Agentic AI Act gap checker reaches 0.831 F1 against 0.533 for the best baseline
Compliance officers collect questionnaires on how high-risk AI systems are built, then must work out which controls are missing. This framework uses a taxonomy of gaps such as accuracy, robustness, logging and human oversight; one agent extracts gaps and a second ranks fixes from a catalog. Across 9 AI systems it scores a gap-type F1, a balance of precision and recall, of 0.831 versus 0.533 for the strongest baseline.