simulating-flash-loans

模拟去中心化金融中的闪电贷策略,支持跨协议的价格套利、清算机会评估及多平台费用对比,提供净收益计算、交易成本分解与风险评分,帮助用户在不执行真实交易的前提下验证策略可行性。

快捷安装

在终端运行此命令,即可一键安装该 Skill 到您的 Claude 中

npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill "simulating-flash-loans"

Simulating Flash Loans

Contents

Overview | Prerequisites | Instructions | Output | Error Handling | Examples | Resources

Overview

Simulate flash loan strategies across Aave V3, dYdX, and Balancer with profitability calculations, gas cost estimation, and risk assessment. Evaluate flash loan opportunities without executing real transactions.

Prerequisites

  1. Install Python 3.9+ with web3, httpx, and rich packages
  2. Configure RPC endpoint access (free public RPCs via https://chainlist.org work fine)
  3. Optionally add Etherscan API key for better gas estimates
  4. Set RPC in ${CLAUDE_SKILL_DIR}/config/settings.yaml or use ETH_RPC_URL env var

Instructions

  1. Simulate a two-DEX arbitrage with automatic fee and gas calculation:
    python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py arbitrage ETH USDC 100 \
      --dex-buy uniswap --dex-sell sushiswap
  2. Compare flash loan providers to find the cheapest for your strategy:
    python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py arbitrage ETH USDC 100 --compare-providers
  3. Analyze liquidation profitability on lending protocols:
    python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py liquidation \
      --protocol aave --health-factor 0.95
  4. Simulate triangular arbitrage with multi-hop circular paths:
    python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py triangular \
      ETH USDC WBTC ETH --amount 50
  5. Add risk assessment (MEV competition, execution, protocol, liquidity) to any simulation:
    python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py arbitrage ETH USDC 100 --risk-analysis
  6. Run full analysis combining all features:
    python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py arbitrage ETH USDC 100 \
      --full --output json > simulation.json

Output

  • Quick Mode: Net profit/loss, provider recommendation, Go/No-Go verdict
  • Breakdown Mode: Step-by-step transaction flow with individual cost components
  • Comparison Mode: All providers ranked by net profit with fee differences
  • Risk Analysis: Competition, execution, protocol, and liquidity scores (0-100) with viability grade (A-F)

See ${CLAUDE_SKILL_DIR}/references/implementation.md for detailed output examples and risk scoring methodology.

Error Handling

ErrorCauseSolution
RPC Rate LimitToo many requestsSwitch to backup endpoint or wait
Stale PricesData older than 30sAuto-refreshes with warning
No Profitable RouteAll routes lose after costsTry different pairs or amounts
Insufficient LiquidityTrade exceeds pool depthReduce amount or split across pools

See ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error handling.

Examples

Basic arbitrage simulation:

python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py arbitrage ETH USDC 100 \
  --dex-buy uniswap --dex-sell sushiswap

Find cheapest provider:

python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py arbitrage ETH USDC 100 --compare-providers

Liquidation opportunity scan:

python ${CLAUDE_SKILL_DIR}/scripts/flash_simulator.py liquidation --protocol aave --health-factor 0.95

See ${CLAUDE_SKILL_DIR}/references/examples.md for multi-provider comparison and backtesting examples.

Resources