Generative AI for Beginners .NET is a hands-on course that teaches .NET developers to build applications using generative AI models and related tools. Its lessons use practical samples covering scenarios such as chat, audio transcription, agents, and local AI. The catalogue entries are add-ons associated with the course repository.
Borrowing it
Nothing to install: this file belongs to microsoft/Generative-AI-for-beginners-dotnet. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/Generative-AI-for-beginners-dotnet/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/microsoft/Generative-AI-for-beginners-dotnetWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/microsoft/generative-ai-for-beginners-dotnet/copilot-instructions)<a href="https://agentmods.dev/instructions/microsoft/generative-ai-for-beginners-dotnet/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/microsoft/generative-ai-for-beginners-dotnet/copilot-instructions/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/microsoft/generative-ai-for-beginners-dotnet/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/microsoft/generative-ai-for-beginners-dotnet/copilot-instructions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01390 | $0.01390 |
| Opus 5.5 | $0.00556 | $0.00556 |
| Sonnet 5.5 | $0.00278 | $0.00278 |
| Haiku 4.5 | $0.00139 | $0.00139 |
Grade A, and why
Generative-AI-for-beginners-dotnet copilot-instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copilot Instructions for Generative-AI-for-beginners-dotnet
Project Purpose & Structure
- This repo is a hands-on .NET course for Generative AI, focused on real-world, runnable code and live coding.
- Lessons are organized in numbered folders (
01-IntroductionToGenerativeAI/through05-ResponsibleAI/), each with areadme.mdfor documentation. - All code samples live in the centralized
samples/directory, organized by category:CoreSamples/,MAF/,AppsWithGenAI/,PracticalSamples/. - Key technologies: .NET 10+, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework, Azure OpenAI, Ollama (local models).
- Multi-language support: see
translations/for localized docs.
Architecture & Patterns
- Each lesson folder contains documentation; code samples are in
samples/(e.g.,samples/AppsWithGenAI/SpaceAINet/demonstrates full-stack AI integration). - Samples are organized under
samples/by category:CoreSamples/,MAF/,AppsWithGenAI/,PracticalSamples/. - AI model calls are always abstracted behind service classes (e.g.,
SpaceAINet.GameActionProcessor), enabling easy provider swapping and testability. - API keys and endpoints are never hardcoded—use user secrets or environment variables (see lesson READMEs for details).
- For SpaceAINet and similar apps:
- AI providers (Ollama, Azure OpenAI) are toggled at runtime via key bindings.
- Game state is sent to the AI model, which returns a JSON action and explanation.
- Screenshots and FPS toggles are built-in for debugging and demonstration.
Developer Workflows
- Code Formatting (Required Before Each Commit):
- Run
dotnet formatbefore committing any changes to ensure proper C# code formatting and style - Ensure all code builds with
dotnet buildand passes tests withdotnet test - Verify formatting with
dotnet format --verify-no-changesif linting is enabled
- Run
- Build & Run:
- Use standard .NET CLI:
dotnet build,dotnet runfrom the relevant project folder (e.g.,cd samples/AppsWithGenAI/SpaceAINet/SpaceAINet.Console). - For local AI: ensure Ollama is running and the required model is pulled (e.g.,
ollama pull phi4-mini). - For Azure: set secrets via
dotnet user-secretsor Codespaces secrets.
- Use standard .NET CLI:
- Switching AI Providers:
- Most samples support toggling between local (Ollama) and cloud (Azure OpenAI) models at runtime (see app key bindings and README tables).
- Codespaces:
- Dev containers are pre-configured for .NET, Azure, and Ollama workflows. Choose the right container for your use case.
- Testing:
- Run sample apps in the
samples/directory to verify model integration and workflow.
- Run sample apps in the
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 88 lines · 1,390 tokens per session scan A ab7f9ef8d02c
Generative-AI-for-beginners-dotnet copilot-instructions.md is an instructions file published in the GitHub repository microsoft/Generative-AI-for-beginners-dotnet (3,136 stars, last pushed 3d ago), licensed MIT. It adds 1,390 tokens to every session, about $0.0056 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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