timesfm-forecasting

SKILL.md

TimesFM Forecasting

Overview

TimesFM (Time Series Foundation Model) is a pretrained decoder-only foundation model
developed by Google Research for time-series forecasting. It works zero-shot — feed it
any univariate time series and it returns point forecasts with calibrated quantile
prediction intervals, no training required.

This skill wraps TimesFM for safe, agent-friendly local inference. It includes a
mandatory preflight system checker that verifies RAM, GPU memory, and disk space
before the model is ever loaded so the agent never crashes a user's machine.

Key numbers: TimesFM 2.5 uses 200M parameters (~800 MB on disk, ~1.5 GB in RAM on
CPU, ~1 GB VRAM on GPU). The archived v1/v2 500M-parameter model needs ~32 GB RAM.
Always run the system checker first.

When to Use This Skill