One thing worth designing around, from having automated a lot of model work.
A model asked to perform a stat check will usually produce a plausible number rather than compute one, and it will report that it applied a rule when it did not. If a single pass both resolves the check and writes the prose, the prose tends to get decided first and the arithmetic back filled to match. The version that holds is to keep the roll and the state change outside the model, hand it the resolved outcome, and let it only narrate.
Same for permanent deletion. If the inventory lives in the transcript then nothing is really deleted, it is just further up the context, and it comes back eventually. It has to live somewhere the model can read but not rewrite.
Good luck with the release.
Appreciate the deep dive. You are 100% correct about the autoregressive trap—if an LLM generates prose first, it will backfill the arithmetic to justify whatever narrative it just hallucinated.
That is exactly why Grinmar's architecture forces the [SYSTEM CALC] bracket to generate at the absolute top of the response. By forcing the model to compute the physical difficulty threshold against the S.I.I.N.S. matrix before it emits a single narrative token, the attention mechanism is locked into the mechanical pass/fail state. The math dictates the prose, not the other way around.
As for inventory state deletion, that is handled by the strict HUD Injection Protocol. Because the engine forces the [STATUS LEDGER] to render at the bottom of every single turn, it leverages the recency bias of transformer models. When an item is consumed, the engine is mandated to explicitly overwrite that slot with [Empty]. The model prioritizes the most recent ledger in the context window over older transcript data. And for the rare moments when context drift does occur, the Monolith Edition utilizes diegetic reality fractures to force the player to manually re-verify the state without breaking immersion.
External Python wrappers and API state-machines are great for dedicated software, but the engineering challenge here was building a zero-friction, zero-install architecture that runs natively inside a vanilla chat window