Developed AI tooling configuration for the kotest/kotest repository, focusing on enabling AI coding assistants to generate contributions that align with established architectural patterns. The work involved creating project-specific configuration files and comprehensive documentation in Kotlin and Markdown, detailing conventions such as spec styles and MatcherResult usage. By integrating AI-aware artifacts and updating repository rules, the developer facilitated safer, more efficient AI-assisted development without introducing build-breaking changes. This approach reduced review friction and improved onboarding for new contributors, ensuring that AI-generated code adheres to project standards while maintaining repository stability. No major bugs were addressed during this period.