ToolMisuseBench: An Offline Deterministic Benchmark for Tool Misuse and Recovery in Agentic Systems

TL;DR

ToolMisuseBench is a comprehensive offline benchmark designed to evaluate tool misuse and recovery in agentic systems, addressing operational failures with fault injection and detailed metrics.

Contribution

It introduces a new deterministic benchmark, dataset, and evaluation pipeline for assessing tool misuse and recovery in various environments.

Findings

Schema aware methods improve fault-specific recovery.

Overall success remains limited under strict authorization and failure settings.

Benchmark covers CRUD, retrieval, file, and scheduling environments.

Abstract

Tool using agents often fail for operational reasons even when language understanding is strong. Common causes include invalid arguments, interface drift, weak recovery, and inefficient retry behavior. We introduce ToolMisuseBench, an offline deterministic benchmark for evaluating tool misuse and recovery under explicit step, call, and retry budgets. The benchmark covers CRUD, retrieval, file, and scheduling environments with replayable fault injection. It reports success, invalid call behavior, policy violations, recovery quality, and budgeted efficiency. We release a public dataset with 6800 tasks and a reproducible evaluation pipeline. Baseline results show fault specific recovery gains for schema aware methods, while overall success remains limited under the released authorization and hard failure settings.