arXiv AI By Amir H. Rezaeian, Weiyi Sun, Yassine Benajiba, Dan Roth

Prefix Executability: Evaluating Tool-Using Agents Beyond Final Success

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The paper introduces prefix executability, a trajectory-level evaluation protocol for tool-using agents that checks whether every prefix of a predicted tool-call sequence remains executable under tool schemas, state preconditions, and data dependencies. It defines metrics such as Prefix Executability Curves, First-Error Depth, Trajectory Executability Rate, horizon-normalized AUC-PEC, and Recovery Rate to quantify reliability. Experiments on BFCL-v3, ToolSandbox, and $ au^3$-bench show that agents can achieve high final success while having low trajectory executability, revealing failure modes that final success metrics miss, and demonstrate that explicit pre-execution plan checking can improve prefix-level reliability without sacrificing terminal success.

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arXiv AI
1d ago

Agent Harness Awareness: Turning Verified Telemetry into Operational Control for Tool-Using Agents

Agent Harness Awareness addresses the gap between tool descriptions and real‑time operational suitability by having the host provide a verified, up‑to‑date state snapshot before an agent dispatches an action. In controlled benchmarks, this approach cut observable policy regret by nearly 97 % and boosted single‑dispatch completion from 69.4 % to 95.8 %. In live, fault‑injected tests, verified state eliminated excess operational cost and achieved 100 % completion across all model‑by‑fault scenarios.

By Manu Agrawal, Shrey Nagpal