Appinsights Instrumentation

OrganizationPopular

microsoft

appinsights-instrumentation

Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.

Overview

Publisher	microsoft
Repository	`azure-skills`
Skill name	`appinsights-instrumentation`
Stars	1.5K
Forks	246
Bundled files	11
License	MIT
Links	Skill source Repository

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.
11 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by microsoft on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/microsoft/azure-skills.git /tmp/azure-skills
mkdir -p .claude/skills
cp -r /tmp/azure-skills/skills/appinsights-instrumentation .claude/skills/appinsights-instrumentation

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Appinsights Instrumentation 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 Appinsights Instrumentation 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 Appinsights Instrumentation 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.

AppInsights Instrumentation Guide

This skill provides guidance and reference material for instrumenting webapps with Azure Application Insights.

⛔ ADDING COMPONENTS?

If the user wants to add App Insights to their app, invoke azure-prepare instead. This skill provides reference material—azure-prepare orchestrates the actual changes.

When to Use This Skill

User asks how to instrument (guidance, patterns, examples)
User needs SDK setup instructions
azure-prepare invokes this skill during research phase
User wants to understand App Insights concepts

When to Use azure-prepare Instead

User says "add telemetry to my app"
User says "add App Insights"
User wants to modify their project
Any request to change/add components

Prerequisites

The app in the workspace must be one of these kinds

An ASP.NET Core app hosted in Azure
A Node.js app hosted in Azure

Guidelines

Collect context information

Find out the (programming language, application framework, hosting) tuple of the application the user is trying to add telemetry support in. This determines how the application can be instrumented. Read the source code to make an educated guess. Confirm with the user on anything you don't know. You must always ask the user where the application is hosted (e.g. on a personal computer, in an Azure App Service as code, in an Azure App Service as container, in an Azure Container App, etc.).

Prefer auto-instrument if possible

If the app is a C# ASP.NET Core app hosted in Azure App Service, use AUTO guide to help user auto-instrument the app.

Manually instrument

Manually instrument the app by creating the AppInsights resource and update the app's code.

Create AppInsights resource

Use one of the following options that fits the environment.

Add AppInsights to existing Bicep template. See examples/appinsights.bicep for what to add. This is the best option if there are existing Bicep template files in the workspace.
Use Azure CLI. See scripts/appinsights.ps1 for what Azure CLI command to execute to create the App Insights resource.

No matter which option you choose, recommend the user to create the App Insights resource in a meaningful resource group that makes managing resources easier. A good candidate will be the same resource group that contains the resources for the hosted app in Azure.

Modify application code

If the app is an ASP.NET Core app, see ASPNETCORE guide for how to modify the C# code.
If the app is a Node.js app, see NODEJS guide for how to modify the JavaScript/TypeScript code.
If the app is a Python app, see PYTHON guide for how to modify the Python code.

SDK Quick References

OpenTelemetry Distro: Python | TypeScript
OpenTelemetry Exporter: Python | Java

Platform-Specific Guides

Container Apps: Observability Guide

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Appinsights Instrumentation AI skill do?

Why use Appinsights Instrumentation on TypingMind?

Because you install it once and use it with any model. Appinsights Instrumentation 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 Appinsights Instrumentation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/azure-skills/tree/main/skills/appinsights-instrumentation. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Appinsights Instrumentation?

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 Appinsights Instrumentation?

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

Is the Appinsights Instrumentation AI skill free?

Yes. It is published on GitHub by microsoft under the MIT 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

AppInsights Instrumentation Guide

When to Use This Skill

When to Use azure-prepare Instead

Prerequisites

Guidelines

Collect context information

Prefer auto-instrument if possible

Manually instrument

Create AppInsights resource

Modify application code

SDK Quick References

Platform-Specific Guides

Bundled files

Frequently asked questions

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