TNA Agent Specification v1

The TNA Agent Specification v1 defines the architectural and operational requirements for an autonomous system capable of structural reconstruction, expansion, and evaluation across diverse knowledge domains. By integrating the TNA Core Language, Interpreter Layer, Reconstruction Protocol, and Benchmark Suite, the agent functions as an executable epistemic architecture designed to generate novel, domain-consistent expansions by systematically confronting structural limits. The agent's modular design—comprising an Interpreter, Boundary Engine, Expansion Engine, Evaluator, and Memory—enables it to map complex systems into TNA representations and trigger iterative expansion loops when boundary pressure (FB) is detected. Operating in specialized modes such as Reconstruction, Exploratory, and Stress Mode, the agent facilitates continuous, self-driven learning that is structural rather than statistical. This framework shifts the paradigm of AI intelligence from optimizing fixed objectives to the active expansion of domains when internal logic fails. Ultimately, the TNA Agent serves as an AI-native foundation for non-terminal evolution and cross-domain theoretical unification.