UREA: Read Like a Chemist, Commit Like a Compiler

The chemical literature is written to be read by chemists: reactions are distributed across schemes, tables, captions, and procedures, and faithful extraction has resisted automation. UREA (UREA Reaction Extracting Agent) is an agentic framework for such multimodal reading: a general-purpose vision-language model cross-references figures with procedures, zooms into regions at will, and maintains a compound ledger, while a deterministic chemistry compiler resolves shared definitions into structured records. The workflow combines structural validation, one-label-one-structure authoring, count reconciliation, and evidence pointers. Reading stays permissive; commitment makes its decisions explicit and checkable. Count reconciliation addresses silent truncation, where whole-document reading returns well-formed output covering only a fraction of a paper's reactions: the agent inventories experiments up front, reconciles its records against that inventory, and revisits shortfalls. We also audit and correct the benchmark's reference annotations; UREA achieves state-of-the-art 89.73 hard-match F1 on the corrected whole-document chemical reaction benchmark. The design transfers across model families and agent harnesses, and the largest observed performance swing in the ablations follows a change in reasoning effort. Adapted through task-specific prompts to standalone molecular recognition, the reader outperforms MinerU.Chem under author review on 500 development images. Together, these results motivate a design pattern that combines flexible reading with explicit, checkable records for domains where structured knowledge must stay faithful to source documents.