{"skill":{"slug":"cud-advisor","displayName":"Cud Advisor","summary":"Recommend optimal GCP Committed Use Discount portfolio (spend-based vs resource-based) with risk analysis","tags":{"latest":"1.0.0"},"stats":{"comments":0,"downloads":317,"installsAllTime":0,"installsCurrent":0,"stars":0,"versions":1},"createdAt":1772735088561,"updatedAt":1777525644377},"latestVersion":{"version":"1.0.0","createdAt":1772735088561,"changelog":"- Initial release of gcp-cud-advisor skill.\n- Provides guidance on selecting optimal GCP Committed Use Discount (CUD) types (spend-based vs resource-based) for compute workloads with risk analysis.\n- Supports evaluation for Compute Engine, GKE, and Cloud Run workloads.\n- Users provide exported data (utilization reports, usage history, or billing export); no direct access or credentials required.\n- Outputs clear CUD recommendations with savings estimates, coverage gaps, SUD interaction, and risk scenarios.\n- Includes updated rules for 2025: Cloud Run and GKE Autopilot are now CUD-eligible.","license":null},"metadata":null,"owner":{"handle":"anmolnagpal","userId":"publishers:anmolnagpal","displayName":"Anmol Nagpal","image":"https://avatars.githubusercontent.com/u/4303310?v=4"},"moderation":null}