In March 2026, Jmilinovich developed a cross-backend search quality benchmarking feature for the tobi/qmd repository, introducing the qmd bench CLI command. This tool benchmarks search quality across BM25, vector, hybrid, and full-pipeline backends, measuring metrics such as precision@k, recall, MRR, F1, and latency using user-provided fixture files. Built with TypeScript and JavaScript, the solution enables fixture-driven regression testing to ensure search quality remains stable after code or configuration changes. Jmilinovich’s work established a repeatable benchmarking workflow, enhancing backend development, testing, and benchmarking practices while supporting pull request reviews and release planning for the project.