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Patrickjoshanedez
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content-analysis

Analyze sentiment, topics, and classifications in text using NLP and LLM methods.

1|Updated Feb 28, 2026
Search Tags:#llm#nlp#sentiment analysis#text analysis#topic modeling#content insights
One-click install
npx skills add https://github.com/Patrickjoshanedez/CMS-V2 --skill content-analysis-patrickjoshanedez
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: content-analysis
Source: https://github.com/Patrickjoshanedez/CMS-V2/tree/main/.agents/skills/content-analysis
Command: npx skills add https://github.com/Patrickjoshanedez/CMS-V2 --skill content-analysis-patrickjoshanedez

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, matplotlib, seaborn, nltk, scikit-learn, wordcloud, openai, dashscope, requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill tackles the challenge of understanding large volumes of text by providing automated analysis of sentiment, topics, and key insights, making complex data accessible and actionable.

Core Features & Use Cases

  • Dual-Mode Analysis: Leverages both traditional NLP and advanced LLM techniques for comprehensive understanding.
  • Insight Generation: Extracts sentiment, topics, keywords, and actionable recommendations from diverse text sources.
  • Use Case: Analyze thousands of customer reviews to identify common pain points, gauge overall sentiment, and discover emerging product feature requests.

Quick Start

Use the content-analysis skill to analyze the sentiment of the provided customer feedback.

Frequently Asked Questions about content-analysis

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

FAQPage Schema
How do I perform sentiment analysis and topic extraction on customer reviews?▼

You can analyze large volumes of social media or marketing text by applying traditional NLP and LLM-enhanced methods. This approach processes your data to generate deep content insights and actionable intelligence without manual review.

Can I use openai and dashscope libraries for text analysis of video transcripts?▼

Yes, openai and dashscope are supported dependencies for executing text analysis on video transcripts. The skill integrates these LLM frameworks alongside pandas and nltk to process transcripts and yield meaningful content insights.

What is the best way to extract actionable insights from social media text?▼

The best way to extract actionable insights from social media text is leveraging LLM-enhanced content classification. This method identifies common pain points and emerging feature requests by combining traditional NLP topic modeling with LLM reasoning.

Does this text analysis approach require nltk and scikit-learn for topic modeling?▼

Yes, nltk and scikit-learn are required dependencies for executing traditional topic modeling and text classification. They provide the foundational NLP processing framework that complements the LLM-based analysis components.

How do I classify product reviews using NLP and LLM techniques?▼

Product reviews are classified by applying a dual-mode analysis that combines traditional NLP and LLM techniques. This classifies diverse text sources to identify common pain points and gauge overall sentiment automatically.

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