Forecasting Time Series Data

jeremylongshore/claude-code-plugins-plus-skills

This one handles time series forecasting using ARIMA and Prophet models to predict future values from historical data. It analyzes trends, seasonality, and autocorrelation, then trains a model and spits out predictions with confidence intervals. You'd reach for this when forecasting sales, predicting traffic patterns, or analyzing stock price trends. The skill automates model selection based on data characteristics, which saves you from manually testing different approaches. It's practical for business forecasting scenarios where you need quick predictions without building a custom pipeline, though you'll want clean data going in since garbage data means garbage forecasts regardless of the model.

skills.sh installs: 170
GitHub stars: 2.6K
last updated: Aug 21, 2026

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Install

$ npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill forecasting-time-series-data --agent claude-code

Installs into .claude/skills of the current project.

Files

Time Series Forecaster

Forecast future values from historical time series data using ARIMA, Prophet, and other models with trend, seasonality, and confidence interval analysis.

Overview

This skill empowers Claude to perform time series forecasting, providing insights into future trends and patterns. It automates the process of data analysis, model selection, and prediction generation, delivering valuable information for decision-making.

How It Works

Data Analysis: Claude analyzes the provided time series data, identifying key characteristics such as trends, seasonality, and autocorrelation.
Model Selection: Based on the data characteristics, Claude selects an appropriate forecasting model (e.g., ARIMA, Prophet).
Prediction Generation: The selected model is trained on the historical data, and future values are predicted along with confidence intervals.