forecasting-time-series-data

Quick Review

The skill provides a clear conceptual overview of time series forecasting with good structural organization and relevant examples. However, it lacks critical implementation details needed for actual execution: no concrete code scripts, no specification of which forecasting libraries to use, no data format requirements, and no model training procedures. The description mentions ARIMA and Prophet models but provides no guidance on how to implement them. A CLI agent would understand WHAT to do but not HOW to do it. The novelty is moderate - while time series forecasting is valuable, the skill as documented doesn't provide sufficient automation or technical depth to meaningfully reduce token costs compared to a general-purpose AI assistant handling these requests directly.