How do I see all available classification models?

Run the command 'classifier models' to list all pre-trained and custom models currently available for use.

What pre-trained models are available by default?

The skill includes models for SMS spam filtering (sms-spam-filter), movie review sentiment (imdb-sentiment), and emotion detection (emotion-detection).

Is this skill part of a larger ecosystem?

Yes, it is part of the ai-marketplace repository, which focuses on providing unified Claude Code plugins for the Apple ecosystem and beyond.

Can I train the classifier with my own data?

Yes, you can train custom models using the 'classifier train' command with your own text strings or by pointing to directories of text files.

Can I save my custom-trained models for later use?

Yes, you can use 'classifier save [filename.json]' to export your trained model and 'classifier load' to bring it back into a future session.

AI Text Classifier & ML Engine

Name: AI Text Classifier & ML Engine
Author: cardmagic

bycardmagic

데이터 과학 및 ML

Categorizes text, detects sentiment, and filters spam using pre-trained and custom-trained machine learning models.

소개

The Classifier skill empowers Claude to perform sophisticated natural language processing tasks directly within your development environment. It provides a suite of pre-trained models for immediate use in spam detection, sentiment analysis, and emotion classification, while also offering a robust framework for training custom models on your own datasets. This skill is ideal for developers who need to automate text-heavy workflows, analyze user feedback, or build intelligent categorization systems without leaving the Claude Code interface.

주요 기능

Model management for saving and loading domain-specific classifiers
Custom training capabilities using local text files or raw input
Support for multi-category training and balanced data sets
0 GitHub stars
Pre-trained models for spam, sentiment, and emotion detection
Real-time classification via simple command-line triggers

사용 사례

Automating spam filtering for messaging applications or feedback forms
Analyzing customer reviews and support tickets for sentiment and emotional tone
Organizing large documentation or data sets into custom-defined categories

소개

주요 기능

Model management for saving and loading domain-specific classifiers
Custom training capabilities using local text files or raw input
Support for multi-category training and balanced data sets
0 GitHub stars
Pre-trained models for spam, sentiment, and emotion detection
Real-time classification via simple command-line triggers

사용 사례

Automating spam filtering for messaging applications or feedback forms
Analyzing customer reviews and support tickets for sentiment and emotional tone
Organizing large documentation or data sets into custom-defined categories