Overview
Detect and analyze arbitrage opportunities across cryptocurrency exchanges and DeFi protocols. Aggregates prices from CEX and DEX sources, calculates net profit after fees, and identifies direct, triangular, and cross-chain arbitrage paths.
Prerequisites
- Python 3.9+ with
httpx,rich, andnetworkxpackages - Internet access for API calls (no API keys required for basic use)
- Optional: Exchange API keys for real-time order book access
- Understanding of arbitrage concepts and trading fees
Instructions
-
Quick spread scan on a specific pair:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py scan ETH USDC
Shows current prices per exchange, spread %, estimated profit after fees, and recommended action.
-
Multi-exchange comparison across specific exchanges:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py scan ETH USDC \ --exchanges binance,coinbase,kraken,kucoin,okx -
DEX price comparison across decentralized exchanges:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py scan ETH USDC --dex-onlyCompares Uniswap V3, SushiSwap, Curve, Balancer with gas cost estimates.
-
Triangular arbitrage discovery within a single exchange:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py triangular binance --min-profit 0.5 -
Cross-chain opportunities across different blockchains:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py cross-chain USDC \ --chains ethereum,polygon,arbitrum -
Real-time monitoring with threshold alerts:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py monitor ETH USDC \ --threshold 0.5 --interval 5 -
Export opportunities for bot integration:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py scan ETH USDC --output json > opportunities.json
Output
- Quick mode (default): Best opportunity with profit estimate, buy/sell recommendation, risk level
- Detailed mode (
--detailed): All exchange prices, fee breakdown, slippage estimates, historical spread context - Monitor mode: Real-time updates with threshold alerts and trend indicators
See ${CLAUDE_SKILL_DIR}/references/implementation.md for exchange fee tables and output format examples.
Error Handling
| Error | Cause | Fix |
|---|---|---|
| Rate limited | Too many API requests | Reduce polling frequency or add API key |
| Stale prices | Data older than 10s | Flagged with warning; retry |
| No spread | Efficient market pricing | Normal condition; try different pairs |
| Insufficient liquidity | Trade exceeds order book depth | Reduce trade size |
Examples
Quick ETH/USDC spread scan - Find best buy/sell across all CEX exchanges:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py scan ETH USDC
Sample detection output:
ARB OPPORTUNITY: ETH/USDC
Buy: Binance @ $3,198.50 | Sell: Coinbase @ $3,214.20
Spread: 0.49% | Net Profit (after fees): 0.29% ($9.27 per ETH)
Risk: LOW | Confidence: HIGH | Window: ~30s
Triangular arb on Binance - Discover circular paths with minimum 0.5% net profit:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py triangular binance --min-profit 0.5
Cross-chain USDC opportunities - Compare stablecoin prices across L1/L2 chains:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py cross-chain USDC --chains ethereum,polygon,arbitrum
Calculate exact profit - Detailed fee breakdown for a specific trade:
python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py calc \
--buy-exchange binance --sell-exchange coinbase --pair ETH/USDC --amount 10 # 10 = trade size in ETH
Resources
- CoinGecko API - Free price data
- CCXT Library - Unified exchange API
- Uniswap Subgraph - DEX data
${CLAUDE_SKILL_DIR}/references/implementation.md- Exchange fee tables, configuration, advanced arbitrage types, disclaimer