ToolGate: Contract-Grounded and Verified Tool Execution for LLMs

Fuente: arXiv
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Autori principali: Liu, Yanming, Peng, Xinyue, Cao, Jiannan, Wang, Xinyi, Deng, Songhang, Chen, Jintao, Yin, Jianwei, Zhang, Xuhong
Natura: Preprint
Pubblicazione: 2026
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author Liu, Yanming
Peng, Xinyue
Cao, Jiannan
Wang, Xinyi
Deng, Songhang
Chen, Jintao
Yin, Jianwei
Zhang, Xuhong
author_facet Liu, Yanming
Peng, Xinyue
Cao, Jiannan
Wang, Xinyi
Deng, Songhang
Chen, Jintao
Yin, Jianwei
Zhang, Xuhong
contents Large Language Models (LLMs) augmented with external tools have demonstrated remarkable capabilities in complex reasoning tasks. However, existing frameworks rely heavily on natural language reasoning to determine when tools can be invoked and whether their results should be committed, lacking formal guarantees for logical safety and verifiability. We present \textbf{ToolGate}, a forward execution framework that provides logical safety guarantees and verifiable state evolution for LLM tool calling. ToolGate maintains an explicit symbolic state space as a typed key-value mapping representing trusted world information throughout the reasoning process. Each tool is formalized as a Hoare-style contract consisting of a precondition and a postcondition, where the precondition gates tool invocation by checking whether the current state satisfies the required conditions, and the postcondition determines whether the tool's result can be committed to update the state through runtime verification. Our approach guarantees that the symbolic state evolves only through verified tool executions, preventing invalid or hallucinated results from corrupting the world representation. Experimental validation demonstrates that ToolGate significantly improves the reliability and verifiability of tool-augmented LLM systems while maintaining competitive performance on complex multi-step reasoning tasks. This work establishes a foundation for building more trustworthy and debuggable AI systems that integrate language models with external tools.
format Preprint
id arxiv_https___arxiv_org_abs_2601_04688
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle ToolGate: Contract-Grounded and Verified Tool Execution for LLMs
Liu, Yanming
Peng, Xinyue
Cao, Jiannan
Wang, Xinyi
Deng, Songhang
Chen, Jintao
Yin, Jianwei
Zhang, Xuhong
Computation and Language
Artificial Intelligence
Formal Languages and Automata Theory
Large Language Models (LLMs) augmented with external tools have demonstrated remarkable capabilities in complex reasoning tasks. However, existing frameworks rely heavily on natural language reasoning to determine when tools can be invoked and whether their results should be committed, lacking formal guarantees for logical safety and verifiability. We present \textbf{ToolGate}, a forward execution framework that provides logical safety guarantees and verifiable state evolution for LLM tool calling. ToolGate maintains an explicit symbolic state space as a typed key-value mapping representing trusted world information throughout the reasoning process. Each tool is formalized as a Hoare-style contract consisting of a precondition and a postcondition, where the precondition gates tool invocation by checking whether the current state satisfies the required conditions, and the postcondition determines whether the tool's result can be committed to update the state through runtime verification. Our approach guarantees that the symbolic state evolves only through verified tool executions, preventing invalid or hallucinated results from corrupting the world representation. Experimental validation demonstrates that ToolGate significantly improves the reliability and verifiability of tool-augmented LLM systems while maintaining competitive performance on complex multi-step reasoning tasks. This work establishes a foundation for building more trustworthy and debuggable AI systems that integrate language models with external tools.
title ToolGate: Contract-Grounded and Verified Tool Execution for LLMs
topic Computation and Language
Artificial Intelligence
Formal Languages and Automata Theory
url https://arxiv.org/abs/2601.04688