reversa-archaeologist

To extract module-level intent from legacy code, analyze control flow, algorithms, data structures, and metadata configurations. This process resolves modules into clear, audit-defensible technical documentation by uncovering configuration intent and main functions.

The best way to generate audit-ready documentation is performing module-by-module reverse analysis to extract parameters, return values, conditionals, loops, and error handling, producing field-level data dictionaries for audit defense.

Yes, you can generate Mermaid flowcharts and data dictionaries from source code by setting the doc_level parameter. This enables field-level documentation for entities and DTOs, including types, required or optional status, and defaults.

Document control flow and algorithms by analyzing each module to extract main functions, methods, and exception handling. This creates consolidated code-analysis markdown files and structured module JSON artifacts for downstream use.

Yes, you need a plan file enumerating target modules and a surface JSON file providing scout context. The analysis reads these configurations to ensure consistent excavations and deterministic artifact generation.

A key limitation is that data dictionary generation and per-function Mermaid flowcharts are optional outputs controlled by the doc_level state configuration, meaning detailed field-level documentation requires explicitly enabling higher documentation levels.