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timesfm-forecasting

An AI agent skill from google-research/timesfm, scored 80 out of 100 by code.

80/ 100B

Code score by group

  • Spec18/20
  • Description10/20
  • Procedure13/15
  • Done criteria15/15
  • Resources9/10
  • Scripts3/8
  • Safety7/7
  • Upkeep5/5

It loses the most points in Description (10), the group that checks whether the description says what the skill does and when to use it.

What the author says it does

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.…

This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.

Repository
google-research/timesfm
Folder
timesfm-forecasting
License
Apache-2.0
GitHub stars
35,426
SKILL.md lines
512
Other files
28

Add timesfm-forecasting to your agent

npx skills add google-research/timesfm --skill timesfm-forecasting

The command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.

Labelled for

Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.