demand-forecasting-engine
AI-powered demand prediction skill using historical data, market signals, and external factors for improved forecast accuracy
npx skills add a5c-ai/babysitter --skill demand-forecasting-engine --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.
# Demand Forecasting Engine ## Overview The Demand Forecasting Engine is an AI-powered skill that generates accurate demand predictions using historical data, market signals, and external factors. It employs multiple forecasting methods including time series analysis and machine learning models to improve forecast accuracy and support inventory planning decisions. ## Capabilities - **Time Series Forecasting (ARIMA, Prophet, etc.)**: Apply classical and modern time series methods for demand prediction - **Machine Learning Demand Models**: Use ML algorithms to capture complex demand patterns and relationships - **Promotional Lift Modeling**: Incorporate promotional calendar and estimate promotional demand lift - **External Factor Integration (Weather, Events)**: Include weather, events, and economic indicators in forecasts - **Forecast Accuracy Measurement**: Track and report forecast accuracy using standard metrics (MAPE, bias, etc.) - **Demand Sensing with POS Data**: Incorporate point-of-sale data for short-term demand adjustments - **New Product Forecasting**: Generate forecasts for new products using analogous items or market research ## Tools and Libraries - Prophet - statsmode
- Overview
- Capabilities
- Tools and Libraries
- Used By Processes
- Usage
- Integration Points
- Performance Metrics
What does the demand-forecasting-engine skill do?
AI-powered demand prediction skill using historical data, market signals, and external factors for improved forecast accuracy
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill demand-forecasting-engine --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.