Quick Start

Execute your first autonomous prediction market trade in 5 minutes.

---

Prerequisites

Before starting, ensure you have:

• ✅ MoltMarket installed (Installation Guide)

• ✅ Configuration file created at ~/.moltmarket/config.yaml

• ✅ At least one platform configured (Polymarket or Kalshi)

• ✅ Funded wallet with $50+ for testing

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Step 1: Initialize Agent

Create a new Python file market_agent.py:

from openclaw import Agent
from moltmarket import PredictionMarketProvider

# Initialize agent with MoltMarket
agent = Agent(
    name="market_analyst",
    providers=[
        PredictionMarketProvider(
            platforms=["polymarket", "kalshi"],
            config_path="~/.moltmarket/config.yaml"
        )
    ]
)

print("✓ Agent initialized successfully")

Run the agent:

python market_agent.py

Expected output:

✓ Agent initialized successfully
✓ Connected to Polymarket
✓ Connected to Kalshi

---

Step 2: Search Markets

Add natural language market search:

# Search for markets
result = agent.run("""
  Find presidential election markets with > $1M liquidity
  on Polymarket and Kalshi
""")

print(result)

Expected output:

{
  "markets": [
    {
      "id": "0x1a2b3c...",
      "platform": "polymarket",
      "title": "Will Donald Trump win the 2024 presidential election?",
      "probability": 0.47,
      "liquidity": 5200000,
      "volume_24h": 850000,
      "close_date": "2024-11-05T23:59:59Z"
    },
    {
      "id": "PRES-2024",
      "platform": "kalshi",
      "title": "Presidential Election Winner 2024",
      "probability": 0.52,
      "liquidity": 2100000,
      "volume_24h": 320000,
      "close_date": "2024-11-05T23:59:59Z"
    }
  ],
  "count": 2
}

---

Step 3: Open a Position

Execute a conditional trade:

# Conditional position opening
result = agent.run("""
  If the presidential election market on Polymarket has
  probability < 45%, buy $100 YES position.

  Set stop-loss at 35% and take-profit at 65%.
""")

print(result)

Expected output:

{
  "status": "executed",
  "market_id": "0x1a2b3c...",
  "platform": "polymarket",
  "side": "YES",
  "amount": 100,
  "shares": 212.77,
  "avg_price": 0.47,
  "position_id": "pos_9x8y7z...",
  "stop_loss": 0.35,
  "take_profit": 0.65,
  "transaction_hash": "0x5d6e7f..."
}

---

Step 4: Monitor Portfolio

Check your positions and P&L:

# Get portfolio overview
result = agent.run("""
  Show all open positions with current P&L
""")

print(result)

Expected output:

{
  "positions": [
    {
      "position_id": "pos_9x8y7z...",
      "market": "Presidential Election 2024",
      "platform": "polymarket",
      "side": "YES",
      "shares": 212.77,
      "entry_price": 0.47,
      "current_price": 0.51,
      "unrealized_pnl": 8.51,
      "unrealized_pnl_percent": 8.51
    }
  ],
  "total_positions": 1,
  "total_value": 108.51,
  "total_unrealized_pnl": 8.51
}

---

Step 5: Close Position

Close your position when ready:

# Close position at market price
result = agent.run("""
  Close my position in the presidential election market
  on Polymarket at market price
""")

print(result)

Expected output:

{
  "status": "closed",
  "position_id": "pos_9x8y7z...",
  "market": "Presidential Election 2024",
  "platform": "polymarket",
  "shares_sold": 212.77,
  "exit_price": 0.51,
  "realized_pnl": 8.51,
  "realized_pnl_percent": 8.51,
  "fees": 0.50,
  "net_profit": 8.01
}

---

Complete Example

Here's the full working example:

from openclaw import Agent
from moltmarket import PredictionMarketProvider
import time

# Initialize agent
agent = Agent(
    name="market_analyst",
    providers=[
        PredictionMarketProvider(
            platforms=["polymarket", "kalshi"],
            config_path="~/.moltmarket/config.yaml"
        )
    ]
)

# 1. Search markets
print("Step 1: Searching markets...")
markets = agent.run("""
  Find presidential election markets with > $1M liquidity
""")
print(f"✓ Found {markets['count']} markets\n")

# 2. Open position
print("Step 2: Opening position...")
position = agent.run("""
  If Polymarket presidential market probability < 45%,
  buy $100 YES position with stop-loss at 35%
""")
print(f"✓ Opened position: {position['shares']} shares @ ${position['avg_price']}\n")

# 3. Monitor (wait 60 seconds)
print("Step 3: Monitoring position...")
time.sleep(60)

portfolio = agent.run("Show portfolio P&L")
print(f"✓ Current P&L: ${portfolio['total_unrealized_pnl']:.2f}\n")

# 4. Close position
print("Step 4: Closing position...")
result = agent.run("Close presidential election position at market price")
print(f"✓ Closed with profit: ${result['net_profit']:.2f}")

Run the complete example:

python market_agent.py

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Advanced Examples

Arbitrage Detection

agent.run("""
  Monitor presidential election markets on Polymarket and Kalshi.
  Alert when probability difference > 5%.
  If Polymarket < 45% and Kalshi > 50%, execute arbitrage
  with $200 position size.
""")

Market Making

agent.run("""
  Place limit orders on both sides of Fed rate decision market.
  Maintain 2% spread with $500 depth per side.
  Cancel and rebalance every 5 minutes.
""")

Portfolio Rebalancing

agent.run("""
  Target allocation: 40% politics, 30% economics, 30% tech.
  Rebalance when drift > 10% from targets.
  Report concentration risk.
""")

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Safety Tips

1. Start Small - Test with $50-100 before scaling

2. Set Stop-Losses - Always define maximum loss tolerance

3. Monitor Positions - Check portfolio at least daily

4. Understand Markets - Read market rules before trading

5. Use Demo Mode - Kalshi offers demo environment for testing

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What's Next?

Now that you've executed your first trade, explore:

• Configuration Guide - Advanced security and risk settings

• Agent Setup - Multi-agent coordination patterns

• MCP Tools Reference - All available tools

• Security Best Practices - Hardware wallets and session keys

• Use Case Examples - Production strategies

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Troubleshooting

Position Not Executing

Cause: Insufficient balance or risk limits exceeded

Solution:

# Check risk limits
agent.run("Show current risk limits and exposure")

# Increase position size limit if needed (config.yaml)
# security.max_position_size: 1000

"Market Not Found" Error

Cause: Market ID changed or market closed

Solution:

# Search for current market ID
agent.run("Find latest presidential election market on Polymarket")

Transaction Failed

Cause: Insufficient gas, slippage too high, or market moved

Solution:

# Retry with higher slippage tolerance
agent.run("""
  Buy $100 YES position with 2% slippage tolerance
""")

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Support

Questions? Reach out:

• GitHub Discussions

• Email Support

• Documentation