Sentinel Mood

Analyze the sentiment and emotional tone of text using NLTK and VADER. Use this to gauge user mood, detect urgency, or analyze content tone.

A lightweight sentiment analysis skill powered by NLTK's VADER (Valence Aware Dictionary and sEntiment Reasoner). It is specifically tuned for social media texts, conversational language, and short updates.

Capabilities

• Analyze Sentiment: Get positive, negative, neutral, and compound scores for any text.
• Detect Tone: (Implicit) Infer tone based on polarity scores.

Usage

User: "Analyze the sentiment of this message: 'I love how this project is turning out, great job!'" Agent: [Runs skill] -> Returns sentiment scores (e.g., compound: 0.8, pos: 0.6).

Technical Details

This skill uses a Python script (analyze.py) that imports nltk.sentiment.SentimentIntensityAnalyzer.

Dependencies

• Python 3
• nltk library (pip install nltk)
• vader_lexicon (downloaded via nltk.downloader)

Implementation

The skill executes a python script that takes text as an argument and outputs JSON.