Agent-Skills.md

Agent Skills: Simulating Flash Loans

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UncategorizedID: jeremylongshore/claude-code-plugins-plus-skills/simulating-flash-loans

Repository

jeremylongshore/claude-code-plugins-plus-skills
jeremylongshoreLicense: NOASSERTION
1,723221

Install this agent skill to your local

pnpm dlx add-skill https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/HEAD/plugins/crypto/flash-loan-simulator/skills/simulating-flash-loans

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plugins/crypto/flash-loan-simulator/skills/simulating-flash-loans/SKILL.md

Skill Metadata

Name
simulating-flash-loans
Description
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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

| Error | Cause | Solution | |-------|-------|----------| | RPC Rate Limit | Too many requests | Switch to backup endpoint or wait | | Stale Prices | Data older than 30s | Auto-refreshes with warning | | No Profitable Route | All routes lose after costs | Try different pairs or amounts | | Insufficient Liquidity | Trade exceeds pool depth | Reduce 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