Skill UI

Automates building and evaluating classification models by analyzing datasets, selecting features, tuning hyperparameters, and reporting metrics via the classification-model-builder plugin for supervised learning requests.

Aeon is a scikit-learn compatible toolkit for time series machine learning, covering classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search, and feature extraction on temporal data.

Query InterPro for protein family, domain, and GO annotations via a REST API with Python helpers, enabling function prediction, domain architecture mapping, and evolutionary classification insights for proteomic workflows.

A comprehensive skill for managing the entire lifecycle of datasets on the Hugging Face Hub. It allows users to initialize, configure, and stream updates for datasets of various types (Chat, Text Classification, Tabular). Crucially, it extends data handling capabilities by enabling powerful SQL-based querying and transformation directly on Hub datasets using the DuckDB engine, facilitating advanced data exploration and pipeline creation.

A sophisticated skill for detecting Command and Control (C2) traffic tunneled through DNS protocols. It utilizes advanced techniques like Shannon entropy analysis of subdomains, Machine Learning for DGA classification, and correlation with network logs from Zeek/Suricata. Ideal for SOC analysts and threat hunters investigating data exfiltration, DNS beaconing, or suspicious DNS activity.

Aeon is a scikit-learn compatible Python toolkit for time series machine learning, covering classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search with specialized algorithms.

This internal agent skill processes raw X/Twitter posts into structured bug candidates. It systematically performs parsing, content deduplication, PII redaction, reliability scoring, and classification. Finally, it clusters related reports using deterministic signatures, providing a highly organized output for efficient bug triage and analysis from large-scale social media streams.

This skill enables querying nutritional information, comparing food items, and performing calculations based on structured food data. It supports database retrieval, portion conversion, and classification filtering for precise nutritional analysis rather than general text suggestions.