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Automating technical documentation for a legacy codebase is achieved by scanning directory structures and detecting technology stacks to generate architecture overviews, API contracts, and source tree analyses automatically.

Resuming a deep-dive codebase analysis is fully supported because the workflow tracks progress via state files and JSON reports, ensuring resumability across sessions without losing context.

Python 3 is required to generate architecture overviews for brownfield projects, as it handles the workflow resolution and script execution needed to analyze the directory structures.

Updating documentation after a full rescan of an existing project is handled natively by initiating a rescan update, which re-evaluates the technology stack and refreshes the technical docs while maintaining state.

Automated project analysis handles complex brownfield technology stacks by intelligently detecting project types within the directory structure and generating relevant documentation tailored to the discovered stack.

Exhaustive deep-dive analysis should be used instead of an initial project scan when you need to document specific modules in detail, rather than just generating a high-level architecture overview of the entire codebase.