time-series-forecaster
Time series forecasting skill for business metric prediction and demand planning
Profile →npx skills add a5c-ai/babysitter --skill time-series-forecaster --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Time Series Forecaster ## Overview The Time Series Forecaster skill provides comprehensive capabilities for predicting business metrics over time using classical statistical methods, machine learning, and deep learning approaches. It supports automated model selection, ensemble forecasting, and uncertainty quantification for robust business planning. ## Capabilities - Classical methods (ARIMA, ETS, Theta) - Machine learning methods (XGBoost, LightGBM for time series) - Deep learning methods (Prophet, N-BEATS, Temporal Fusion Transformer) - Ensemble forecasting - Prediction interval generation - Forecast accuracy metrics (MAPE, RMSE, MASE) - Anomaly detection - Seasonality decomposition ## Used By Processes - Predictive Analytics Implementation - KPI Framework Development - Market Sizing and Opportunity Assessment ## Usage ### Data Input ```python # Time series data configuration time_series_data = { "target": "monthly_revenue", "datetime_column": "date", "frequency": "M", # Monthly "data": [ {"date": "2023-01-01", "value": 1000000, "marketing_spend": 50000}, {"date": "2023-02-01", "value": 1050000, "marketing_spend": 55000}, # ... more data ], "exogenous_variables": ["marketing_s
- Overview
- Capabilities
- Used By Processes
- Usage
- Data Input
- Model Configuration
- Seasonality Analysis
- Model Selection Guide
- Accuracy Metrics
- Input Schema
- Output Schema
- Best Practices
- Integration Points
What does the time-series-forecaster skill do?
Time series forecasting skill for business metric prediction and demand planning
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill time-series-forecaster --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.