Detailed Instructions

Begin by defining a modular architecture where the core bot logic is separate from configuration, data fetching, and transaction execution modules. This separation of concerns makes the bot easier to test, maintain, and upgrade. The primary dependency is Ethers.js v6 for blockchain interaction. You will also need a library for managing private keys securely, such as dotenv, and potentially a task scheduler like node-cron for periodic execution.

• Sub-step 1: Initialize a new Node.js project using npm init -y and create the basic directory structure (src/, config/, abis/).
• Sub-step 2: Install core dependencies: npm install ethers dotenv node-cron.
• Sub-step 3: Create a .env file to store sensitive data like your private key and RPC provider URL (e.g., from Infura or Alchemy). Never hardcode these.

Tip: Use environment-specific .env files (.env.production) and consider a key management service for production to avoid storing raw private keys.

Detailed Instructions

A reliable connection to the blockchain is critical. You must configure a JSON-RPC provider and instantiate a Wallet object. For mainnet interactions, use a paid RPC endpoint from services like Alchemy or Infura for higher rate limits and reliability. The wallet will be used to sign and send transactions. Always calculate and monitor gas fees dynamically.

• Sub-step 1: In your configuration module, load the environment variables: RPC_URL and PRIVATE_KEY.
• Sub-step 2: Create a provider: const provider = new ethers.JsonRpcProvider(process.env.RPC_URL);.
• Sub-step 3: Create the wallet: const wallet = new ethers.Wallet(process.env.PRIVATE_KEY, provider);. The wallet address, like 0x742d35Cc6634C0532925a3b844Bc9e..., will be your bot's identity on-chain.

Tip: For initial testing, use a testnet (e.g., Sepolia) and testnet ETH. Always keep a small balance for gas in your bot's wallet.

Detailed Instructions

To call functions on the lending protocol's smart contracts, you need their Application Binary Interfaces (ABIs). These are typically found in the protocol's GitHub repository or on Etherscan. For a protocol like Aave, you would need the ABIs for the LendingPool and possibly the ERC20 token contracts. Store these ABIs as JSON files in your abis/ directory.

• Sub-step 1: Locate and download the necessary ABIs. For example, the Aave V2 LendingPool address on mainnet is 0x7d2768dE32b0b80b7a3454c06BdAc94A69DDc7A9.
• Sub-step 2: In your code, import the ABI JSON file and create a contract instance: const lendingPool = new ethers.Contract(lendingPoolAddress, lendingPoolABI, wallet);.
• Sub-step 3: Similarly, create contract instances for relevant tokens, like USDC at 0xA0b86991c6218b36c1d19D4a2e9Eb0cE3606eB48.

Tip: Use TypeChain to generate type-safe contract bindings, which will provide autocomplete and reduce errors.

Detailed Instructions

Before executing any transactions, your bot must reliably read on-chain data. Implement a health check function that verifies the bot's connectivity, wallet balance, and access to protocol data. This involves querying the user account data from the lending protocol, which includes details like total collateral, debt, and available borrowing power.

• Sub-step 1: Create a function to check the wallet's ETH balance: const balance = await provider.getBalance(wallet.address);.
• Sub-step 2: Call the protocol's getUserAccountData function: const userData = await lendingPool.getUserAccountData(wallet.address);. This returns an array with values like health factor.
• Sub-step 3: Set up basic logging (using console.log or winston) to output these values. For example, log: Health Factor: ${ethers.formatUnits(userData.healthFactor, 18)}.

Tip: A health factor below 1.0 means the position can be liquidated. Your bot's logic should monitor this critical metric.

Detailed Instructions

First, you must establish a secure connection to the target blockchain network and instantiate the protocol's smart contract interfaces. Initialize your Web3 provider using a reliable RPC endpoint, such as https://eth-mainnet.g.alchemy.com/v2/your-api-key. Then, load your wallet's private key from a secure environment variable to sign transactions. The core action is to create contract instances for the protocol's key contracts, like the LendingPool or Comptroller, using their ABI and deployed address. For example, on Ethereum's Aave V3, the main pool address is 0x87870Bca3F3fD6335C3F4ce8392D69350B4fA4E2.

