FI

finding-arbitrage-opportunities

Scans multiple crypto exchanges for price spreads and arbitrage opportunities.

Install

mkdir -p .claude/skills/finding-arbitrage-opportunities && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1603" && unzip -o skill.zip -d .claude/skills/finding-arbitrage-opportunities && rm skill.zip

Installs to .claude/skills/finding-arbitrage-opportunities

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Detect profitable arbitrage opportunities across CEX, DEX, and cross-chain
74 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Scan for price spreads on specific cryptocurrency pairs
  • Compare prices across multiple centralized exchanges
  • Compare prices across decentralized exchanges including gas costs
  • Discover triangular arbitrage opportunities within a single exchange
  • Identify cross-chain arbitrage opportunities for stablecoins
  • Monitor arbitrage opportunities in real-time with threshold alerts

How it works

The skill aggregates cryptocurrency prices from CEX and DEX sources, then calculates net profit after fees for direct, triangular, and cross-chain arbitrage paths. It provides real-time monitoring and export options for identified opportunities.

Inputs & outputs

You give it
Cryptocurrency pair (e.g., ETH USDC), optional exchanges, chains, or minimum profit
You get back
Best arbitrage opportunity with profit estimate, buy/sell recommendation, and risk level

When to use finding-arbitrage-opportunities

  • Scan for price spreads between exchanges
  • Calculate arbitrage profit after trading fees
  • Identify triangular arbitrage paths
  • Compare DEX and CEX prices in real-time

About this skill

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

ErrorCauseFix
Rate limitedToo many API requestsReduce polling frequency or add API key
Stale pricesData older than 10sFlagged with warning; retry
No spreadEfficient market pricingNormal condition; try different pairs
Insufficient liquidityTrade exceeds order book depthReduce 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

When not to use it

  • When the market is efficient and shows no spread
  • When trade size exceeds order book depth

Prerequisites

Python 3.9+ with `httpx`, `rich`, and `networkx` packagesInternet access for API calls

Limitations

  • Rate limits can occur with too many API requests
  • Prices may become stale if data is older than 10 seconds
  • Insufficient liquidity can prevent large trades

How it compares

This skill automates the aggregation of market data and calculation of net profits for various arbitrage strategies, unlike manual price comparison across multiple exchange interfaces.

Compared to similar skills

finding-arbitrage-opportunities side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
finding-arbitrage-opportunities (this skill)325dReviewIntermediate
quant-analyst1032moNo flagsAdvanced
stock-analyzer712moReviewBeginner
google-analytics436moReviewIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

More by jeremylongshore

View all by jeremylongshore

analyzing-logs

jeremylongshore

Analyze application logs to detect performance issues, identify error patterns, and improve stability by extracting key insights.

14123

ollama-setup

jeremylongshore

Configure auto-configure Ollama when user needs local LLM deployment, free AI alternatives, or wants to eliminate hosted API costs. Trigger phrases: "install ollama", "local AI", "free LLM", "self-hosted AI", "replace OpenAI", "no API costs". Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

1167

backtesting-trading-strategies

jeremylongshore

Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".

1071

generating-database-seed-data

jeremylongshore

Process this skill enables AI assistant to generate realistic test data and database seed scripts for development and testing environments. it uses faker libraries to create realistic data, maintains relational integrity, and allows configurable data volumes. u... Use when working with databases or data models. Trigger with phrases like 'database', 'query', or 'schema'.

1033

cursor-codebase-indexing

jeremylongshore

Execute set up and optimize Cursor codebase indexing. Triggers on "cursor index setup", "codebase indexing", "index codebase", "cursor semantic search". Use when working with cursor codebase indexing functionality. Trigger with phrases like "cursor codebase indexing", "cursor indexing", "cursor".

885

testing-mobile-apps

jeremylongshore

Execute mobile app testing on iOS and Android devices/simulators. Use when performing specialized testing. Trigger with phrases like "test mobile app", "run iOS tests", or "validate Android functionality".

810

You might also like

quant-analyst

zenobi-us

Expert quantitative analyst specializing in financial modeling, algorithmic trading, and risk analytics. Masters statistical methods, derivatives pricing, and high-frequency trading with focus on mathematical rigor, performance optimization, and profitable strategy development.

103355

stock-analyzer

FrancyJGLisboa

Provides comprehensive technical analysis for stocks and ETFs using RSI, MACD, Bollinger Bands, and other indicators. Activates when user requests stock analysis, technical indicators, trading signals, or market data for specific ticker symbols.

71214

google-analytics

davila7

Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.

43193

data-engineering

pluginagentmarketplace

ETL pipelines, Apache Spark, data warehousing, and big data processing. Use for building data pipelines, processing large datasets, or data infrastructure.

13192

math-tools

ananddtyagi

Deterministic mathematical computation using SymPy. Use for ANY math operation requiring exact/verified results - basic arithmetic, algebra (simplify, expand, factor, solve equations), calculus (derivatives, integrals, limits, series), linear algebra (matrices, determinants, eigenvalues), trigonometry, number theory (primes, GCD/LCM, factorization), and statistics. Ensures mathematical accuracy by using symbolic computation rather than LLM estimation.

26134

crawl4ai

basher83

This skill should be used when users need to scrape websites, extract structured data, handle JavaScript-heavy pages, crawl multiple URLs, or build automated web data pipelines. Includes optimized extraction patterns with schema generation for efficient, LLM-free extraction.

21137

Search skills

Search the agent skills registry