CED as a python module for coherence in complex system

We present a validated Python implementation of the Category Error Detector (CED) as a portable, self-contained diagnostic module. The CED scans any system—AI, simulation, or theoretical model—for structural misalignment across five nodes: Axes, Interface, Projection, Lagrangian, and Attractors. The module is lightweight, system-agnostic, and includes a self-assessment that proves its own coherence axiomatically. We provide the full source code, validation results, and guidelines for integration into larger computational workflows.