Parity/coherence failure protocol The model runs without errors but output is wrong. Scalar taps hide directional bugs, and each new tap costs a full recompile. Build a per-layer tensor-dump comparator first. Every later check becomes a numpy read from disk. Use this skill when MAX output disagrees with a PyTorch reference you can run and hook. The primary case is a custom-architecture port that serves but fails parity or coherence checks. The same protocol covers a quantized variant of a working port, a multi-GPU conversion of a working single-GPU port, and a regression after a MAX upgrade.…