Developed and delivered a cross-backend search quality benchmarking feature for the tobi/qmd repository, introducing a new CLI command that evaluates search performance across BM25, vector, hybrid, and full-pipeline backends. The solution measures key metrics such as precision@k, recall, MRR, F1, and latency using user-provided fixture files, enabling comprehensive regression testing to maintain search quality after code or configuration changes. Implemented primarily in TypeScript and JavaScript, this work established a repeatable benchmarking workflow that supports pull request reviews and release planning, enhancing backend development, testing, and benchmarking practices within the project’s continuous integration and quality assurance processes.