Does it provide confidence scores for sentiment?

Yes, when performing sentiment analysis, the skill can provide a sentiment label along with a confidence score to indicate accuracy.

How do I trigger the NLP analysis in Claude Code?

Simply ask Claude to 'analyze text', 'perform sentiment analysis', or 'extract keywords' from your provided content to activate the skill.

Can it handle technical or specialized vocabulary?

Yes, the AI/ML techniques used are designed to identify and extract relevant terms even from complex technical documents or news articles.

Is this skill useful for data scientists?

Absolutely, it is ideal for quickly prototyping data pipelines, benchmarking text models, or analyzing large unstructured datasets.

NLP Text Analyzer

Name: NLP Text Analyzer
Author: intent-solutions-io

byintent-solutions-io

数据科学与机器学习

Performs comprehensive natural language processing tasks including sentiment analysis, keyword extraction, and topic modeling directly within Claude.

关于

This skill empowers Claude with advanced NLP capabilities using the nlp-text-analyzer plugin, allowing users to extract deep insights from textual data. It streamlines the process of evaluating user sentiment, identifying core themes through topic modeling, and isolating critical keywords from documents or datasets. Whether you are processing customer feedback, news articles, or technical documentation, this skill provides the analytical framework needed to transform raw text into actionable intelligence with high confidence and precision.

主要功能

Precision keyword extraction for document indexing and summarization
Automated sentiment analysis with confidence scoring
Seamless integration with AI/ML pipelines and FastAPI services
Topic modeling to identify core themes in large datasets
Natural language processing for unstructured text data
0 GitHub stars

使用场景

Analyzing customer reviews to gauge product sentiment and common pain points
Summarizing news articles or research papers by extracting essential keywords
Categorizing large sets of support tickets using topic modeling to improve response efficiency

关于

主要功能

Precision keyword extraction for document indexing and summarization
Automated sentiment analysis with confidence scoring
Seamless integration with AI/ML pipelines and FastAPI services
Topic modeling to identify core themes in large datasets
Natural language processing for unstructured text data
0 GitHub stars

使用场景

Analyzing customer reviews to gauge product sentiment and common pain points
Summarizing news articles or research papers by extracting essential keywords
Categorizing large sets of support tickets using topic modeling to improve response efficiency