About
The Eval Gap Finder is a specialized workflow tool designed for developers working with the AILANG substrate to bridge the performance gap between standard Python execution and AI-native reasoning. It automates the process of running comparative evaluations, categorizing failure modes—such as syntax errors, type unification failures, or logic gaps—and iteratively improving model prompts or language specifications. By providing structured analysis and automated testing of examples, it ensures that AI models achieve high success rates in domain-specific languages by identifying exactly where documentation or language features are lacking.
