A powerful local tool for tracking public sentiment across social media and news platforms using automated analysis and reporting.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install sentiment-tracker
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 sentiment-tracker 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 Tracker?
The Sentiment Tracker is an advanced utility designed for the Openclaw Skills ecosystem that allows developers and marketers to monitor public perception in real-time. By aggregating data from diverse sources like Twitter, Reddit, YouTube, and Hacker News, this skill provides a comprehensive view of how brands, products, or cryptocurrencies are perceived without relying on expensive or restrictive external APIs.
This skill prioritizes data privacy by storing all analysis, entity configurations, and historical reports locally on your machine. Whether you are conducting a one-shot deep dive into a specific topic or setting up a long-term monitoring dashboard, Sentiment Tracker ensures you stay ahead of market shifts and potential PR crises through automated alerting, multi-entity comparisons, and trend quantification.
Sentiment Tracker Use Cases
- Monitor brand reputation across multiple social media platforms simultaneously to identify shifts in public opinion.
- Track cryptocurrency market sentiment to identify emerging trends or potential volatility before it hits mainstream news.
- Compare competitor performance using multi-entity dashboards that highlight relative volume and sentiment trends.
- Set up automated alerts for negative spikes or viral posts to manage PR crises proactively.
- Analyze product launch reception by quantifying feedback from tech-focused communities like Hacker News and Reddit.
How Sentiment Tracker Works
- The user defines tracking entities such as brands, products, or keywords in the local configuration file.
- The skill executes multi-source searches across Twitter, Reddit, YouTube, and news sites to gather diverse perspectives and minimize bias.
- Collected data is processed locally to quantify mention volume, sentiment percentages (positive, negative, neutral), and top recurring themes.
- Detailed reports are generated as Markdown files, providing a structured summary of findings and engagement metrics.
- The system compares current results against historical baselines to identify significant trends or anomalies.
- If specific thresholds are met, such as a 20% increase in negative sentiment, an alert is automatically triggered.
- Scheduled monitoring tasks update the local database at defined intervals to maintain a persistent dashboard.
Sentiment Tracker Setup
To begin using this skill within your Openclaw Skills environment, initialize the tracking directory and configure your entities.
# Install the sentiment tracker skill
clawhub install sentiment-tracker
# Follow the initial setup guidelines stored locally
cat ~/sentiment-analysis/setup.md
# Sync your skills to ensure you have the latest updates
clawhub sync
Sentiment Tracker Data Schema & Taxonomy
The skill organizes all data within a structured local directory ~/sentiment-analysis/ to ensure privacy and portability.
| File/Folder | Purpose | Format |
|---|---|---|
memory.md |
Main configuration, tracked entities, and schedules | Markdown |
entities/ |
Individual tracking history for each specific brand or keyword | Markdown |
reports/ |
Time-stamped analysis reports (YYYY-MM-DD-entity.md) | Markdown |
alerts.md |
Historical log of all triggered alerts and spikes | Markdown |
Sentiment Tracker Advanced Features
- Automated scheduled monitoring with customizable cron schedules for different priority levels.
- Multi-source cross-referencing to eliminate platform-specific biases from Reddit or Twitter.
- Relative performance tracking for side-by-side comparison of multiple brands or competitors.
- Local-first architecture ensuring all tracking data and configurations remain on your machine.
- Intelligent alerting system that triggers only on meaningful deviations from established sentiment baselines.
SKILL.md
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