Imported from jeremylongshore/tons-of-skills-marketplace (skills/.curated/finding-arbitrage-opportunities/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill finding-arbitrage-opportunities. Copyright stays with the author (MIT).

Finding Arbitrage Opportunities

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, and networkx packages
• 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

1. 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.

2. Multi-exchange comparison across specific exchanges:

   python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py scan ETH USDC \
     --exchanges binance,coinbase,kraken,kucoin,okx

3. DEX price comparison across decentralized exchanges:

   python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py scan ETH USDC --dex-only

   Compares Uniswap V3, SushiSwap, Curve, Balancer with gas cost estimates.

4. Triangular arbitrage discovery within a single exchange:

   python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py triangular binance --min-profit 0.5

5. Cross-chain opportunities across different blockchains:

   python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py cross-chain USDC \
     --chains ethereum,polygon,arbitrum

6. Real-time monitoring with threshold alerts:

   python ${CLAUDE_SKILL_DIR}/scripts/arb_finder.py monitor ETH USDC \
     --threshold 0.5 --interval 5

7. 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

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