A prototype energy signal tool is demonstrated for operational whole-building and system-level energy use evaluation. The purpose of the tool is to give a summary of building energy use which allows a building operator to quickly distinguish normal and abnormal energy use. Toward that end, energy use status is displayed as a traffic light, which is a visual metaphor for energy use which is substantially different from expected (red and yellow lights) or more or less the same as expected (green light). Which light to display for a given energy end-use is determined by comparing expected energy use to actual energy use. As expected energy use is necessarily uncertain, we cannot choose the appropriate light with certainty. Instead the energy signal tool chooses the light by minimizing the expected cost of displaying the wrong light. The expected energy use is represented by a probability distribution. Energy use is modeled by a low-order lumped parameter model. Uncertainty in energy use is quantified by a Monte Carlo exploration of the influence of model parameters on energy use. Distributions over model parameters are updated over time via Bayes' theorem. The simulation study is devised to assess whole building energy signal accuracy in the presence of uncertainty and faults at the submetered level, which may lead to tradeoffs at the whole building level not detectable without submetering. Published by Elsevier Ltd.