name: headless-trading description: "Autonomous trading for AI agents on Solana and BNB Chain. Use when: (1) executing token swaps on DEXs (Raydium, PancakeSwap), (2) checking token prices and balances, (3) monitoring liquidity pools, (4) implementing trading strategies, (5) managing portfolio positions. Supports headless execution without browser interaction."

Headless Trading

Autonomous trading toolkit for AI agents on Solana (Raydium) and BNB Chain (PancakeSwap).

Core Capabilities

1. Token Swaps

Execute swaps on decentralized exchanges without browser interaction:

Raydium (Solana): SOL ↔ SPL tokens
PancakeSwap (BNB Chain): BNB ↔ BEP20 tokens

2. Price Monitoring

Fetch real-time token prices:

DEX liquidity pool prices
Multiple pair support
Slippage calculation

3. Portfolio Management

Check balances and positions:

Native token balances (SOL, BNB)
Token holdings across wallets
Transaction history

4. Strategy Execution

Implement automated trading strategies:

Limit orders (via monitoring + execution)
DCA (Dollar Cost Averaging)
Stop-loss / Take-profit
Arbitrage opportunities

Quick Start

Prerequisites

Private key (environment variable or secure storage)
RPC endpoint (public or private node)
Python 3.8+ with dependencies

Installation

pip install solana web3 anchorpy raydium-py base58
pip install web3 pancakeswap-sdk

Basic Swap Example

from scripts.raydium_swap import swap_on_raydium

# Swap 0.1 SOL for USDC
tx_hash = swap_on_raydium(
    input_token="SOL",
    output_token="USDC",
    amount=0.1,
    slippage=1.0  # 1% slippage tolerance
)

Workflow Decision Tree

1. What chain are you trading on?

Solana → Use raydium_* scripts + See references/raydium.md
BNB Chain → Use pancakeswap_* scripts + See references/pancakeswap.md

2. What operation do you need?

Get token price → get_price.py
Check wallet balance → get_balance.py
Execute swap → swap.py
Monitor liquidity → monitor_pool.py

3. What strategy are you implementing?

One-time trade → Direct swap
Automated strategy → See references/strategies.md

Trading Operations

Get Token Price

from scripts.get_price import get_token_price

# Get current price of a token
price = get_token_price(
    chain="solana",
    token_address="EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v",  # USDC
    quote_token="SOL"
)
print(f"Price: {price} SOL")

Check Wallet Balance

from scripts.get_balance import get_balance

# Check SOL balance
balance = get_balance(
    chain="solana",
    wallet_address="YOUR_WALLET_ADDRESS"
)
print(f"Balance: {balance} SOL")

Execute Swap

from scripts.swap import execute_swap

# Swap tokens with slippage protection
result = execute_swap(
    chain="solana",
    input_token="SOL",
    output_token="USDC",
    amount=0.5,
    slippage=1.0,
    private_key="YOUR_PRIVATE_KEY"  # Use env var in production
)

Monitor Liquidity Pool

from scripts.monitor_pool import get_pool_info

# Get liquidity pool stats
pool_info = get_pool_info(
    chain="solana",
    token_a="SOL",
    token_b="USDC"
)
print(f"Liquidity: ${pool_info['liquidity']}")
print(f"24h Volume: ${pool_info['volume_24h']}")

Security Best Practices

1. Private Key Management

NEVER hardcode private keys. Use environment variables or secure vaults:

import os

PRIVATE_KEY = os.getenv("TRADING_PRIVATE_KEY")
if not PRIVATE_KEY:
    raise ValueError("TRADING_PRIVATE_KEY not set")

2. Slippage Protection

Always set reasonable slippage limits:

Stablecoins: 0.1-0.5%
Blue chips: 0.5-1%
Low liquidity: 1-3% (risky)

3. Transaction Simulation

Test swaps on devnet/testnet first:

result = execute_swap(
    chain="solana",
    input_token="SOL",
    output_token="USDC",
    amount=0.01,  # Small test amount
    slippage=1.0,
    simulate=True  # Dry run
)

4. Rate Limiting

Respect RPC rate limits:

Public RPCs: ~5 req/sec
Private RPCs: Check provider limits

5. Error Handling

Always handle transaction failures:

try:
    tx_hash = execute_swap(...)
    print(f"Success: {tx_hash}")
except InsufficientFundsError:
    print("Not enough balance")
except SlippageExceededError:
    print("Price moved too much")
except RPCError as e:
    print(f"RPC failed: {e}")

Common Patterns

Pattern 1: Price Monitoring Bot

Monitor token prices and execute when conditions are met:

from scripts.get_price import get_token_price
from scripts.swap import execute_swap
import time

TARGET_PRICE = 100  # USDC per token
CHECK_INTERVAL = 60  # seconds

while True:
    price = get_token_price(chain="solana", token_address="...", quote_token="USDC")
    
    if price <= TARGET_PRICE:
        execute_swap(
            chain="solana",
            input_token="USDC",
            output_token="TARGET_TOKEN",
            amount=100,
            slippage=1.0
        )
        break
    
    time.sleep(CHECK_INTERVAL)

Pattern 2: DCA (Dollar Cost Averaging)

Buy fixed amounts at regular intervals:

import schedule

def dca_buy():
    execute_swap(
        chain="solana",
        input_token="SOL",
        output_token="BTC",
        amount=0.1,  # 0.1 SOL every day
        slippage=1.0
    )

# Run daily at 9 AM
schedule.every().day.at("09:00").do(dca_buy)

Pattern 3: Stop-Loss

Sell when price drops below threshold:

ENTRY_PRICE = 100
STOP_LOSS_PERCENT = 10  # 10% loss

while True:
    current_price = get_token_price(...)
    loss_percent = ((ENTRY_PRICE - current_price) / ENTRY_PRICE) * 100
    
    if loss_percent >= STOP_LOSS_PERCENT:
        execute_swap(...)  # Sell position
        break
    
    time.sleep(60)

Resources

scripts/

Executable Python scripts for trading operations:

get_price.py - Fetch token prices from DEXs
get_balance.py - Check wallet balances
swap.py - Execute token swaps
monitor_pool.py - Get liquidity pool info
raydium_swap.py - Raydium-specific swap implementation
pancakeswap_swap.py - PancakeSwap-specific swap implementation

references/

raydium.md - Raydium DEX API reference and pool addresses
pancakeswap.md - PancakeSwap DEX API reference
strategies.md - Detailed trading strategy implementations
rpc_endpoints.md - List of public/private RPC providers

Limitations

Gas fees: Transactions require native tokens (SOL, BNB)
Slippage: High volatility can cause failed transactions
RPC reliability: Public RPCs may be slow/unstable
MEV: Transactions may be frontrun on popular pairs

Troubleshooting

"Insufficient funds"

Check wallet balance with get_balance.py
Ensure enough native token for gas fees

"Slippage exceeded"

Increase slippage tolerance (carefully)
Wait for lower volatility
Split large orders into smaller ones

"Transaction failed"

Check RPC endpoint is responsive
Verify token addresses are correct
Ensure wallet has approval for token spend

"Rate limited"

Switch to private RPC
Add delays between requests
Use multiple RPC endpoints

Headless Crypto trading for agents

Description