tuning-hyperparameters

The skill's described capabilities are coherent with its stated purpose: it generates and executes hyperparameter tuning workflows using standard ML libraries and reports results. It relies on well-known registries for dependencies and does not indicate access to sensitive credentials. Minor risks include potential unbounded compute in shared environments and lack of explicit per-step user approvals for long-running tasks. Overall, the footprint is proportionate to the task and does not reveal obvious malicious patterns.