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prediction-markets

Integrate Polymarket and Kalshi prediction markets into crypto trading platforms.

2|Updated Jun 30, 2026
Search Tags:#market analysis#crypto trading#prediction market#event mapping#auto-trading
One-click install
npx skills add https://github.com/Canhada-Labs/ceo-orchestration --skill prediction-markets-canhada-labs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prediction-markets
Source: https://github.com/Canhada-Labs/ceo-orchestration/tree/main/.claude/skills/domains/fintech/skills/prediction-markets
Command: npx skills add https://github.com/Canhada-Labs/ceo-orchestration --skill prediction-markets-canhada-labs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, typescript, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for integrating and trading in prediction markets, offering strategies, event mapping, and analysis tools for crypto trading platforms.

Core Features & Use Cases

  • Prediction Market Integration: Connect and trade on platforms like Polymarket and Kalshi.
  • Trading Strategies: Implement strategies such as V2 insurance model, multi-timeframe trading, and cross-venue price discrepancies analysis.
  • Event Mapping: Automatically match real-world events to prediction markets with confidence threshold.
  • Use Case: Use this Skill to analyze the potential impact of a real-world event on a crypto asset's price and place a trade accordingly.

Quick Start

Run the prediction-markets skill to analyze the impact of a significant real-world event on a crypto asset.

Frequently Asked Questions about prediction-markets

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate prediction markets into crypto trading?▼

Prediction market integration connects crypto trading platforms to event markets using Polymarket and Kalshi APIs. You can execute trades based on automated event mapping and cross-venue price discrepancy analysis using Python and TypeScript environments.

How does event mapping work for crypto trading strategies?▼

Event mapping automatically matches real-world events to prediction markets using a confidence threshold. It analyzes the potential impact of significant events on crypto asset prices to trigger corresponding trades across connected platforms.

What prediction market trading strategies can I implement?▼

Prediction market trading strategies include V2 insurance models, multi-timeframe trading, and cross-venue price discrepancy analysis. These strategies identify arbitrage opportunities and hedge risk by trading event outcomes on Polymarket and Kalshi.

Do I need Python and TypeScript to analyze prediction market data?▼

Yes, you need both Python and TypeScript environments with specific libraries and API access to analyze prediction market data. These dependencies support the backend processing required for event mapping and executing auto-trading strategies.

Can I use prediction markets to hedge crypto asset price risks?▼

Prediction markets provide hedging mechanisms for crypto asset price risks through V2 insurance models. By trading on event outcomes via Polymarket and Kalshi APIs, you can offset potential losses from adverse real-world market movements.

What is the best way to detect cross-venue price discrepancies?▼

Detecting cross-venue price discrepancies involves analyzing event pricing variations between platforms like Polymarket and Kalshi. This Skill automates the comparison process to identify arbitrage opportunities for automated crypto trading execution.

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