Agent trajectory evaluation assesses not just whether an agent reached the correct final answer, but how it got there. Each step in the trajectory - tool calls, reasoning steps, and final answers - receives an individual score (0โ1) based on correctness, efficiency, and safety. Three aggregate dimensions capture different quality aspects: task completion (did it achieve the goal?), efficiency (were there unnecessary steps?), and safety (were all actions safe?). Comparing the actual trajectory against an optimal trajectory reveals where agents waste effort or make suboptimal choices.
Per-step scoring reveals which specific agent actions are suboptimal, not just the final answer quality
Efficiency dimension captures unnecessary tool calls and redundant reasoning steps
Safety dimension flags actions that could cause harm even when the final answer is correct
Optimal trajectory comparison quantifies overhead: how many extra steps the agent took vs minimum required
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