azure-copilot
Expert knowledge for Azure Copilot development including troubleshooting, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when sizing VMs, generating Bicep/Terraform, configuring Cosmos DB storage, or debugging App Service/VM disks, and other Azure Copilot related development tasks. Not for Azure AI services (use microsoft-foundry-tools), Azure Machine Learning (use azure-machine-learning), Azure AI Search (use azure-cognitive-search), Azure AI Bot Service (use azure-bot-service).
What this skill does
# Azure Copilot Skill This skill provides expert guidance for Azure Copilot. Covers troubleshooting, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. It combines local quick-reference content with remote documentation fetching capabilities. ## How to Use This Skill > **IMPORTANT for Agent**: Use the **Category Index** below to locate relevant sections. For categories with line ranges (e.g., `L35-L120`), use `read_file` with the specified lines. For categories with file links (e.g., `[security.md](security.md)`), use `read_file` on the linked reference file > **IMPORTANT for Agent**: If `metadata.generated_at` is more than 3 months old, suggest the user pull the latest version from the repository. If `mcp_microsoftdocs` tools are not available, suggest the user install it: [Installation Guide](https://github.com/MicrosoftDocs/mcp/blob/main/README.md) This skill requires **network access** to fetch documentation content: - **Preferred**: Use `mcp_microsoftdocs:microsoft_docs_fetch` with query string `from=learn-agent-skill`. Returns Markdown. - **Fallback**: Use `fetch_webpage` with query string `from=learn-agent-skill&accept=text/markdown`. Returns Markdown. ## Category Index | Category | Lines | Description | |----------|-------|-------------| | Troubleshooting | L34-L39 | Using Copilot to diagnose and resolve Azure App Service/Functions issues and analyze Azure VM disk performance problems, including slow I/O and bottlenecks. | | Decision Making | L40-L48 | Using Copilot to compare options and make cost‑efficient Azure decisions: VM sizing, workload templates, Marketplace offers, storage estate insights, and Load Balancer SKU selection. | | Architecture & Design Patterns | L49-L53 | Using Copilot to design, validate, and troubleshoot Azure network architectures, including connectivity, routing, security, and performance issues across VNets and hybrid setups. | | Security | L54-L62 | Security and access control for Azure Copilot: storage hardening, user/tenant access, agent access policies, attack surface insights, and responsible AI/data use. | | Configuration | L63-L67 | How to set up and configure Azure Cosmos DB as the storage backend for Azure Copilot conversation data, including required settings and integration steps. | | Integrations & Coding Patterns | L68-L73 | Using Azure Copilot to generate and refine infra-as-code and automation: APIM policies, Azure CLI/PowerShell scripts, Kubernetes YAML for AKS, and Terraform/Bicep templates. | ### Troubleshooting | Topic | URL | |-------|-----| | Troubleshoot Azure App Service and Functions with Copilot | https://learn.microsoft.com/en-us/azure/copilot/troubleshoot-app-service | | Troubleshoot Azure VM disk performance using Copilot | https://learn.microsoft.com/en-us/azure/copilot/troubleshoot-disk-performance | ### Decision Making | Topic | URL | |-------|-----| | Use Azure Copilot to analyze and optimize cloud costs | https://learn.microsoft.com/en-us/azure/copilot/analyze-cost-management | | Choose and deploy cost-efficient Azure VMs with Copilot | https://learn.microsoft.com/en-us/azure/copilot/deploy-vms-effectively | | Find and deploy workload templates using Azure Copilot | https://learn.microsoft.com/en-us/azure/copilot/deploy-workload-templates | | Find suitable Azure Marketplace solutions with Copilot | https://learn.microsoft.com/en-us/azure/copilot/discover-marketplace | | Select and manage Azure Load Balancer SKUs with Copilot | https://learn.microsoft.com/en-us/azure/copilot/work-load-balancer | ### Architecture & Design Patterns | Topic | URL | |-------|-----| | Design and troubleshoot Azure networks with Copilot | https://learn.microsoft.com/en-us/azure/copilot/copilot-networking | ### Security | Topic | URL | |-------|-----| | Improve and migrate Azure storage accounts with Copilot | https://learn.microsoft.com/en-us/azure/copilot/improve-storage-accounts | | Manage user access and authorization for Azure Copilot | https://learn.microsoft.com/en-us/azure/copilot/manage-access | | Control tenant access to Azure Copilot agents preview | https://learn.microsoft.com/en-us/azure/copilot/manage-agents-preview | | Query Defender EASM attack surface insights with Azure Copilot | https://learn.microsoft.com/en-us/azure/copilot/query-attack-surface | | Understand responsible AI and data use in Azure Copilot | https://learn.microsoft.com/en-us/azure/copilot/responsible-ai-faq | ### Configuration | Topic | URL | |-------|-----| | Configure Cosmos DB storage for Azure Copilot conversations | https://learn.microsoft.com/en-us/azure/copilot/bring-your-own-storage | ### Integrations & Coding Patterns | Topic | URL | |-------|-----| | Author Azure API Management policies using Copilot | https://learn.microsoft.com/en-us/azure/copilot/author-api-management-policies | | Generate Kubernetes YAML for AKS with Azure Copilot | https://learn.microsoft.com/en-us/azure/copilot/generate-kubernetes-yaml | | Create Terraform and Bicep configurations with Azure Copilot | https://learn.microsoft.com/en-us/azure/copilot/generate-terraform-bicep |
Related in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
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plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.