Formalizing literature-review construction as a compositional and recursive operator system

Producing a long literature review requires a system to find relevant papers, organize their evidence, write individual sections, and combine those sections without losing the link between claims and sources. We present , a workflow that divides this process into nine operators. Each operator has a defined input, output, and responsibility, so its implementation can be replaced and evaluated independently. We test the design in four ways. First, we recover section trees from 2,221 scholarly reviews and show that their organization can be distinguished from closely matched artificial alternatives. Second, citation data trains an effective paper ranker, and section data supports recognition of common organization patterns. Third, controlled replacements show that evidence-aware organization and validation improve 1,000-word reviews. Fourth, when every method receives the same 32 evidence cards, hierarchical writing and integration outperform naive chunking, a fixed outline, and flat generation on all six long-form topics. These results show that explicit operator interfaces support both controlled experimentation and higher-quality long-form synthesis.