mofa-org/mofa/text-analysis

Text Analysis Skill

This skill provides natural language processing capabilities for text analysis.

When to Use

Use this skill when you need to:

• Analyze text sentiment (positive/negative/neutral)
• Extract named entities (people, places, organizations)
• Identify keywords and phrases
• Perform text classification
• Summarize long documents

Analysis Types

Sentiment Analysis

Determines the emotional tone of text:

• Positive: Expresses satisfaction, happiness, approval
• Negative: Expresses dissatisfaction, sadness, disapproval
• Neutral: Factual or informational content

Entity Extraction

Identifies and categorizes:

• People: Person names
• Places: Locations, addresses
• Organizations: Companies, institutions
• Dates: Temporal expressions
• Numbers: Quantities, measurements

Keyword Analysis

Extracts important terms and phrases:

• TF-IDF scoring
• Phrase frequency
• Collocation detection

Code Tools

@code: python analyze.py --input {input} - Perform various text analyses

Example Usage

Analyze the sentiment of this customer review: "The product exceeded my expectations!"
Result: Positive sentiment detected (confidence: 0.95)

Extract entities from: "Apple Inc. was founded by Steve Jobs in Cupertino, California."
Entities:
- Organization: Apple Inc.
- Person: Steve Jobs
- Location: Cupertino, California