• Sub-step 1: Install and import necessary libraries like web3.js or ethers.js.
• Sub-step 2: Configure the provider and wallet, ensuring the account has sufficient ETH for gas.
• Sub-step 3: Fetch and store the contract ABIs, then instantiate the contract objects.

Tip: Use environment variables for sensitive data like private keys and API keys to avoid hardcoding them into your source code.

Detailed Instructions

The bot's decision engine relies on real-time data about its positions. You must periodically call view functions on the lending protocol contracts to retrieve the user's collateral balances, debt amounts, and the critical health factor. On Compound, for instance, you would call getAccountLiquidity(address account) on the Comptroller. The health factor determines if a position is at risk of liquidation; a value below 1.0 is dangerous. Your logic should parse the returned data structures to extract usable numbers, such as the total collateral value in USD and the total borrowed value.

• Sub-step 1: Create a function getUserPosition() that queries the relevant contract methods for your connected wallet address.
• Sub-step 2: Calculate key metrics: Health Factor, Collateral Ratio, and Available Borrowing Power.
• Sub-step 3: Set up an interval (e.g., every 12 seconds) to poll this data and update an in-memory state object.

Tip: Consider using a library like axios to also pull price oracle data from an external API if needed for accurate USD valuations.

Detailed Instructions

This step involves writing the functions that interact with the protocol to manage collateral. The core action is to call supply() or withdraw() on the lending pool contract. Your bot's strategy must define rules, such as "supply 1 ETH if the health factor is above 2.0" or "withdraw 50% of available USDC if the borrowing rate exceeds 5% APY." You must handle ERC-20 token approvals before supplying. The transaction must be built, signed, and sent, and you should implement robust error handling for revert reasons like insufficient balance or market paused.

• Sub-step 1: For a supply action, first call approve() on the token contract for the lending pool address.
• Sub-step 2: Construct the transaction data for the supply call, specifying the asset address, amount, and onBehalfOf parameter.
• Sub-step 3: Send the transaction, wait for confirmation, and log the transaction hash for auditing.

javascriptCopy
// Example supply transaction with ethers.js
const tx = await lendingPool.supply(assetAddress, amountWei, wallet.address, 0);
await tx.wait();

Detailed Instructions

The borrow/repay logic is critical for managing leverage and risk. The bot must call borrow() or repay() based on predefined conditions, such as borrowing more when asset utilization is low or repaying debt when the health factor nears a safety threshold. Key parameters include the asset address, amount, and interest rate mode (stable vs variable). For repayment, you may need to handle partial repayments and ensure the contract is approved to spend your debt token. Always verify that the resulting health factor remains above your strategy's minimum, e.g., 1.5, to avoid immediate liquidation risk.

• Sub-step 1: Check borrowing capacity and current debt levels before initiating a new borrow.
• Sub-step 2: For a repay, check your wallet balance of the debt token and approve the lending pool if necessary.
• Sub-step 3: Execute the transaction and update the local state after confirmation.

javascriptCopy
// Example borrow for variable interest debt
const borrowTx = await lendingPool.borrow(usdcAddress, amountWei, 2, 0, wallet.address);

Tip: Use a slippage tolerance for variable rate borrows, as rates can change between transaction simulation and execution.

Detailed Instructions

This is where you combine all previous components into an automated loop. The decision engine is a function that runs on a timer, fetching the latest state (Step 2) and checking it against your strategy's rules. For example, a simple rule could be: "If health factor > 3.0, borrow up to 20% of borrowing capacity to buy more collateral." The engine should call the appropriate action functions from Steps 3 and 4. Implement rate limiting and error backoff to avoid spamming the RPC or failing transactions due to network congestion. Log all decisions and their outcomes for review.

• Sub-step 1: Define clear numerical thresholds for health factor, collateral ratios, and target borrow rates.
• Sub-step 2: In the main loop, compare current metrics against thresholds to decide on an action (Supply, Withdraw, Borrow, Repay, or Do Nothing).
• Sub-step 3: If an action is triggered, call the corresponding function, handle any errors, and wait for the next cycle.

Tip: Start with a long polling interval (e.g., 60 seconds) in testing to avoid excessive gas costs and rate limits while you refine your logic.