Feasibility of a Signal Temporal Logic (STL) specification asks whether, from a given initial state, an admissible control input can satisfy its continuous-time requirements under actuator limits. Establishing feasibility is essential for detecting unrealizable tasks and repairing specifications before execution. State-of-the-art Mixed-Integer Linear Programming (MILP) methods face growing model sizes as temporal horizons and formula complexity increase, and can accept control witnesses that violate continuous-time STL semantics between samples. We propose a geometric approach to STL feasibility and temporal repair that translates temporal requirements into spatial constraints evaluated at the initial state. Its compiled feasibility check is independent of horizon length for fixed compiled dimensions. We prove nonnegative continuous robustness under a joint controller assumption. On 6D UAV benchmarks, median geometric repair times are 0.265--1.510 ms; we show up to 1.68x10^4 speedup over MILP feasibility checker. All geometric runs pass continuous STL validation, whereas majority of completed MILP control witnesses violate continuous-time STL.

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