Recent applications for distributed mobile devices, including multimedia video/audio streaming, typically process streams of incoming data in a regular, predictable way. The behavior of these applications during runtime can be accurately predicted most of the time by analyzing the data to be processed and annotating the stream with the information collected. We introduce an annotation-based approach to power-quality trade-offs and demonstrate its application on CPU frequency scaling during video decoding, for an improved user experience on portable devices. Our experiments show that up to 50% of the power consumed by the CPU during video decoding can be saved with this approach.