Add license to agent files (#568)

plugins/dotnet-ai/skills/mcp-csharp-create/SKILL.md

@@ -9,6 +9,7 @@ description: >
   DO NOT USE FOR: debugging or running existing servers (use mcp-csharp-debug), writing tests
   (use mcp-csharp-test), publishing or deploying (use mcp-csharp-publish), building MCP
   clients, non-.NET MCP servers.
+license: MIT
 ---
 
 # C# MCP Server Creation

plugins/dotnet-ai/skills/mcp-csharp-debug/SKILL.md

@@ -9,6 +9,7 @@ description: >
   protocol messages, configuring logging for stdio and HTTP servers.
   DO NOT USE FOR: creating new MCP servers (use mcp-csharp-create), writing automated tests
   (use mcp-csharp-test), publishing or deploying to production (use mcp-csharp-publish).
+license: MIT
 ---
 
 # C# MCP Server Debugging

plugins/dotnet-ai/skills/mcp-csharp-publish/SKILL.md

@@ -11,6 +11,7 @@ description: >
   DO NOT USE FOR: publishing general NuGet libraries (not MCP-specific), general Docker
   guidance unrelated to MCP, creating new servers (use mcp-csharp-create), debugging
   (use mcp-csharp-debug), writing tests (use mcp-csharp-test).
+license: MIT
 ---
 
 # C# MCP Server Publishing

plugins/dotnet-ai/skills/mcp-csharp-test/SKILL.md

@@ -9,6 +9,7 @@ description: >
   creating evaluations for MCP servers, writing eval questions, measuring tool quality.
   DO NOT USE FOR: testing MCP clients (this is server testing only), load or performance
   testing, testing non-.NET MCP servers, debugging server issues (use mcp-csharp-debug).
+license: MIT
 ---
 
 # C# MCP Server Testing

plugins/dotnet-ai/skills/technology-selection/SKILL.md

@@ -1,6 +1,7 @@
 ---
 name: technology-selection
 description: "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)."
+license: MIT
 ---
 
 # .NET AI and Machine Learning