← All skills
timesfm-forecasting
75 / 100 · Review before installing
Check before installing. Some of what it can do is expected: a marketing skill usually talks to online services.
By mkurman/zorai (GitHub) · marketing · 327 stars · scanned at commit 8ea1fc3
Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.
Works with any agent that supports SKILL.md skills.
What this skill can do
Runs commands on your computer
The author does not mention this.
Found in 9 places.
Show 6 more
Downloads and installs other software
The author does not mention this.
Found in 14 places.
Show 11 more
- skills/scientific-skills/timesfm-forecasting/SKILL.md, line 43
pip install torch>=2.0.0 --index-url https://download.pytorch.org/whl/cu121 - skills/scientific-skills/timesfm-forecasting/SKILL.md, line 46
pip install torch>=2.0.0 --index-url https://download.pytorch.org/whl/cpu - skills/scientific-skills/timesfm-forecasting/SKILL.md, line 49
pip install torch>=2.0.0 # MPS support is built-in - skills/scientific-skills/timesfm-forecasting/SKILL.md, line 660
5. **TimesFM 2.5 required for `forecast_with_covariates()`** -- TimesFM 1.0 does NOT have this method. Install `pip install timesfm[xreg]` and use checkpoint `g - skills/scientific-skills/timesfm-forecasting/examples/covariates-forecasting/demo_covariates.py, line 7
TimesFM 2.5 + `pip install timesfm[xreg]`. - skills/scientific-skills/timesfm-forecasting/examples/covariates-forecasting/demo_covariates.py, line 411
pip install timesfm[xreg] - skills/scientific-skills/timesfm-forecasting/examples/global-temperature/README.md, line 138
uv pip install "timesfm[torch]" matplotlib pandas numpy - skills/scientific-skills/timesfm-forecasting/references/system_requirements.md, line 148
| jax | Flax backend | `pip install jax[cuda]` | - skills/scientific-skills/timesfm-forecasting/references/system_requirements.md, line 149
| flax | Flax backend | `pip install flax` | - skills/scientific-skills/timesfm-forecasting/references/system_requirements.md, line 150
| scikit-learn | XReg covariates | `pip install scikit-learn` | - skills/scientific-skills/timesfm-forecasting/scripts/check_system.py, line 373
detail=f"{pkg_name} is not installed. Run: uv pip install {pkg_name}",
Connects to the internet
The author does not mention this. Expected for a marketing skill.
Found in 1 place.
Safer alternatives
Low-risk skills in the same category (marketing) that look related. Check that one does what you need.
Install
Paste this into your terminal. It downloads exactly the version we scanned, not whatever is newest.
if [ -e ~/.agents/skills/'timesfm-forecasting' ] || [ -L ~/.agents/skills/'timesfm-forecasting' ]; then echo 'A skill folder named timesfm-forecasting already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/mkurman/zorai' "$d" && git -C "$d" checkout --quiet '8ea1fc3ae126b6e103b8508bacd8f5aa60b6f4ad' -- 'skills/scientific-skills/timesfm-forecasting' && mkdir -p ~/.agents/skills && cp -R "$d"/'skills/scientific-skills/timesfm-forecasting' ~/.agents/skills/'timesfm-forecasting' && rm -rf "$d"; fi
Codex reads ~/.agents/skills directly. For Claude Code, Cursor, Copilot, Gemini CLI, Antigravity or OpenCode, also link it. For Claude Code: ln -s ~/.agents/skills/'timesfm-forecasting' ~/.claude/skills/'timesfm-forecasting' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.
Badge for your README
The badge for mkurman/zorai shows the score of its lowest-scoring skill.
[](https://zalavijaysinh.github.io/skilltrust/repos/mkurman/zorai/)
Score history
| Date | Version | Score |
|---|
| 2026-11-13 | 8ea1fc3 | 75 |