What is tts-studio-pro?

This repository, described in its README as harness-experimental, is a template and toolset for preparing software projects so that AI coding agents can work on them more reliably. The core idea is that most repositories are organized for human developers who already know the codebase, but AI agents typically start each session with only a chat prompt and a snapshot of files. Without additional context, agents tend to edit code before understanding what the product is supposed to do, miss important constraints, and repeat architectural decisions that were already made. The harness addresses this by adding a set of structured documents to a repository. These include an AGENTS.md file that gives an AI agent a stable starting point, a product contract, a feature intake process for classifying how risky a piece of work is, a test matrix that maps expected behaviors to how they should be verified, story packets for breaking large requests into reviewable units, and a decisions folder for recording tradeoffs so future agents inherit them rather than reinventing them. A shell script can install the harness into any existing project directory with a single command. The installer copies the document structure, creates any missing files while leaving existing ones intact in merge mode, and downloads a Rust command-line tool that serves as the main harness interface. The CLI is verified against a checksum during installation. The project is explicitly described as early-stage. There is no application code in the repository itself. The current content is the harness scaffolding only: file templates, the agent operating model, and a small demo that walks through how a product idea moves from a human specification into stories, validation expectations, and implementation work. Contributions the maintainer is looking for include real examples of agent failures caused by missing repository context, harness installs in actual projects, and workflow patterns that work across different AI coding tools.