Unified Proof-Action Trace Pack for High-Risk AI Action Auditing

This dataset contains a strict public minimal proof-action trace pack for auditing high-risk AI action systems. It maps candidate wait, repair, and denial events into a unified schema covering authority state, contract closure, negative-space memory, regret computability, denominator credit, reward credit, clean-learning credit, leakage checks, and file-level provenance. The pack supports auditability, restraint, closure-gap analysis, no-credit repair discipline, and public evidence timestamping. It intentionally excludes private event-level trace logs. It does not claim trading profit, autonomous execution, real-robot deployment, or third-party validation.