An AI-powered utility for extracting sentiment scores, confidence levels, and key phrases from financial and social text.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install betasentiment
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install betasentiment using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Sentiment Analyzer?
The Sentiment Analyzer is a specialized tool designed to evaluate the emotional tone of text-based data, ranging from fast-moving social media posts to complex financial news headlines. As a versatile component within the library of Openclaw Skills, it helps developers and analysts quantify subjective language into actionable data points, such as bullish or bearish signals, to inform decision-making processes.
Sentiment Analyzer Use Cases
- Real-time monitoring of financial news to detect market-moving sentiment shifts.
- Analyzing social media trends for specific keywords, brand mentions, or tickers.
- Batch processing historical data files to evaluate long-term sentiment trends for research.
How Sentiment Analyzer Works
- The user provides a text string or a CSV file path through the command line interface.
- The skill processes the input using Python-based natural language processing to evaluate language patterns.
- It assigns a numerical score and a qualitative verdict, such as Bullish or Bearish, based on the text context.
- High-impact phrases are extracted to provide transparency on why specific sentiment scores were assigned.
- A structured report is generated in the terminal showing the verdict, confidence metrics, and key triggers.
Sentiment Analyzer Setup
This skill requires Python 3 to be installed on your system. To begin using the analyzer, ensure your environment is ready and run the script via CLI:
# Analyze a single string of text
python3 analyze.py --text "Bitcoin to the moon! Best investment ever!"
# Analyze multiple entries from a CSV file
python3 analyze.py --file headlines.csv
Sentiment Analyzer Data Schema & Taxonomy
The Sentiment Analyzer processes input and produces structured metadata to help categorize text data effectively:
| Field | Description |
|---|---|
| Text | The original input string or data point being analyzed |
| Score | A float representing sentiment intensity (typically 0.0 to 1.0) |
| Verdict | The categorical classification (e.g., Bullish, Bearish, Neutral) |
| Confidence | A percentage indicating the reliability of the analysis |
| Key Phrases | A list of high-impact terms and their specific sentiment signals |
Sentiment Analyzer Advanced Features
- Support for high-volume batch processing via CSV integration.
- Context-aware detection specifically tuned for financial and cryptocurrency terminology.
- Extensible architecture that allows for easy integration into larger Openclaw Skills automation pipelines.
SKILL.md
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