skUnit lets .NET developers test AI agents using behavior, not exact text

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Testing AI agents is difficult because correct responses can vary widely in wording, making traditional assertion-based unit tests unreliable. Developer Mehran Davoudi built skUnit, an open-source testing framework for .NET, to address this by verifying agent behavior through semantic conditions rather than exact string matches. The framework uses Markdown files to describe conversation scenarios and evaluates whether responses satisfy intent-based assertions, such as confirming no food was suggested to an angry user. A demo project called Moody Chef, which recommends food based on a user's mood, illustrates two architectural approaches and serves as a practical walkthrough for the framework. skUnit also supports running each test scenario multiple times to reduce false positives caused by non-deterministic model outputs.

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