GitHub Copilot
Browse 34 Agent Skills recorded as compatible with GitHub Copilot.
Compatible skills
Walks an existing AKS cluster from bare to a running AI model: verify cluster, install the AI Runway controller, assess GPUs, pick an inference provider, and deploy a first model.
Reference guidance for instrumenting ASP.NET Core, Node.js, and Python web apps with Azure Application Insights via auto-instrument or manual OpenTelemetry SDK setup.
Router and reference for Azure AI services (AI Search, Speech, OpenAI, Document Intelligence) covering full-text/vector/hybrid search, speech, and OCR via MCP, CLI, and SDKs.
Configures Azure API Management as an AI gateway: token limits, semantic caching, content safety, load balancing, token metrics, and MCP/tool rate limiting via az CLI policies.
Assesses and migrates cross-cloud workloads to Azure (Lambda to Functions, Beanstalk/Heroku to App Service, Fargate/K8s to Container Apps) with reports and code conversion.
Runs Azure compliance and security audits with azqr plus Key Vault expiration checks, classifying findings by priority and proposing remediation across resources and certs.
Router for Azure VM and VMSS tasks: recommend/compare/price sizes, create/provision, troubleshoot connectivity, manage capacity reservations, and Essential Machine Management.
Queries Azure costs, forecasts future spend, and optimizes to reduce waste (orphaned resources, VM rightsizing, storage/Redis tuning) via Cost Management APIs and MCP tools.
Executes deployments for already-prepared apps (azd up/deploy, terraform apply, az deployment) with prerequisite checks, RBAC health verification, and built-in error recovery.
Systematically triages Azure production incidents across App Service, Container Apps, Functions, AKS, and messaging using resource health, logs, and AppLens.
Turns a workload description into an enterprise Azure topology (landing zone, hub-spoke, DR) and generates validated Bicep or Terraform aligned to the Well-Architected Framework.
Scaffolds, modifies, and prepares GitHub Copilot SDK apps for Azure, auto-detecting @github/copilot-sdk markers and orchestrating prepare/validate/deploy with BYOM model config.
Produces a production-ready AKS cluster configuration, separating hard-to-change Day-0 choices (networking, API server) from Day-1 features across security, scaling, and cost.
Assesses existing AKS clusters or local manifests against AKS Automatic safeguards, classifying incompatibilities and generating fix diffs without ever mutating the cluster.
Writes and runs KQL against Azure Data Explorer (Kusto/ADX) for log, telemetry, and time-series analysis, with schema discovery and az CLI fallback.
Diagnoses Azure Event Hubs and Service Bus SDK problems—AMQP link errors, lock loss, idle timeouts, checkpoint resets—mapped to language-specific fixes.
Prepares apps for Azure deployment by writing a mandatory deployment plan, then generating Bicep/Terraform, azure.yaml, and Dockerfiles before handing off to validate and deploy.
Checks and manages Azure service limits and capacity via az quota, mapping ARM types to quota names, comparing regions, and submitting increase requests.
Finds the least-privilege Azure RBAC role for an identity and generates the CLI commands and Bicep to assign it, including custom role definitions when no built-in fits.
Assesses reliability of Azure Functions and App Service apps for zone redundancy, ZRS storage, health probes, and multi-region failover, then drives staged CLI or IaC remediation.
Lists and finds Azure resources across subscriptions and resource groups using Azure Resource Graph KQL, including orphaned resources and tag audits.
Analyzes an Azure resource group and produces a detailed Mermaid architecture diagram plus a markdown report mapping resource relationships, networking, and identity.
Guides Azure Storage operations and decisions across Blob, Files, Queue, Table, and Data Lake, including access tiers, redundancy, lifecycle, and SDK usage.
Assesses and automates Azure workload upgrades between plans, tiers, and SKUs, plus Java SDK modernization and Redis-to-AMR migrations, with idempotent staged steps.
Runs pre-deployment Azure readiness checks—IaC build, RBAC, managed identity, what-if—against the deployment plan, recording proof before allowing the validated status.
Discovers available Azure OpenAI model capacity across all accessible regions and projects, then validates subscription quota and ranks deployment locations.
Interactive guided Azure OpenAI deployment giving full control over version, SKU, capacity, RAI policy, and advanced options, with cross-region fallback and live quota checks.
Unified Azure OpenAI deployment router that detects intent and dispatches to quick preset, full customize, or capacity-discovery modes, with shared project and quota validation.
Provisions Microsoft Entra Agent Identity Blueprints, BlueprintPrincipals, and per-instance agent identities via Graph, wiring OAuth fmi_path token exchange and per-agent permissions.
Guides Microsoft Entra ID app registration, OAuth 2.0 setup, API permissions, client credentials, and MSAL integration via portal, CLI, or Bicep.
Fine-tunes models on Azure AI Foundry with SFT, DPO, or RFT, covering dataset prep and validation, grader calibration, training, checkpoint selection, deployment, and evaluation.
End-to-end Azure AI Foundry agent lifecycle with azd—scaffold, deploy, invoke, evaluate, optimize, fine-tune, and troubleshoot agents—routing to specialized sub-skills per task.
Quickly deploys an Azure OpenAI model to the optimal region by checking capacity across regions and using GlobalStandard SKU with sensible auto-calculated defaults.
Deploys Python Flask, Django, or FastAPI code to Azure App Service Linux with smart defaults, creating the resource group, plan, and web app as needed.