However, this methodology suggests an underlying strategy or optimization in place. The utilization of a cache could be indicative of efforts to enhance efficiency or performance within the system's architecture. It may also point towards considerations for scaling, where direct enumeration might not be as feasible or efficient when dealing with a larger volume of data or in scenarios requiring repeated access to certain data elements.

This approach could potentially reduce the computational overhead associated with direct enumeration, especially if script validation jobs are resource-intensive or if the inputs in question are required by multiple jobs. By fetching inputs from a cache, the system might be leveraging cached data to minimize redundancy in data processing and retrieval, thereby optimizing the overall validation process.

Moreover, this method may offer benefits in terms of data consistency and integrity, particularly in distributed systems where inputs might change during the validation phase. Utilizing a cache as an intermediary storage layer could help ensure that all script validation jobs operate on the same version of input data, thus maintaining consistency across the validation process.

In essence, while the practice of fetching inputs from a cache, instead of direct enumeration post-parsing for block validation, may appear counterintuitive at first glance, it likely serves specific operational or architectural purposes aimed at enhancing efficiency, performance, and consistency within the system.