rlm-processing

You can analyze large codebases exceeding token limits by externalizing context into a REPL-based loader, then chunking and filtering files to apply Recursive Language Model patterns for semantic analysis.

A Recursive Language Model pattern for code analysis uses an llm_query interface to break large repository reasoning into focused semantic sub-tasks, enabling cross-file tracing and dependency mapping across interdependent modules.

You need external context management when a project requires correlating multiple interdependent files, locating cross-cutting concerns across modules, or performing wide-scale auditing that exceeds standard LLM context windows.

Trace cross-cutting concerns across multiple modules by loading interconnected files into a REPL context loader, applying file-chunking strategies, and using the llm_query interface to execute focused pattern discovery and dependency mapping.

No, this code analysis approach requires a REPL-based context loader to externalize files and an llm_query interface to perform semantic sub-tasks, as the workflow depends on chunking and processing code outside the LLM context.

Limitations of using RLM patterns for large codebase analysis include the strict requirement for a REPL-based context loader and llm_query interface, meaning it cannot operate on raw files directly without external context management infrastructure.