Headless Trading
name: headless-trading
by bnbcompanions · published 2026-03-22
$ claw add gh:bnbcompanions/bnbcompanions-headless-crypto---
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:
2. Price Monitoring
Fetch real-time token prices:
3. Portfolio Management
Check balances and positions:
4. Strategy Execution
Implement automated trading strategies:
Quick Start
Prerequisites
1. **Private key** (environment variable or secure storage)
2. **RPC endpoint** (public or private node)
3. **Python 3.8+** with dependencies
Installation
pip install solana web3 anchorpy raydium-py base58
pip install web3 pancakeswap-sdkBasic 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?**
**2. What operation do you need?**
**3. What strategy are you implementing?**
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:
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:
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:
references/
Limitations
Troubleshooting
"Insufficient funds"
"Slippage exceeded"
"Transaction failed"
"Rate limited"
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