harness-setup

To standardize AI agent documentation, you can scaffold a unified .docs directory structure and root index files like AGENTS.md and CLAUDE.md. This establishes a single source of truth for deterministic documentation management and AI instruction delivery.

Setting up an AI context harness for a monorepo involves generating a unified .docs directory structure alongside root context files. This maintains a single source of truth for AI agents while allowing for app-specific instructions in multi-application environments.

Yes, AI documentation scaffolding applies to both single-application and multi-application monorepo environments. It ensures consistent AI instruction delivery and enforces a separation of concerns between project source code and AI-managed artifacts.

You separate project source code from AI-managed artifacts by scaffolding a dedicated .docs directory structure and root index files. This enforces deterministic documentation management and keeps local-only inbox handling isolated from core source files.

A unified documentation directory structure for AI agents solves the fragmentation of design, context, and implementation instructions. It automatically generates root context files to ensure all team members and AI agents share the same project knowledge base.

Yes, you can use harness-setup to onboard an existing codebase by running it in the current directory to instantly initialize the standard AI documentation harness. This automatically generates the .docs directory structure and root context files like AGENTS.md.