Privacy-Preserving Inconsistency Measurement

The project is a specialized academic research artifact sitting at the intersection of symbolic AI (formal logic) and cryptography (SMPC). With 0 stars and 3 forks after nearly a year (322 days), it has no market traction or developer community. Its defensibility is low (2/10) because the value lies in the mathematical proofs and algorithm design rather than the code itself, which serves as a non-performant reference implementation. Frontier labs (OpenAI, Anthropic) are currently focused on neural-network-based uncertainty and 'hallucination' metrics rather than formal symbolic inconsistency, making the risk from those labs low. The primary 'competitors' are general-purpose SMPC frameworks like OpenMined or Zama, which could implement these specific logic-based metrics if a demand ever materialized. The project's niche nature (measuring inconsistency in symbolic knowledge bases) restricts its utility to very specific enterprise or academic use cases where agents with formal rule sets need to collaborate without trust.