Although conventional dynamic surface filters can eliminate the issue of complexity explosion in backstepping design, the convergence of filter errors significantly influences the overall control performance. This paper proposes a unified design framework of an event-triggered adaptive fuzzy design scheme with fixed-time performance for unmodeled strict-feedback nonlinear systems, where the tracking performance, filter error, and parameter learning convergence are considered simultaneously. The unified framework guarantees the smoothness of all the closed-loop signals. A novel dynamic surface filter is designed to avoid the repeated differentiation of recursive virtual control while the filter error converges in fixed time. Compared with the conventional backstepping design, the proposed adaptive fuzzy controller design in this paper can guarantee fixed-time tracking performance. An event-triggered condition with intermittent feedback is developed to decrease the computational and communication burden. Two simulation examples are provided to validate the effectiveness of the unified fixed-time framework.