Technology Selection
Guides technology selection and implementation of AI and ML features in .NET 8+...
Install
npx skills add dotnet/skills --skill technology-selection -g -a claude-code -y- Repository
- dotnet/skills5.8k
- Category
- Data and ML
- Updated
- 3d ago
- License
- MIT
- Context cost
- Mediumabout 1,877 tokens
- Runs scripts
- No, instructions only
What it does
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).
.NET AI and Machine Learning
Pick the right technology first, then deliver only what the task asks for. If the task asks for a plan, comparison, or architecture (or says "do not write code"), produce that, do not scaffold, build, or run code unprompted.
Step 1: Classify the task (decision tree)
State which branch applies and why, then choose that technology.
