A new multimodal dataset for clinical gait analysis has been published, featuring data from patients undergoing total knee arthroplasty. The dataset includes motion capture data in two forms: full-body 3D keypoint trajectories from the markerless SIMI Motion system, and SMPL-based parametric body models derived through post-processing. It also contains detailed clinical gait assessments from experts, available in the original German and an English translation. The dataset provides partial longitudinal coverage with pre- and post-operative recordings at six weeks for a subset of patients. Existing datasets lacked combinations of motion trajectories with expert clinical assessment, with some focusing only on spatiotemporal parameters or using healthy participants imitating pathological gait. The new dataset supports exploratory research in gait analysis, anomaly detection, and motion generation or understanding models, and is suited for proof-of-concept studies and early-stage investigations of gait.