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AI Agent2026
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.NET Agent Skills

A curated collection of reusable 'skills' that let LLM-driven coding agents perform common .NET/C# tasks — build diagnosis, debugging, testing, data access, upgrades, MAUI, and AI/ML workflows. Implements the Agent Skills standard and is published for agent marketplaces (Copilot CLI, Claude Code, Cursor).

Introduction

Most agent ecosystems fail at predictable developer tasks because those agents lack small, well-scoped primitives that reliably perform language- and framework-specific work. This collection provides that missing layer for the .NET world: packaged, testable skills that let an LLM-based agent reason about and act on .NET code, builds, diagnostics, and migrations while exposing metrics for accuracy and efficiency.

What Sets It Apart
  • Framework-focused skill set: plugins cover MSBuild, NuGet, EF/data access, MAUI, testing, and diagnostics — so agents can call focused operations rather than attempt brittle end-to-end code edits.
  • Agent Skills standard compliance: follows agentskills.io, making skills interoperable across marketplaces and agent runtimes — so teams can reuse the same primitives in Copilot CLI, Claude Code, Cursor, or custom agents.
  • Observability and scoring: a public dashboard tracks accuracy and efficiency per plugin, which helps evaluate which skills are safe to enable in automated flows.
  • Coverage for migration and AI integration: includes upgrade and .NET-AI skills (RAG, LLM integration, ML.NET), meaning agents can handle modernization plus LLM-assisted workflows.
Who it's for + Tradeoffs

Great fit if you build or operate LLM-driven developer workflows for .NET codebases and want modular, auditable agent actions rather than opaque end-to-end edits. It’s also useful for tool integrators who need marketplace-compatible plugins. Look elsewhere if you need turnkey, non-programmatic GUIs for non-developers, or if your stack is not .NET/C# — the repo assumes familiarity with .NET tooling and agent integration patterns, and still requires human review for high-risk code changes.

Where It Fits

Positions itself between low-level LLM prompts and full automation: providing tested, narrow-capability RPC-style skills that reduce hallucination surface and improve repeatability when composing agent workflows for software engineering tasks.

Information

  • Websitegithub.com
  • Authorsdotnet (Microsoft)
  • Published date2026/02/03

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