Repo-level rules files can stop AI coding agents from writing low-quality code

AI coding agents tend to produce code that compiles and passes tests but still contains poor practices such as untyped errors, swallowed exceptions, and brittle tests tied to implementation details. The fix, according to a developer guide, is not a better model but structured rules files placed directly in the repository, such as .cursor/rules/*.mdc for Cursor or CLAUDE.md for Claude Code. These files use plain markdown with YAML frontmatter to scope rules by file type and load them automatically into every agent session, with concise 40-line files proving far more effective than lengthy ones. A recommended discipline contract includes a verification ladder, a failure protocol that forces the agent to stop and revert after repeated mistakes, and specific TypeScript rules banning the use of 'any' and empty catch blocks. Typed exhaustiveness checks and behavior-driven testing standards are also suggested to convert potential runtime bugs into compile-time errors the agent cannot silently bypass.