mcpbeat

Timesfm Forecasting

christophacham/timesfm-forecasting

> Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Automatically checks system RAM/GPU before loading the model, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model. For classical statistical time series models (ARIMA, SARIMAX, VAR) use statsmodels; for time series classification/clustering use aeon.

119k tokens
context cost
the whole folder, loaded on every use
27
files
ships runnable scripts
1
copies elsewhere
how many repositories repackaged it
73
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/christophacham/agent-skills-library --skill timesfm-forecasting

Repackaged in 1 other repositories

same content, different owner
agent-skills-hub/agent-skills-hub open on GitHub →

How to use it

Copy the folder

Take christophacham/timesfm-forecasting from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip, uv. Without those the skill loads but fails at the first command.