Does the profit calculation include trading fees?

Yes, the detector is designed to factor in standard platform fees to ensure that the reported profit percentages reflect realistic net gains.

What happens if the APIs are down?

The skill includes error handling for API timeouts and connectivity issues, providing status check links and retry recommendations for both platforms.

Does this skill require API keys for Polymarket and Kalshi?

While public data can often be fetched via the CLOB API, some Kalshi endpoints or higher rate limits may require API authentication configured in your environment.

How does the skill match events between different platforms?

It utilizes a fuzzy string matching algorithm with a customizable similarity threshold (default 70%) to identify when different platforms are referencing the same event.

Is this an automated trading bot?

No, this skill functions as an analysis tool that identifies and reports opportunities. It does not execute trades automatically on your behalf.

The Prediction Market Arbitrage Detector is a specialized skill designed to help users capitalize on market inefficiencies across major prediction platforms. It automatically fetches real-time contract prices from Polymarket and Kalshi, utilizes fuzzy string matching to align corresponding events, and calculates potential returns after accounting for platform-specific fees. By providing a ranked report of arbitrage opportunities, it enables traders and analysts to quickly identify low-risk profit potential in election, economic, and current event markets.

Key Features

01Real-time data fetching from Polymarket CLOB and Kalshi APIs

02Advanced fuzzy string matching for cross-platform event alignment

03Ranked arbitrage opportunity reporting with risk assessment warnings

04Automated profit calculation factoring in platform-specific trading fees

05Comprehensive data export to JSON and CSV for further analysis

060 GitHub stars

Use Cases

01Identifying price discrepancies for election outcomes across different platforms

02Automating market monitoring for professional prediction market traders

03Analyzing market efficiency and liquidity between decentralized and regulated exchanges

name	description	allowed-tools	version
nixtla-arbitrage-detector	Detects arbitrage opportunities between Polymarket and Kalshi prediction markets. Use when a user wants to find price discrepancies for the same event on different platforms. Trigger with "find arbitrage", "detect market inefficiencies", "compare Polymarket and Kalshi prices".	Read,Write,Bash,Glob,Grep,WebFetch	1.0.0

Arbitrage Detector

Identifies potential arbitrage opportunities across Polymarket and Kalshi prediction markets.

Purpose

Finds discrepancies in contract prices for the same event across Polymarket and Kalshi prediction markets, calculating potential profit after fees.

Overview

Scans Polymarket and Kalshi for matching events. Fetches current prices for each event. Calculates the potential profit from buying on one platform and selling on the other, factoring in fees. Outputs a list of arbitrage opportunities ranked by potential profit.

Prerequisites

Tools: Read, Write, Bash, Glob, Grep, WebFetch

Environment: None required

Packages:

pip install requests pandas

Instructions

Step 1: Fetch Polymarket Data

Run the Polymarket data fetcher:

python {baseDir}/scripts/fetch_polymarket.py

This fetches active markets and current prices from Polymarket CLOB API, saving results to polymarket_data.json.

Step 2: Fetch Kalshi Data

Run the Kalshi data fetcher:

python {baseDir}/scripts/fetch_kalshi.py

This fetches open markets from Kalshi API, saving results to kalshi_data.json.

Step 3: Detect Arbitrage Opportunities

Run the arbitrage analyzer:

python {baseDir}/scripts/detect_arbitrage.py

This compares prices across platforms using fuzzy string matching (70% similarity threshold), calculates arbitrage strategies, and outputs opportunities sorted by profit percentage.

Step 4: Generate Report

Create the summary report:

python {baseDir}/scripts/generate_report.py

Generates a formatted markdown report with top opportunities and risk warnings.

Output

polymarket_data.json: Raw market data from Polymarket
kalshi_data.json: Raw market data from Kalshi
arbitrage_opportunities.csv: All detected opportunities with profit calculations
arbitrage_report.md: Formatted summary report

Error Handling

Error: Polymarket API Error Solution: Check Polymarket API status at status.polymarket.com. Retry after 30 seconds.
Error: Kalshi API Error Solution: Check Kalshi API status. May need API authentication for some endpoints.
Error: No matching events found Solution: Lower the similarity threshold (default 0.7) or manually map event names.
Error: Insufficient data to calculate arbitrage Solution: Ensure both platforms have YES and NO prices > 0.

Examples

Example 1: Profitable Arbitrage Found

Scenario: Same election event on both platforms

Event: "Will candidate X win the 2024 election?"
Polymarket: YES = 0.45, NO = 0.55
Kalshi: YES = 0.52, NO = 0.48

Strategy: Buy Polymarket YES + Kalshi NO
Cost: 0.45 * 1.02 + 0.48 * 1.01 = 0.459 + 0.485 = 0.944
Guaranteed Return: $1.00
Profit: $0.056 (5.9%)

Example 2: No Arbitrage

Scenario: Prices are efficiently aligned

Event: "Will it rain tomorrow in NYC?"
Polymarket: YES = 0.50, NO = 0.50
Kalshi: YES = 0.50, NO = 0.50

Cost of any strategy > $1.00 after fees
Result: No profitable arbitrage

Resources

Polymarket data fetcher: {baseDir}/scripts/fetch_polymarket.py
Kalshi data fetcher: {baseDir}/scripts/fetch_kalshi.py
Arbitrage analyzer: {baseDir}/scripts/detect_arbitrage.py
Report generator: {baseDir}/scripts/generate_report.py

Usage

Run the complete workflow:

# 1. Fetch data from both platforms
python {baseDir}/scripts/fetch_polymarket.py
python {baseDir}/scripts/fetch_kalshi.py

# 2. Detect arbitrage opportunities
python {baseDir}/scripts/detect_arbitrage.py

# 3. Generate report
python {baseDir}/scripts/generate_report.py

Or invoke this skill to generate and execute all scripts automatically.

Prediction Market Arbitrage Detector