Coding Agents Harness - Codebase context and quality

I’m building Enola, an open-source tool that gives coding agents a structural model of a codebase. I am now obsessed in understanding what harness people use to gain better understanding of codebase and ensuring its quality. What I have observed is that agents are good at writing code, but they can make changes that pass tests while introducing problems such as dependency cycles, broken layer boundaries, or unexpected dependencies. (They are introducing technical debt). So.. We decided to control that with Enola by building a deterministic graph of the codebase and exposing it to agents through MCP. The graph serves two purposes: give the agent architectural context while it works, and compare the structure before and after a change against defined rules. Curious how others are handling codebase context and architectural checks in their coding agent harnesses.