LLM Poker Calculator Passes Math Check but Fails on Unconfirmed User Assumption

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A developer tested a poker-analysis framework where a large language model acts as an input layer, interpreting natural-language questions and routing them to deterministic local calculators that handle all arithmetic. Across 25 hand-authored test cases, the system was evaluated on whether calculator results remained auditable and numerically verified after the LLM proposed typed inputs. In one key failure case, a Japanese-language query stated 'the pot is 150,' which was ambiguous about whether the figure included the opponent's bet or not. The LLM silently assumed the pre-bet pot was 150, logged the assumption internally, and the calculator correctly returned 20% required equity — but the user had never confirmed that interpretation, meaning a different reading would have yielded 25%. The experiment highlights a specific engineering gap: verified arithmetic does not guarantee a correct outcome when the LLM resolves input ambiguity without seeking user confirmation.

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