EdgeGen extracts compliance rules from agent policy documents and generates database-grounded rule-violating tasks, lifting finetuning mean progress by 2% to 42% on the tau2-bench airline domain and improving Gemma-4-e4b harness optimization by 30% over the base harness
EdgeGen automatically extracts compliance rules from an agent's policy document, enumerates combinations of rule violations, and grounds each scenario in executable database states via a scenario-aware SQL agent, admitting tasks only after data-grounding and scenario-feasibility checks; combined with a synthetic database generation method it forms a fully automated closed loop requiring no human annotation, yielding a 2% to 42% mean progress improvement from finetuning on the tau2-bench airline domain while some baselines degrade for some models, and harness optimization improving 10% and 30% over human-curated and base harnesses for Gemma-4-e4b.