EvolveTool-Bench: Evaluating the Quality of LLM-Generated Tool Libraries as Software Artifacts
- URL: http://arxiv.org/abs/2604.00392v1
- Date: Wed, 01 Apr 2026 02:21:55 GMT
- Title: EvolveTool-Bench: Evaluating the Quality of LLM-Generated Tool Libraries as Software Artifacts
- Abstract summary: We introduce EvolveToolBench, a diagnostic benchmark for tool libraries in software engineering.<n>We define library-level software quality metrics -- reuse, redundancy, composition success, regression, and safety.<n>We show that systems with similar task completion differ by up to 18% in library health, revealing software quality risks invisible to task-only evaluation.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Modern LLM agents increasingly create their own tools at runtime -- from Python functions to API clients -- yet existing benchmarks evaluate them almost exclusively by downstream task completion. This is analogous to judging a software engineer only by whether their code runs, ignoring redundancy, regression, and safety. We introduce EvolveTool-Bench, a diagnostic benchmark for LLM-generated tool libraries in software engineering workflows. Across three domains requiring actual tool execution (proprietary data formats, API orchestration, and numerical computation), we define library-level software quality metrics -- reuse, redundancy, composition success, regression stability, and safety -- alongside a per-tool Tool Quality Score measuring correctness, robustness, generality, and code quality. In the first head-to-head comparison of code-level and strategy-level tool evolution (ARISE vs. EvoSkill vs. one-shot baselines, 99 tasks, two models), we show that systems with similar task completion (63-68%) differ by up to 18% in library health, revealing software quality risks invisible to task-only evaluation. Our results highlight that evaluation and governance of LLM-generated tools require treating the evolving tool library as a first-class software artifact, not a black box.
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