What problem does it solve? Mathematical modeling competition papers often contain assumptions that are circular, unsupported, overly strong, or disconnected from the actual problem statement. This Skill diagnoses each assumption in a paper's model-assumption section against the complete competition problem, identifying necessity, evidence basis, compatibility, and downstream usability. ## Core Features & Use Cases - Per-Assumption Diagnosis: Classifies each assumption by source (given by problem, reasonably inferred, model-required, or unknown) and rates its reasonableness, necessity, and evidence requirements. - Problem Coverage Check: Verifies that assumptions cover all conditions and core factors explicitly stated in the competition problem, and flags missing candidate assumptions. - Strong Assumption Auditing: Detects unsupported claims about normality, independence, stationarity, linearity, or perfect rationality, and specifies how to verify or downgrade them. - Use Case: A student preparing a mathematical modeling contest paper submits the full problem statement and their assumptions section, then receives a structured report with severity-rated issues, revision priorities, and a mapping of each assumption to where it must be reflected in the model body. ## Quick Start Use the bzd-model-assumption-checker to review my model assumptions section against the attached competition problem statement and list issues with revision suggestions.
