AI agents are transforming industries, but improving agent decision-making remains a challenge. Traditional debugging methods struggle to decode agent behavior as they operate in "black boxes", making tool selections without clear reasoning. Structured evaluations and data-driven diagnostics are needed to assess performance and refine decision-making.