classifier

Classify text sentiment and spam using pre-trained CLI models.

Updated Jan 3, 2026

Search Tags:#emotion #text #sentiment #classify #custom-training #pre-trained-models #spam-detection

Ready to run

npx skills add https://github.com/cardmagic/ai-marketplace --skill classifier-cardmagic

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: classifier
Source: https://github.com/cardmagic/ai-marketplace/tree/main/plugins/classifier/skills/classifier
Command: npx skills add https://github.com/cardmagic/ai-marketplace --skill classifier-cardmagic

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables automated text classification and emotion/sentiment detection for text data using pre-trained models or custom-trained classifiers.

Core Features & Use Cases

Pre-trained models: sms-spam-filter, imdb-sentiment, emotion-detection for quick analytics.
Custom training and model management: train, evaluate, save, and load models for domain-specific tasks.
Practical applications: content moderation, customer feedback analysis, and spam detection across chat, email, and social media.

Quick Start

Use the classifier CLI to quickly classify text with a pre-trained model: classifier -r sms-spam-filter "You won a free iPhone! Click here now!" For sentiment analysis: classifier -r imdb-sentiment "This product exceeded my expectations"

Frequently Asked Questions about classifier

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I classify text to detect spam in chat or email messages?▼

Text classification for spam detection uses the sms-spam-filter pre-trained model to automatically flag unwanted messages. You can run classifier -r sms-spam-filter "your text" to instantly categorize chat, email, or social media inputs.

Can I train a custom text classifier for domain-specific sentiment analysis?▼

Custom text classifier training allows you to build domain-specific sentiment models using the classifier train command. You can train, evaluate, save, and load custom models to accurately analyze customer feedback for your specific industry vocabulary.

What pre-trained models are available for emotion detection and sentiment analysis?▼

Pre-trained models for emotion detection and sentiment analysis include sms-spam-filter, imdb-sentiment, and emotion-detection. These models enable quick text analytics across short and long inputs without requiring custom training.

Does text classification work for both short chat messages and long feedback text?▼

Text classification supports both short and long text inputs for sentiment and emotion detection. The pre-trained and custom-trained models process varying text lengths to deliver accurate classification across customer feedback and chat data.

What is the best way to moderate user-generated content using automated text classification?▼

Automated text classification for content moderation uses pre-trained models to identify spam and detect emotions across social media inputs. The classifier CLI instantly evaluates text to filter inappropriate content and analyze customer feedback.

Do I need to install dependencies to run the classifier CLI for text classification?▼

The classifier CLI operates without external dependencies to perform text classification and emotion detection. You can immediately use commands like classifier -r <model> 'text' and classifier models to manage pre-trained and custom models.