--- title: "Google Research (@google-research) · skilld" canonical_url: "https://skilld.dev/@google-research" meta: description: "1 skill and 0 collections from @google-research on skilld." "og:description": "Agent skills written by real maintainers in their own GitHub repos, with links to source" "og:title": skilld --- ` ![Google Research on GitHub](https://skilld.dev/_img/avatar?url=https%3A%2F%2Fgithub.com%2Fgoogle-research.png) # **Google Research** @google-research Earth [GitHub](https://github.com/google-research) [Website](https://research.google) ## [google-research/timesfm](https://skilld.dev/gh/google-research/timesfm) 1 skill ![README badge for google-research/timesfm](https://skilld.dev/b/google-research/timesfm?theme=light&label=0) - [timesfm-forecasting](https://skilld.dev/gh/google-research/timesfm) 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. Supports both basic forecasting and advanced covariate forecasting (XReg) with dynamic and static exogenous variables. Automatically checks system RAM/GPU before loading the model, validates dataset fit before processing, 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 and handle your specific dataset. Updated 7 months ago![README badge for google-research/timesfm](https://skilld.dev/b/google-research/timesfm?theme=light&label=0) [Read source](https://github.com/google-research/timesfm/blob/master/timesfm-forecasting/SKILL.md) ## **Curated setups ** Skills grouped for one workflow and installable with one command. ### **No collections yet ** When @google-research publishes a collection, it will appear here. [Browse curators](https://skilld.dev/community)