Use for time-series tasks: forecasting (demand, sales, energy, finance), time-series classification, and anomaly detection over time (sensors, logs, monitoring). Picks classical vs ML vs deep forecasters, enforces temporal splits (no future leakage), and uses proper time-series metrics/backtesting. Triggers on 'forecast', 'predict next/future', 'time series', 'demand/sales/energy prediction', 'anomaly detection over time', 'seasonality'.
How to install domain-time-series?
mxslr/mlcraft/domain-time-series
$npx -y skills add mxslr/mlcraft --skill domain-time-seriesInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/mxslr/mlcraft" --skill "mxslr/mlcraft/domain-time-series"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/mxslr/mlcraft" that are relevant to the current task. Run `npx skills add "https://github.com/mxslr/mlcraft"` and select the relevant skills, then follow their instructions.
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