Agent skill · Data & Analytics

aeon

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

K-Dense-AIgithub.com/K-Dense-AIGitHub ↗
claude-codecan modify filesMIT
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill aeon --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 12
SKILL.md size: 12 KB
Bundled scripts: none
Version: 1.0
Allowed tools: ReadWriteEditBash
Requires: Requires Python 3.10+ and the aeon package (uv pip install). Optional aeon[all_extras] for deep learning and extended…
Path: skills/aeon/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 32,619
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Aeon Time Series Machine Learning ## Overview Aeon is a scikit-learn compatible Python toolkit for time series machine learning ([aeon-toolkit.org](https://www.aeon-toolkit.org/)). It provides algorithms across classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search, distances, transformations, benchmarking, and visualization — with a consistent estimator API. **Version note:** Examples target **aeon 1.x** (stable docs: v1.4.0, March 2026). The v1.0 release reworked forecasting and transformations; import paths differ from aeon 0.x/sktime-era code. ## When to Use This Skill Apply this skill when: - Classifying or predicting from time series data - Detecting anomalies or change points in temporal sequences - Clustering similar time series patterns - Forecasting future values - Finding repeated patterns (motifs) or unusual subsequences (discords) - Comparing time series with specialized distance metrics - Extracting features from temporal data ## Installation Requires **Python 3.10+** (3.11+ recommended). Pin a 1.x release for reproducibility: ```bash uv pip install "aeon>=1.4,<2" ``` For deep learning forecasters/classifiers and othe

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Installation
  4. Experimental modules
  5. Core Capabilities
  6. 1. Time Series Classification
  7. 2. Time Series Regression
  8. 3. Time Series Clustering
  9. 4. Forecasting
  10. 5. Anomaly Detection
  11. 6. Segmentation
  12. 7. Similarity Search
  13. Feature Extraction and Transformations
  14. Distance Metrics
Ships with 11 files
  • references/anomaly_detection.md
  • references/classification.md
  • references/clustering.md
  • references/datasets_benchmarking.md
  • references/distances.md
  • references/forecasting.md
  • references/networks.md
  • references/regression.md
  • references/segmentation.md
  • references/similarity_search.md
  • references/transformations.md
Commands it runs
uv pip install "aeon>=1.4,<2"
uv pip install "aeon[all_extras]>=1.4,<2"
More from scientific-agent-skills
All skills →
About this skill
What does the aeon skill do?

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

How do I install it?

Run `npx skills add K-Dense-AI/scientific-agent-skills --skill aeon --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going