There is an increasing need for automatic and objective surgical skill assessment methods to make the surgeon training process more effective. We studied an automatic skill assessment system based on the surgical instrument tip trajectories extracted from cadaveric trans-nasal endoscopic sinus surgery videos. We proposed a tracking algorithm by combining a segmentation-based instrument tip detector and Kalman filter. For surgical skill assessment, we explored four new motion-related metrics. The proposed method has been tested with 10 surgery videos from 4 experts and 5 trainees and shown its potential for the automatic surgical skill assessment.