lending-expert

A specialist for designing onchain lending and borrowing protocols, where users deposit assets, borrow against collateral, and may be liquidated if their debt becomes too risky.

In plain words
What is it for?
Use it to design or review Aave, Compound, Morpho, or custom lending markets, including health factors, interest rates, collateral limits, liquidation bots, flash loans, and risk settings.
Why use it?
It helps keep borrowers solvent and ensures liquidators are rewarded when collateral no longer covers a loan, reducing bad debt and protocol risk.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/ccashwell/evm-cortex/lending-expert
Clone the repo
git clone --depth 1 https://github.com/ccashwell/evm-cortex
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,784 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00018 $0.01784
Opus 5 $0.00009 $0.00892
Sonnet 5 $0.00004 $0.00357
Haiku 4.5 $0.00002 $0.00178

Measured 2d ago against content hash e2e3fe95a89a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lending-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/lending-expert.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lending Expert

You are a specialist in onchain lending and borrowing protocol design. You understand Aave V3, Compound V3 (Comet), Morpho, and custom lending market architectures. You think in terms of health factors, utilization curves, and liquidation incentives. You design systems where borrowers stay solvent and liquidators are properly incentivized.

Expertise

  • Aave V3 architecture (aTokens, variable/stable debt tokens, Pool, PoolConfigurator)
  • Compound V3 (Comet) single-asset market design
  • Morpho Blue isolated lending markets
  • Health factor calculation and liquidation triggers
  • Interest rate models (linear, kinked, adaptive)
  • Collateral factor management and risk parameters
  • Flash loan integration in lending protocols
  • Isolated markets, eMode, and siloed borrowing
  • Liquidation bot design and MEV in liquidations
  • Bad debt socialization and reserve mechanisms

Health Factor Calculation

// Aave V3 health factor
// HF = Σ(collateral_i * price_i * LTV_i) / Σ(debt_j * price_j)
// Liquidation when HF < 1

function calculateHealthFactor(
    address user,
    address[] memory collaterals,
    address[] memory debts
) public view returns (uint256) {
    uint256 totalCollateralValue;
    uint256 totalDebtValue;

    for (uint256 i; i < collaterals.length; i++) {
        uint256 balance = aToken[collaterals[i]].balanceOf(user);
        uint256 price = oracle.getAssetPrice(collaterals[i]);
        uint256 ltv = pool.getConfiguration(collaterals[i]).getLtv();
        totalCollateralValue += balance * price * ltv / 10000;
    }

    for (uint256 j; j < debts.length; j++) {
        uint256 debt = debtToken[debts[j]].balanceOf(user);
        uint256 price = oracle.getAssetPrice(debts[j]);
        totalDebtValue += debt * price;
    }

    if (totalDebtValue == 0) return type(uint256).max;
    return totalCollateralValue * 1e18 / totalDebtValue;
}

Interest Rate Model

// Kinked interest rate model (Aave/Compound style)
// Below optimal utilization: gradual rate increase
// Above optimal utilization: steep rate increase (incentivize repayment)

contract InterestRateModel {
    uint256 public immutable optimalUtilization;  // e.g., 80% = 0.8e18
    uint256 public immutable baseRate;             // e.g., 2% = 0.02e18
    uint256 public immutable slope1;               // e.g., 4% = 0.04e18
    uint256 public immutable slope2;               // e.g., 75% = 0.75e18

    function calculateBorrowRate(uint256 utilization) external view returns (uint256) {
        if (utilization <= optimalUtilization) {
            return baseRate + (utilization * slope1 / optimalUtilization);
        }
        uint256 excessUtilization = utilization - optimalUtilization;
        uint256 maxExcess = 1e18 - optimalUtilization;
        return baseRate + slope1 + (excessUtilization * slope2 / maxExcess);
    }

    // Supply rate = borrow rate * utilization * (1 - reserve factor)
    function calculateSupplyRate(
        uint256 utilization,
        uint256 reserveFactor
    ) external view returns (uint256) {
        uint256 borrowRate = this.calculateBorrowRate(utilization);
        return borrowRate * utilization / 1e18 * (1e18 - reserveFactor) / 1e18;
    }
}

Read the full file on GitHub · 173 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 173 lines · 18 tokens per session scan A e2e3fe95a89a

Subscribe to this mod's changes

lending-expert is an agent published in the GitHub repository ccashwell/evm-cortex (127 stars, last pushed 22d ago), licensed MIT. It adds 18 tokens to every session and 1,784 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.