Ramya Shree developed a production-ready audit prompt for BigQuery pipelines in the github/awesome-copilot repository, focusing on cost safety, idempotency, and production readiness. She designed a structured evaluation framework that enables data engineers to assess Python and BigQuery scripts for efficiency and safe deployment. Her approach emphasized reducing operational costs and improving pipeline reliability by guiding users through best practices. Ramya updated the project documentation to clearly outline the new prompt’s usage, supporting faster adoption of safe production standards. The work demonstrated practical application of data engineering principles, leveraging BigQuery, Python, and prompt design to address real-world deployment challenges.