We focus on how to generate well-written texts to describe an object from a database, and propose several strategies that are needed in generation stages. To build reliable generation rules, we performed corpus analysis through annotating descriptive texts. This paper also describes an implemented text generation system called XExplainer, which can dynamically produce a description of an object in Korean. XExplainer was applied to two domains — a home shopping database and a business administration database — to show that it can be applied to any domain as long as the information is provided in the required format. The Generated texts were evaluated by humans using several criteria, such as content completeness, structural coherence, expression conciseness, and text layout.