The paper discusses a prototype module for on-line checking of term consistency in a workbench for knowledge-based Machine Aided Human Translation (MAHT). We present the linguistic resources and the knowledge base (KB) of the system as well as their place in the processes. To discover missing or misleading translations, the checker relies on the lexicon information and the hierarchy in the KB. To detect comprehension difficulties, the module checks ambiguities in the target text by resolving anaphora. The module design is based on the assumption that in aligned parallel texts some types of difficulties to resolve anaphora could be used to find wrong, missing and/or cognitively difficult translations. The paper explains the algorithms for checking term consistency. An evaluation of the approach and prospects for further work conclude the paper.