SpecKV introduces a lightweight controller that dynamically selects speculation length per step using draft model confidence and entropy signals (~0.56 correlation with acceptance rate). Achieves 56.0% improvement over fixed-gamma=4 baseline with only 0.34ms overhead across 5,112 step-level records. Demonstrates that compression level and speculation length are coupled dimensions requiring joint optimization.