I’m building Enola, an open-source tool that gives coding agents a structural model of a codebase. I’ve become increasingly interested in what people actually put into their coding agent harness to help agents understand a codebase and keep changes within its architecture. One problem I keep seeing, an agent can make a change that builds and passes written tests, but still introduces a dependency cycle, breaks a layer boundary, or creates an unexpected dependency. We built Enola to avoid this. It builds a deterministic graph of the codebase and exposes it through MCP. Agents can use the graph as context while working, then compare the structure before and after a change and check it against architectural rules. It’s open source: https://github.com/enola-labs/enola For those building coding agent harnesses: what are you using for codebase context and checks beyond tests and linters? Would appreciate feedback, especially from people using coding agents. Is architectural regression something you care about?   submitted by   /u/yellow-llama1 [link]   [comments]