How do I trigger sentiment analysis in Claude Code?

You can trigger the skill by using keywords like 'analyze sentiment', 'opinion mining', 'emotion detection', or 'calculate polarity' followed by your text.

Does it provide a numerical sentiment score?

Yes, the skill provides both a categorical classification (positive, negative, neutral) and a sentiment score to indicate the intensity of the tone.

Is this skill suitable for processing large batches of data?

Yes, it is designed to help automate the analysis of feedback at scale when integrated into your Claude Code development environment.

What types of text can this skill analyze?

This skill can process any text-based input, including customer reviews, social media posts, survey responses, and support tickets.

Can it handle sarcasm or irony?

While the underlying ML models are advanced, it is best practice to consider context as sarcasm can occasionally affect the accuracy of sentiment polarity.

Sentiment Analysis Tool

Name: Sentiment Analysis Tool
Author: intent-solutions-io

byintent-solutions-io

Data Science & ML

Analyzes the emotional tone and polarity of text data to classify content as positive, negative, or neutral.

About

The Sentiment Analysis Tool is a specialized Claude Code skill designed to help developers and analysts extract emotional insights from text-based data. By identifying the sentiment—whether positive, negative, or neutral—this tool enables users to automate opinion mining for customer reviews, social media interactions, and survey feedback. It provides actionable sentiment scores and classifications, making it an essential utility for understanding public perception and refining communication strategies through data-driven AI/ML techniques.

Key Features

Automated sentiment classification (positive, negative, neutral)
Real-time opinion mining for social media and customer feedback
Emotion detection across diverse text datasets
0 GitHub stars
Granular sentiment scoring for detailed polarity analysis
Seamless integration with feedback-driven automation workflows

Use Cases

Processing open-ended survey responses for rapid qualitative data analysis
Evaluating customer feedback and product reviews to identify satisfaction trends
Monitoring social media mentions to gauge brand sentiment and public opinion

About

Key Features

Automated sentiment classification (positive, negative, neutral)
Real-time opinion mining for social media and customer feedback
Emotion detection across diverse text datasets
0 GitHub stars
Granular sentiment scoring for detailed polarity analysis
Seamless integration with feedback-driven automation workflows

Use Cases

Processing open-ended survey responses for rapid qualitative data analysis
Evaluating customer feedback and product reviews to identify satisfaction trends
Monitoring social media mentions to gauge brand sentiment and public opinion