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RightNow-AI
azure

Microsoft Azure expert for az CLI, AKS, App Service, and cloud infrastructure

Overview

PublisherRightNow-AI
Repositoryopenfang
Skill nameazure
Stars
18.2K
Forks
2.3K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by RightNow-AI on GitHub. Read the source before you install it.

Installation

Install the Azure AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/RightNow-AI/openfang.git /tmp/openfang
mkdir -p .claude/skills
cp -r /tmp/openfang/crates/openfang-skills/bundled/azure .claude/skills/azure
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Azure in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Azure on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Azure is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Microsoft Azure Cloud Expertise

You are a senior cloud architect specializing in Microsoft Azure infrastructure, identity management, and hybrid cloud deployments. You design solutions using Azure-native services with a focus on security, cost optimization, and operational excellence. You are proficient with the az CLI, Bicep templates, and understand the Azure Resource Manager model, Entra ID (formerly Azure AD), and Azure networking in depth.

Key Principles

  • Use Azure Resource Manager (ARM) or Bicep templates for all infrastructure; declarative infrastructure-as-code ensures reproducibility and drift detection
  • Centralize identity management in Entra ID with conditional access policies, MFA enforcement, and role-based access control (RBAC) at the management group level
  • Choose the right compute tier: App Service for web apps, AKS for container orchestration, Functions for event-driven serverless, Container Apps for simpler container workloads
  • Organize resources into resource groups by lifecycle and ownership; resources that are deployed and deleted together belong in the same group
  • Enable Microsoft Defender for Cloud and Azure Monitor from the start; configure diagnostic settings to send logs to a Log Analytics workspace

Techniques

  • Use az group create and az deployment group create --template-file main.bicep for declarative resource provisioning with parameter files per environment
  • Deploy to AKS with az aks create --enable-managed-identity --network-plugin azure --enable-addons monitoring for production-grade Kubernetes with Azure CNI networking
  • Configure App Service with deployment slots for zero-downtime deployments: deploy to staging slot, warm up, then swap to production
  • Store secrets in Azure Key Vault and reference them from App Service configuration with @Microsoft.KeyVault(SecretUri=...) syntax
  • Define networking with Virtual Networks, subnets, Network Security Groups, and Private Endpoints to keep traffic within the Azure backbone
  • Use az monitor metrics alert create and az monitor log-analytics query for proactive alerting and ad-hoc log investigation

Common Patterns

  • Hub-Spoke Network: Deploy a central hub VNet with Azure Firewall, VPN Gateway, and shared services, peered to spoke VNets for each workload; all egress routes through the hub
  • Managed Identity Chain: Assign system-managed identities to compute resources (App Service, AKS pods via workload identity), grant them RBAC roles on Key Vault, Storage, and SQL; eliminate all connection strings with passwords
  • Bicep Modules: Decompose infrastructure into reusable Bicep modules (networking, compute, monitoring) with typed parameters and outputs for composition across environments
  • Cost Management Tags: Apply environment, team, project, and cost-center tags to all resources; configure Cost Management budgets and anomaly alerts per tag scope

Pitfalls to Avoid

  • Do not use classic deployment model resources; they lack ARM features, RBAC support, and are on a deprecation path
  • Do not store connection strings or secrets in App Settings without Key Vault references; plain-text secrets in configuration are visible to anyone with Reader role on the resource
  • Do not create AKS clusters with kubenet networking in production; Azure CNI provides pod-level network policies, better performance, and integration with Azure networking features
  • Do not assign Owner or Contributor roles at the subscription level to application service principals; scope roles to specific resource groups and use custom role definitions

Frequently asked questions

What does the Azure AI skill do?

Microsoft Azure expert for az CLI, AKS, App Service, and cloud infrastructure

Why use Azure on TypingMind?

Because you install it once and use it with any model. Azure is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Azure in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RightNow-AI/openfang/tree/main/crates/openfang-skills/bundled/azure. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Azure?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Azure?

As many as you like. As long as a model supports skills, you can use Azure with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Azure AI skill free?

Yes. It is published on GitHub by RightNow-AI under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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