How do I install the Analyzing Text With Nlp skill?

Run npx skillmds@latest add gabrielmoreira/analyzing-text-with-nlp in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Analyzing Text With Nlp safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Analyzing Text With Nlp?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Analyzing Text With Nlp free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Analyzing Text With Nlp?

gabrielmoreira (@gabrielmoreira) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Analyzing Text With Nlp by gabrielmoreira

Name: Analyzing Text With Nlp
Rating: 4.666666666666667 (3 reviews)
Author: gabrielmoreira

Analyzing Text With Nlp

Execute this skill enables AI assistant to perform natural language processing and text analysis using the nlp-text-analyzer plugin. it should be used when the user requests analysis of text, including sentiment analysis, keyword extraction, topic modeling, or ... Use when analyzing code or data. Trigger with phrases like 'analyze', 'review', or 'examine'.

gabrielmoreira Updated Sep 9, 2026 17 repo stars

File contents

Nlp Text Analyzer

Analyze text using NLP techniques including sentiment analysis, keyword extraction, named entity recognition, and topic modeling.

Overview

This skill empowers Claude to analyze text using the nlp-text-analyzer plugin, extracting meaningful information and insights. It facilitates tasks such as sentiment analysis, keyword extraction, and topic modeling, enabling a deeper understanding of textual data.

How It Works

Request Analysis: Claude receives a user request to analyze text.
Text Processing: The nlp-text-analyzer plugin processes the text using NLP techniques.
Insight Extraction: The plugin extracts insights such as sentiment, keywords, and topics.

When to Use This Skill

This skill activates when you need to:

Perform sentiment analysis on a piece of text.
Extract keywords from a document.
Identify the main topics discussed in a text.

Examples

Example 1: Sentiment Analysis

User request: "Analyze the sentiment of this product review: 'I loved the product! It exceeded my expectations.'"

The skill will:

Process the review text using the nlp-text-analyzer plugin.
Determine the sentiment as positive and provide a confidence score.

Example 2: Keyword Extraction

User request: "Extract the keywords from this news article about the latest AI advancements."

The skill will:

Process the article text using the nlp-text-analyzer plugin.
Identify and return a list of relevant keywords, such as "AI", "advancements", "machine learning", and "neural networks".

Best Practices

Clarity: Be specific in your requests to ensure accurate and relevant analysis.
Context: Provide sufficient context to improve the quality of the analysis.
Iteration: Refine your requests based on the initial results to achieve the desired outcome.

Integration

This skill can be integrated with other tools to provide a comprehensive workflow, such as using the extracted keywords to perform further research or using sentiment analysis to categorize customer feedback.

Prerequisites

Appropriate file access permissions
Required dependencies installed

Instructions

Invoke this skill when the trigger conditions are met
Provide necessary context and parameters
Review the generated output
Apply modifications as needed

Output

The skill produces structured output relevant to the task.

Error Handling

Invalid input: Prompts for correction
Missing dependencies: Lists required components
Permission errors: Suggests remediation steps

Resources

Project documentation
Related skills and commands

---name: analyzing-text-with-nlpdescription: Execute this skill enables AI assistant to perform natural language processing and text analysis using the nlp-text-analyzer plugin. it should be used when the user requests analysis of text, including sentiment analysis, keyword extraction, topic modeling, or ... Use when analyzing code or data. Trigger with phrases like 'analyze', 'review', or 'examine'.license: MIT---# Nlp Text Analyzer Analyze text using NLP techniques including sentiment analysis, keyword extraction, named entity recognition, and topic modeling. ## Overview This skill empowers Claude to analyze text using the nlp-text-analyzer plugin, extracting meaningful information and insights. It facilitates tasks such as sentiment analysis, keyword extraction, and topic modeling, enabling a deeper understanding of textual data. ## How It Works 1. **Request Analysis**: Claude receives a user request to analyze text. 2. **Text Processing**: The nlp-text-analyzer plugin processes the text using NLP techniques. 3. **Insight Extraction**: The plugin extracts insights such as sentiment, keywords, and topics. ## When to Use This Skill This skill activates when you need to: - Perform sentiment analysis on a piece of text. - Extract keywords from a document. - Identify the main topics discussed in a text. ## Examples ### Example 1: Sentiment Analysis User request: "Analyze the sentiment of this product review: 'I loved the product! It exceeded my expectations.'" The skill will: 1. Process the review text using the nlp-text-analyzer plugin. 2. Determine the sentiment as positive and provide a confidence score. ### Example 2: Keyword Extraction User request: "Extract the keywords from this news article about the latest AI advancements." The skill will: 1. Process the article text using the nlp-text-analyzer plugin. 2. Identify and return a list of relevant keywords, such as "AI", "advancements", "machine learning", and "neural networks". ## Best Practices - **Clarity**: Be specific in your requests to ensure accurate and relevant analysis. - **Context**: Provide sufficient context to improve the quality of the analysis. - **Iteration**: Refine your requests based on the initial results to achieve the desired outcome. ## Integration This skill can be integrated with other tools to provide a comprehensive workflow, such as using the extracted keywords to perform further research or using sentiment analysis to categorize customer feedback. ## Prerequisites - Appropriate file access permissions - Required dependencies installed ## Instructions 1. Invoke this skill when the trigger conditions are met 2. Provide necessary context and parameters 3. Review the generated output 4. Apply modifications as needed ## Output The skill produces structured output relevant to the task. ## Error Handling - Invalid input: Prompts for correction - Missing dependencies: Lists required components - Permission errors: Suggests remediation steps ## Resources - Project documentation - Related skills and commands

Frequently asked questions