polymarket-trading

Automate creation, testing, and deployment of trading strategies on Polymarket.

Updated Feb 11, 2026
One-click install
npx skills add https://github.com/storyclaw-official/storyclaw-assistant --skill polymarket-trading-storyclaw-official
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: polymarket-trading
Source: https://github.com/storyclaw-official/storyclaw-assistant/tree/main/skills/polymarket-trading
Command: npx skills add https://github.com/storyclaw-official/storyclaw-assistant --skill polymarket-trading-storyclaw-official

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires py-clob-client, and includes scripts (resource) and credentials (resource) and strategies (resource) and state (resource) components.

What problem does it solve?

This Skill automates the process of designing, testing, and deploying trading strategies on the Polymarket prediction market platform, aiming to achieve profitable automated trading.

Core Features & Use Cases

  • Strategy Design: Collaboratively define trading strategies based on market analysis and user input.
  • Paper Trading & Auto-Improvement: Run strategies in a simulated environment (dry-run), automatically adjust parameters to improve performance based on defined metrics, and track progress.
  • Live Trading Transition: Once a strategy demonstrates a profitable edge, it can be transitioned to live trading after user confirmation.
  • Use Case: A user interested in trading on political prediction markets can work with the bot to define a strategy, let it paper trade, automatically optimize its parameters, and then approve it for live trading when it shows consistent profitability.

Quick Start

Use the polymarket-trading skill to set up your credentials by running python3 {baseDir}/scripts/polymarket.py setup.

Frequently Asked Questions about polymarket-trading

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

FAQPage Schema
How do I automate trading strategies on Polymarket?

Automating Polymarket trading strategies involves designing market filters and signal methods, running simulated paper trades to auto-improve parameters, and transitioning to live execution once a profitable edge is confirmed.

How does automated strategy testing work for prediction markets?

Automated strategy testing for prediction markets works by executing dry-run paper trades, automatically adjusting parameters based on performance metrics like edge and win rate, and tracking progress before live deployment.

Do I need Python and API credentials to use a Polymarket trading bot?

Yes, you need Python 3 and specific environment variables for API access to use a Polymarket trading bot, configuring your credentials initially via the provided setup script.

What is the best way to auto-improve trading bot parameters?

The best way to auto-improve trading bot parameters is running strategies in a simulated dry-run environment that automatically adjusts configurations based on performance metrics like edge and win rate.

Can I transition a prediction market strategy from paper trading to live trading?

Yes, you can transition a prediction market strategy from paper trading to live trading after user confirmation, once the strategy demonstrates a profitable edge during the simulated dry-run phase.

When should I avoid using algorithmic trading on prediction markets?

You should avoid algorithmic trading on prediction markets if your strategy has not demonstrated a consistent profitable edge during paper trading and auto-improvement dry-runs.