How to Build AI Evals for Tool-Calling Agents
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Directly addresses building evals for tool-calling agents, a core need for AI agent development.
Summary
Building an eval suite for tool-calling agents requires testing decisions, not just output. Mastra enables layered evals with deterministic quick checks, trajectory scorers for tool-call sequences, and LLM-as-a-judge graders, all runnable in CI via Vitest. Unlike traditional unit tests, agent behavior is non-deterministic, so evals must average scores across multiple runs to measure typical performance.