Why would one consider indexing validators? Reuse.
The value of reuse seems obvious for structural and semantic specification, i.e. schemas and controlled vocabularies – there is opportunity to perceive two datasets as aligned. But, this alignment is only indicated, not necessarily validated.
Two datasets, A and B, are stated to both conform to schema S. If you wish to verify this, what do you do? You apply a validator V to both. Therefore, it seems that if the same validator V is already stated to have been successfully applied to both datasets A and B in order to verify conformance to S, you will have higher confidence in proceeding to analysis without applying validation yourself, or at least without insisting on comprehensive, compute-intensive validation by default.
A given schema-specification validator may also be relatively sophisticated and transform an input dataset to conform more tightly to the specification, as per Postel’s Law, making it even more valuable to reuse unambiguously identified validators as part of data-integration workflows.
Validators may be composed, e.g. conjunctively as attribute/predicate specs are in Datomic, encouraging granular reuse. However, one could not naively employ conformers-as-validators in such a scheme unless they formed a commutative semigroup (mutually rectifying robustness – Postel would approve!).