codebase-onboarding

To generate onboarding documentation, analyze the codebase structure, core modules, and entry points, then map the discovered data to a structured template to output a ready-to-use docs/onboarding.md file. This automates the extraction of architecture and tech stack details for new team members.

The best way to document a project's tech stack is to scan dependency files like package.json, pyproject.toml, and go.mod, alongside top-level directories like src or lib. This captures the technical architecture and maps it directly into an onboarding template for new developers.

Yes, codebase documentation generation applies to diverse projects and languages. It scans top-level directories and configuration files like Dockerfile, go.mod, and package.json to identify the tech stack and structure, regardless of the specific programming language used.

To create an onboarding.md file that omits irrelevant sections, map codebase findings to the structured onboarding template while automatically skipping sections that lack information. This ensures the generated documentation only includes verified architecture and module details.

Yes, you can extract entry points and core modules from a repository automatically by scanning the codebase structure. The process identifies key files and directories, summarizes the architecture, and feeds the findings into an onboarding document template.