This paper explores the semantics of Tumato 2.0, a constraint-based planning framework, through the lens of Linear Temporal Logic (LTL). Tumato enables the generation of policies for autonomous agents, ensuring safe and robust goal-oriented behavior. The framework guarantees that critical safety constraints hold across all potential outcomes of non-deterministic actions, while pre-computed policies eliminate the need for runtime decision-making. By translating Tumato’s language constructs into LTL, we formalize its approach to handling safety, liveness, and robustness properties. This contribution offers a foundation for reliable agent behavior under real-world uncertainties, as well as improved interpretability. We further demonstrate the semantics of Tumato’s specification language through a case study, demonstrating how LTL guides system specification and supports potential formal verification efforts. These contributions align with key challenges in engineering intelligent and multi-agent systems, focusing on safety, correctness, and robust operation within complex environments. Overall, this work emphasizes the importance of declarative approaches in delivering reliable solutions for real-world applications.