Domain-Specific Languages, apart from the design and formal definition aspects involved to build, also require Model-to-Text (M2T) transformations to generate executable code. Authoring the M2T templates is a manual, labor-intensive process that often generates frustrating, time consuming errors. And, although Large Language Models have advanced code and grammar generation, the automated synthesis of downstream Model-to-Text templates still remains largely unaddressed. In the context of software engineering and model-driven development, automating such transformations addresses a core challenge in modern software toolchain construction. This paper presents a work-in-progress multi-agent system that automatically generates production-ready Jinja2 templates from a textX grammar, natural language requirements and sample model instances. The architecture decomposes the generation task into seven stages orchestrated by eleven specialized agents, employing deterministic runtime introspection to provide ground-truth structural data. To ensure reliability, the generation process is coupled with a rigorous three-level deterministic validation loop that evaluates template syntax, rendering execution and target-language correctness without relying on self-assessment by the language models. We demonstrate the pipeline on two structurally versatile domains, specifically a recursive calculator and a declarative smart home automation language, illustrating its ability to produce functional templates, rendered code and test artifacts across diverse grammar paradigms.