A novel multi-agent document analysis framework that prioritizes preservation of conceptual distinctions rather than text compression. Unlike conventional summarization, which often collapses subtle boundaries, the system uses specialized agents—such as a Nitpicker, Skeptic, and Admissibility Auditor—to analyze documents from complementary perspectives. Its primary output is a distinction ledger identifying non-equivalent concepts, formally represented as (X \neq Y).
Implemented as a lightweight Unix shell pipeline, the architecture minimizes information loss by allowing agents to operate in parallel rather than through recursive summarization. The resulting distinction-centered analysis reconstructs the logical structure of a document, supporting more precise reasoning, retrieval, and critique. Preliminary experiments show that the framework can automatically extract dozens of unique conceptual boundaries from a single text segment.
Inference as Constraint Closure
Cosmological Observables Without Expansion: A Scalar-Vector-Entropy Field Theory of Redshift, Luminosity Distance, and the Hubble Tension