[2604.04131] Profile-Then-Reason: Bounded Semantic Complexity for Tool-Augmented Language Agents

Computer Science > Artificial Intelligence arXiv:2604.04131 (cs) [Submitted on 5 Apr 2026] Title:Profile-Then-Reason: Bounded Semantic Complexity for Tool-Augmented Language Agents Authors:Paulo Akira F. Enabe View a PDF of the paper titled Profile-Then-Reason: Bounded Semantic Complexity for Tool-Augmented Language Agents, by Paulo Akira F. Enabe View PDF HTML (experimental) Abstract:Large language model agents that use external tools are often implemented through reactive execution, in which reasoning is repeatedly recomputed after each observation, increasing latency and sensitivity to error propagation. This work introduces Profile--Then--Reason (PTR), a bounded execution framework for structured tool-augmented reasoning, in which a language model first synthesizes an explicit workflow, deterministic or guarded operators execute that workflow, a verifier evaluates the resulting trace, and repair is invoked only when the original workflow is no longer reliable. A mathematical formulation is developed in which the full pipeline is expressed as a composition of profile, routing, execution, verification, repair, and reasoning operators; under bounded repair, the number of language-model calls is restricted to two in the nominal case and three in the worst case. Experiments against a ReAct baseline on six benchmarks and four language models show that PTR achieves the pairwise exact-match advantage in 16 of 24 configurations. The results indicate that PTR is particularly eff...