aeon SKILL.md skillA

aeon from aicodedecode/awesome-muse-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add aicodedecode/awesome-muse-skills/aeon@git:20260927.806f3e1

Pins git:20260927.806f3e1 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
aicodedecode/awesome-muse-skills
Path
skills-imported/aeon/SKILL.md
Versions recorded
1
Latest version
git:20260927.806f3e1, committed Sep 27, 2026
Size
10,515 bytes
Repository stars
25
License
MIT

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.

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

# Aeon Time Series Machine Learning

## Overview

Aeon is a scikit-learn compatible Python toolkit for time series machine learning. It provides state-of-the-art algorithms for classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search.

## 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

```bash
uv pip install aeon
```

## Core Capabilities

### 1. Time Series Classification

Categorize time series into predefined classes. See `references/classification.md` for complete algorithm catalog.

**Quick Start:**
```python
from aeon.classification.convolution_based import RocketClassifier
from aeon.datasets import load_classification

# Load data
X_train, y_train = load_classification("GunPoint", split="train")
X_test, y_test = load_classification("GunPoint", split="test")
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add aicodedecode/awesome-muse-skills/aeon@sha256:c45c5d51959e174b

The line at the top of this page pins the label git:20260927.806f3e1, 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.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_gzjtdgxxoyhhvrfy.svg)](https://markdownregistry.com/a/art_gzjtdgxxoyhhvrfy)

3 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Sep 27, 2026.

versioncommittedcommitsizeaudit
git:20260927.806f3e1 latest2026-09-27 806f3e1 10,515 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (10515 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

GitHub

aicodedecode/awesome-muse-skills · 25 stars · license MIT · pushed 2026-10-10 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_gzjtdgxxoyhhvrfy
GET https://markdownregistry.com/api/v1/resolve?ref=aicodedecode/awesome-muse-skills/aeon
GET https://markdownregistry.com/api/v1/blob/c45c5d51959e174b984ce873735c586854a388036180798bee5adb0d97faf471

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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