timesfm-forecasting SKILL.md skillA
timesfm-forecasting from jzkk720/cubecloud-skills-bundle-kit is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jzkk720/cubecloud-skills-bundle-kit/timesfm-forecasting@v1.0.0Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jzkk720/cubecloud-skills-bundle-kit
- Path
upstream/timesfm-forecasting/SKILL.md- Versions recorded
- 1
- Latest version
- v1.0.0, committed Sep 15, 2026
- Size
- 18,897 bytes
- Repository stars
- 4
- License
- a license file GitHub does not identify
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…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 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 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 the 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 Use this skill when: - Forecasting **any univariate time series** (sales, demand, sensor, vitals, price, weather) - You need **zero-shot forecasting** without training a custom model - You want **probabilistic forecasts** with calibrated prediction intervals (quantiles) - You have time series of **any length** (the model handles 1–16,384 context points) …
Read the whole file at its exact version.
How to install
mdr add jzkk720/cubecloud-skills-bundle-kit/timesfm-forecasting@sha256:cb83b741010d9f14The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_hoo7rc2qk3v6at5a)
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Versions
The registry has recorded 1 version of this file, committed on Sep 15, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (18897 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jzkk720/cubecloud-skills-bundle-kit · 4 stars · license a license file GitHub does not identify · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_hoo7rc2qk3v6at5a GET https://markdownregistry.com/api/v1/resolve?ref=jzkk720/cubecloud-skills-bundle-kit/timesfm-forecasting GET https://markdownregistry.com/api/v1/blob/cb83b741010d9f14448ca41866bcdf6f66bbaca28f5c3146b39663a1d86c6f18
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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