How do I trigger the NLP analysis within Claude Code?

You can trigger the skill by using phrases such as 'analyze text', 'extract keywords', or 'perform sentiment analysis' followed by the content or file path you want to process.

Does it provide confidence scores for sentiment results?

Yes, the underlying nlp-text-analyzer plugin returns both the sentiment classification (e.g., positive/negative) and a numerical confidence score to help you gauge result reliability.

Can this skill process multiple documents at once?

Yes, you can request Claude to analyze a set of files or a directory, and the skill will leverage the plugin to identify topics and keywords across the provided dataset.

What kind of NLP tasks can this skill perform?

The skill handles a wide range of tasks including sentiment analysis, keyword extraction, topic modeling, and general text insight generation using AI/ML techniques.

NLP Text Analyzer

Name: NLP Text Analyzer
Author: jeremylongshore

byjeremylongshore

•

883

数据科学与机器学习

Performs comprehensive natural language processing tasks including sentiment analysis and keyword extraction directly within the Claude Code environment.

关于

This skill integrates the nlp-text-analyzer plugin into Claude Code to provide deep textual insights through advanced machine learning techniques. It allows users to automatically determine sentiment, identify core topics, and extract relevant keywords from documents or snippets without leaving the command line. Ideal for developers and data scientists who need to process large amounts of text or automate content categorization workflows, it enhances Claude's native capabilities with structured, plugin-driven NLP outputs.

主要功能

Pattern-based text categorization and labeling
883 GitHub stars
Automated sentiment analysis with confidence scoring
Multi-document topic modeling to identify recurring themes
Intelligent keyword extraction for document indexing
Seamless integration with CLI-based text processing workflows

使用场景

Summarizing technical documentation by extracting essential keywords for better searchability
Categorizing large sets of log files or chat transcripts by identifying primary topics
Analyzing customer feedback and reviews to track brand sentiment and satisfaction

关于

主要功能

Pattern-based text categorization and labeling
883 GitHub stars
Automated sentiment analysis with confidence scoring
Multi-document topic modeling to identify recurring themes
Intelligent keyword extraction for document indexing
Seamless integration with CLI-based text processing workflows

使用场景

Summarizing technical documentation by extracting essential keywords for better searchability
Categorizing large sets of log files or chat transcripts by identifying primary topics
Analyzing customer feedback and reviews to track brand sentiment and satisfaction