A sophisticated monitoring and analysis toolkit designed to identify and capitalize on pricing inefficiencies within Polymarket prediction markets.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install polymarket-arbitrage
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 polymarket-arbitrage 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 Polymarket Arbitrage?
The Polymarket Arbitrage skill provides a robust framework for traders looking to exploit mathematical discrepancies in decentralized prediction markets. By leveraging Openclaw Skills, this tool scans active markets to find scenarios where the sum of outcome probabilities allows for a guaranteed profit, even after accounting for platform fees. It is built to handle the complexities of multi-outcome markets, providing real-time data on net profit percentages and risk scores.
This skill is particularly valuable for developers building automated trading systems on the Polygon network. It handles the heavy lifting of data scraping, fee calculation (assuming a 2% taker fee), and opportunity deduplication. Whether you are performing manual paper trading or scaling toward full automation, this skill provides the technical foundation needed to navigate the volatile landscape of prediction market arbitrage.
Polymarket Arbitrage Use Cases
- Detecting math arbitrage opportunities where the sum of outcome probabilities is less than 100%.
- Monitoring high-volume prediction markets to ensure trade liquidity and minimize slippage.
- Calculating exact net profit margins after subtracting multi-leg taker fees.
- Automating alerts for new arbitrage gaps via webhooks to stay ahead of the competition.
- Implementing a phased trading workflow from initial paper testing to live USDC execution.
How Polymarket Arbitrage Works
- The system utilizes fetch_markets.py to scrape current market data, volumes, and probabilities directly from Polymarket.
- The detect_arbitrage.py script processes the raw JSON data to identify probability mismatches.
- It applies a fee-adjusted calculation (2% per outcome leg) to determine the true net edge of each opportunity.
- A risk score (0-100) is assigned based on market liquidity and volume thresholds to filter out 'stale' or unexecutable data.
- The monitor.py script runs on a loop, alerting the user to new opportunities while maintaining an internal state to prevent duplicate notifications.
Polymarket Arbitrage Setup
To get started with this skill using Openclaw Skills, ensure you have Python installed and follow these steps:
# Navigate to the skill directory
cd skills/polymarket-arbitrage
# Install the necessary Python dependencies
pip install requests beautifulsoup4
# Run a test scan to see current market opportunities
python scripts/monitor.py --once --min-edge 3.0
Polymarket Arbitrage Data Schema & Taxonomy
The skill organizes its findings in the polymarket_data/ directory using the following structure:
| File | Description |
|---|---|
markets.json |
The latest raw scan of active Polymarket events and their current probabilities. |
arbs.json |
A filtered list of executable arbitrage opportunities including net_profit_pct and risk_score. |
alert_state.json |
A state-tracking file used to ensure you are only notified of new, unique opportunities. |
Polymarket Arbitrage Advanced Features
- Webhook integration for real-time Telegram or Discord notifications of new arbitrage gaps.
- Advanced risk management scoring that flags low-volume markets and high-risk sell-side arbitrage.
- Configurable monitoring intervals and minimum edge thresholds to suit different bankroll sizes.
- Mathematical position sizing logic to ensure equal profit distribution regardless of the event outcome.
- Support for multi-outcome math arbitrage (Type A Buy arbs) which are historically the safest for beginners.
SKILL.md
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