The AgentLens benchmark moves beyond binary pass/fail metrics to evaluate the entire execution path of coding agents. It combines formal verification with LLM-written reviews to diagnose how models use tools and recover from errors. This approach provides developers with readable explanations for failures. Practitioners can now pinpoint specific behavioral flaws rather than guessing from a score.