deepinit

To generate AI context documentation for a large codebase, deepinit creates hierarchical AGENTS.md files that mirror your repository structure and clarify component relationships for agent navigation. It maps directories by depth and produces parent-resolved files with validated links.

Repository onboarding context for AI agents is best provided through standardized AGENTS.md templates. Deepinit generates these files to describe directory purpose, key files, subdirectories, and specific agent working or testing guidance across the entire codebase.

You create hierarchical AGENTS.md files across directories by running deepinit, which maps your repository structure and plans generation by directory depth. It produces navigable parent references and validates hierarchy links to prevent broken connections across submodules.

You can preserve manually added documentation sections during codebase documentation regeneration. Deepinit isolates and maintains your manual notes while regenerating automated sections, ensuring custom working guidance is not overwritten during repository mapping updates.

Generating AI-readable repository maps with deepinit does require YAML frontmatter-based skill activation. This mechanism ensures the hierarchical mapping process correctly initializes and produces valid AGENTS.md files with standardized structural templates.

Standardized AGENTS.md files provide hierarchical directory documentation with parent references for navigable context, unlike isolated code comments. Deepinit ensures consistent AI-readable context across directories and submodules, clarifying how components relate for agent workflows.