| name | sentinel-mood |
| description | Analyze the sentiment and emotional tone of text using NLTK and VADER. Use this to gauge user mood, detect urgency, or analyze content tone. |
| metadata | {"openclaw":{"emoji":"🎭","requires":{"python_packages":"[Truncated]"}}} |
Sentinel Mood
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.
