Natural Language Generation (NLG) systems can make data accessible in an easily digestible textual form; but using such systems requires sophisticated linguistic and sometimes even programming knowledge. We have designed and implemented an environment for creating and modifying NLG templates that requires no programming knowledge, and can operate with a minimum of linguistic knowledge. It allows specifying templates with any number of variables and dependencies between them. It internally uses an existing sentence realization NLG tool in order to provide the linguistic background knowledge. We tested the performance and usability of our system in the context of interactive simulation games. We incrementally improved our system in order to obtain all the capabilities needed to reproduce all the sentences and templates manually created for already existing games. We trained the users and measured their satisfaction with the system by comparing the results of writing new games' narrative content manually vs. using our system. In general, the use of the system made the task faster, more enjoyable, and less prone to errors. (Contains 4 tables and 2 figures.)