Beyond Function Calling: Benchmarking Tool-Using Agents under Tool-Environment Unreliability

• URL: http://arxiv.org/abs/2606.25819v2
• Date: Sat, 27 Jun 2026 07:38:41 GMT
• Title: Beyond Function Calling: Benchmarking Tool-Using Agents under Tool-Environment Unreliability
• Abstract summary: We introduce ToolBench-X, a benchmark for evaluating agents under recoverable reliability hazards.<n>Starting from clean tool environments, ToolBench-X injects five structured hazard types.<n>Experiments reveal a substantial reliability gap: agents that perform well with reliable tools often fail under recoverable hazards.
• Score: 14.862168786900382
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Large language models are increasingly deployed as agents that solve tasks by interacting with external tool environments. Although recent tool-use benchmarks increasingly cover complex task settings, they still largely assume clean, stable, and trustworthy tool environments, leaving tool-environment unreliability insufficiently examined. We introduce ToolBench-X, a benchmark for evaluating agents under recoverable reliability hazards. ToolBench-X contains executable multi-step tasks across diverse domains and sequential, parallel, and mixed workflows, each paired with deterministic tools and a canonical final answer for automatic evaluation. Starting from clean tool environments, ToolBench-X injects five structured hazard types: Specification Drift, Invocation Error, Execution Failure, Output Drift, and Cross-source Conflict. Crucially, each injected instance remains solvable through at least one valid recovery path, such as retrying, fallback, verification, or cross-checking. Experiments reveal a substantial reliability gap: agents that perform well with reliable tools often fail under recoverable hazards. Further analysis shows that failures are driven less by tool-use volume or inference budget than by limited hazard diagnosis and ineffective recovery. Targeted recovery hints recover many failed tasks, while test-time scaling yields more limited gains. These results suggest that tool-use evaluation should move beyond function-call accuracy toward task completion under unreliable tool environments. The code and data is available at https://github.com/Foreverskyou/ToolBench-X.

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