An intelligent help system needs to take into account the user's knowledge when formulating answers. This allows the system to provide more concise answers, because it can avoid telling users things that they already know. Since these concise answers concentrate exclusively on pertinent new information, they are also easier to understand. Information about the user's knowledge also allows the system to take advantage of the user's prior knowledge in formulating explanations. The system can provide better answers by referring to the user's prior knowledge in the explanation (e.g., through use of similes). This process of refining answers is called answer expression. The process of answer expression has been implemented in the UCExpress component of UC (UNIX Consultant), a natural language system that helps the user solve problems in using the UNIX operating system. UCExpress separates answer expression into two phases: pruning and formatting. In the pruning phase, subconcepts of the answer are pruned by being marked as already known by the user (and hence do not need to be generated), or marked as candidates for generating anaphora or ellipsis (since they are part of the conversational context). In the formatting phase, UCExpress uses information about the user's prior domain knowledge to select among specialized expository formats, such as similes and examples, for expressing information to the user. These formats allow UCExpress to present different types of information to the user in a clear, concise manner. The result of UCExpress' answer expression process is an internal form that a tactical level generator can easily use to produce good English.