![dotNET Skills]()
Microsoft has announced .NET Skills, a new initiative aimed at improving how AI coding assistants handle .NET development tasks. The feature introduces a repository called dotnet/skills, which packages specialized knowledge and workflows that AI coding agents can use to perform common development tasks more effectively.
The goal is to give AI assistants—such as coding agents used in IDEs and command-line tools—better context about the .NET ecosystem so they can produce more reliable code and developer guidance.
What Are Agent Skills?
An agent skill is essentially a lightweight package that contains task-specific knowledge, instructions, and supporting resources that an AI coding assistant can access while solving a problem.
Instead of relying solely on a model’s pre-training, skills provide structured context that helps the AI:
Understand developer intent
Follow established engineering patterns
Execute complex workflows with fewer errors
Each skill bundles instructions, metadata, and optional resources, enabling coding agents to discover and apply the right expertise automatically when working on a task.
The dotnet/skills Repository
With this release, Microsoft is publishing a collection of official skills created by the .NET team based on the workflows they use internally while developing the platform.
These skills encode patterns that Microsoft engineers have already tested in real engineering scenarios, helping AI agents solve common .NET problems without relying on generic prompts.
The idea is simple: rather than asking an AI assistant vague questions, developers can rely on curated skills that guide the agent through proven development practices.
Supported AI Coding Tools
The .NET Skills system is designed to work across multiple AI development tools that support the Agent Skills specification, including:
This cross-tool compatibility allows the same skills to enhance coding assistants regardless of which AI platform a developer prefers.
Measuring Whether Skills Actually Help
Microsoft says it is also experimenting with evaluation systems to measure the effectiveness of each skill.
For every new skill added to the repository, the team runs automated tests comparing the performance of an AI agent with and without the skill enabled. This helps determine whether the additional context actually improves results.
The evaluation approach works similarly to unit testing, where each skill is validated independently before being recommended to developers.
Installing .NET Skills
Developers can install the skills directly into compatible coding agents using plugin marketplaces.
For example, in a compatible CLI environment, developers can register the repository as a plugin source and install specific skills from it.
This approach allows developers to add capabilities incrementally instead of loading every possible skill into the AI’s context.
Source: Microsoft