllers. Use when building interactive UIs, real-time updates, form handling, partial page updates, or when user mentions Turbo, Stimulus, or Hotwire.

Corrects speech-to-text transcription errors in meeting notes, lectures, and interviews using dictionary rules and AI. Learns patterns to build personalized correction databases. Use when working with transcripts containing ASR/STT errors, homophones, or Chinese/English mixed content requiring cleanup.

Evaluate implementation options before coding changes. Creates comparison matrices, pros/cons analysis, risk assessment, and a recommended approach for architecture, feature planning, refactors, and debugging strategy decisions. Use when the user wants to compare multiple approaches before implementation. Trigger: "explore", "investigar", "think through", "analizar", "research", "sdd explore", "evaluar opciones", "/sdd:explore".