databricks-performance-tuning

The skill presents a cohesive and coherent footprint for its stated purpose of Databricks performance tuning. It uses well-scoped capabilities (cluster sizing, Spark config tuning, Delta optimization, query analysis, and caching/join strategies) and does not rely on unverifiable binaries or credential harvesting. Data access appears limited to legitimate Databricks resources (cluster config, query history, Delta table metadata). Overall risk is low-to-medium with respect to security, appropriate for a developer tooling guide aimed at performance optimization.