A powerful tool for calculating probability ranges for Polymarket events based on real-time network research and historical data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install polymarket-prob-analyzer
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-prob-analyzer 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 Probability Analyzer?
The Polymarket Probability Analyzer is an advanced analytical tool designed for the Openclaw Skills ecosystem. It empowers traders to move beyond simple market sentiment by performing deep-dive research into specific events. By synthesizing expert opinions, news cycles, and historical trends, the skill provides a multi-layered probability outlook. This tool is essential for anyone looking to refine their strategy in prediction markets by understanding the underlying factors driving event likelihoods.
This skill automates the heavy lifting of information gathering, allowing users to focus on decision-making rather than manual data collection. By integrating with high-quality data sources, it offers a quantitative edge in the fast-paced world of decentralized prediction markets.
Polymarket Probability Analyzer Use Cases
- Assessing the probability of financial milestones like crypto price targets.
- Analyzing the impact of political developments on election outcomes.
- Researching economic shifts such as interest rate changes for informed trading.
- Using Openclaw Skills to automate the data gathering process for complex prediction market positions.
How Polymarket Probability Analyzer Works
- Event Identification: The user provides an event name or a direct Polymarket URL to the skill.
- Information Gathering: The analyzer initiates a comprehensive search across news outlets, historical data, and expert reports.
- Probability Calculation: Data is processed through a heuristic algorithm to calculate low, mid, and high probability bounds.
- Billing Check: A balance check is performed via SkillPay.me to ensure the user has sufficient credits (0.001 USDT per analysis).
- Analysis Delivery: The final report is delivered, including confidence levels, specific risk factors, and source citations.
Polymarket Probability Analyzer Setup
To utilize this within the Openclaw Skills framework, ensure you have Python 3 and the requests library installed. Run the following commands in your terminal:
# Analyze a specific event by name
python scripts/prob_analyzer.py --event "Will Bitcoin hit $100k by 2025?"
# Analyze via a direct Polymarket link
python scripts/prob_analyzer.py --url https://polymarket.com/event/bitcoin-100k
# Enable verbose mode for a deeper breakdown of factors
python scripts/prob_analyzer.py --event "Trump 2024" --verbose
Note: First-time users will receive a payment link to top up their SkillPay.me balance (8.00 USDT minimum) before the analysis proceeds.
Polymarket Probability Analyzer Data Schema & Taxonomy
The skill organizes its output into a structured format for clear interpretation:
| Attribute | Description |
|---|---|
| Event Name | The specific name or URL of the Polymarket event. |
| Probability Range | Low (Conservative), Mid (Balanced), and High (Optimistic) percentages. |
| Confidence Level | A rating (Low, Medium, or High) indicating the reliability of the data. |
| Key Factors | A list of primary drivers influencing the current probability. |
| Sources | The number of distinct online sources analyzed during the research phase. |
Polymarket Probability Analyzer Advanced Features
- Integrated SkillPay.me billing for seamless micro-transactions within the Openclaw Skills ecosystem.
- Specialized modules for Crypto, Political, and Economic events providing domain-specific analysis.
- Verbose Output mode for power users needing factor weighting and historical comparisons.
- Developer-friendly flags including --skip-billing for testing and debugging environments.
SKILL.md
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