databricks-cost-tuning

The skill aims to implement cost optimization for Databricks environments via policy, spot-usage, and monitoring tooling. Its data flows and operational footprint are largely internal to Databricks, with no evident credential theft, arbitrary code execution, or external data exfiltration. The footprint is broadly coherent with its stated purpose, though there are minor concerns about configuration drift across multiple languages/formats and potential ambiguity in cloud-provider specifics. Overall, the security posture remains BENIGN with MEDIUM risk due to operational complexity and potential misconfigurations affecting cost and availability rather than security.