> ## Documentation Index
> Fetch the complete documentation index at: https://zyfai.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# getAggressivePoolStatus

Get aggressive pool status with derived health, risk level, APY trend, and yield consistency indicators.

## Signature

```typescript theme={null}
getAggressivePoolStatus(chainId?: number): Promise<PoolStatus[]>
```

## Parameters

| Parameter | Type   | Required | Description                                              |
| --------- | ------ | -------- | -------------------------------------------------------- |
| chainId   | number | ❌        | Optional chain ID filter (Base, Arbitrum, Plasma, Sonic) |

## Returns

List of aggressive/degen pools with computed status indicators for quick assessment.

### Return Type

```typescript theme={null}
interface PoolStatus {
  poolName: string;           // Name of the lending pool
  protocolName: string;       // Protocol name (e.g., Morpho, Euler, Harvest)
  chainId: number;            // Blockchain ID where the pool is deployed
  healthScore: string;        // Overall health: "healthy", "moderate", "risky"
  riskLevel: string;          // Risk assessment: "low", "medium", "high"
  apyTrend: string;           // Yield direction: "rising", "falling", "stable"
  yieldConsistency: string;   // Yield volatility: "consistent", "mixed", "volatile"
  liquidityDepth: string;     // Liquidity tier: "deep", "moderate", "shallow"
  avgCombinedApy7d: number | null; // Average combined APY over 7 days
}
```

### Field Descriptions

* **poolName**: The name of the lending pool or vault
* **protocolName**: The DeFi protocol hosting the pool (typically newer or higher-risk protocols)
* **chainId**: The blockchain network ID (8453 = Base, 42161 = Arbitrum, 9745 = Plasma, 146 = Sonic)
* **healthScore**: Aggregate health indicator based on stability metrics and liquidity
  * `"healthy"`: All or most stability indicators are positive, good liquidity depth
  * `"moderate"`: Mixed stability indicators or moderate liquidity (common in aggressive strategies)
  * `"risky"`: Multiple negative stability indicators or shallow liquidity
  * **Calculation**: Combines `tvlStability + apyStability + tvlApyCombinedRisk + liquidityDepth bonus`. Score ≥3 = healthy, ≥1.5 = moderate, \<1.5 = risky
  * **Note**: Aggressive pools may naturally have "moderate" or "risky" health scores due to higher volatility
* **riskLevel**: Count of negative risk signals
  * `"low"`: 0 risk signals (rare in aggressive strategies)
  * `"medium"`: 1-2 risk signals present (common in aggressive pools)
  * `"high"`: 3+ risk signals detected (proceed with caution)
  * **Risk signals include**: Unstable TVL, unstable APY, unstable combined risk, shallow liquidity, >90% utilization
  * **Note**: "Medium" risk in aggressive pools is typical and may still be acceptable for yield-seeking users
* **apyTrend**: Direction of yield movement over time
  * `"rising"`: 7-day APY is >10% higher than 30-day APY (momentum building, possible new incentives)
  * `"falling"`: 7-day APY is >10% lower than 30-day APY (incentives ending, demand decreasing)
  * `"stable"`: APY change between 7d and 30d is within ±10%
  * **Use case**: Rising trends may indicate good entry points; falling trends may signal time to exit
* **yieldConsistency**: Volatility assessment of yield over time
  * `"consistent"`: Spread between 7d and 30d APY is ≤10% (rare in aggressive strategies)
  * `"mixed"`: Spread between 7d and 30d APY is 10-30% (typical for aggressive pools)
  * `"volatile"`: Spread between 7d and 30d APY is >30% (high variability, common with incentive programs)
  * **Note**: Aggressive pools often have "mixed" or "volatile" consistency due to changing incentive structures
* **liquidityDepth**: Liquidity tier - "deep" (>$10M), "moderate" ($1M-$10M), "shallow" (&lt;$1M)
  * Shallow liquidity in aggressive pools increases slippage risk for large deposits
* **avgCombinedApy7d**: Current 7-day average yield (typically higher than conservative pools)

## Example

```typescript theme={null}
// Get aggressive pool status for Arbitrum
const arbAggressiveStatus = await sdk.getAggressivePoolStatus(42161);

// Sort by APY to find highest yields
const sortedByApy = arbAggressiveStatus
  .filter((pool) => pool.avgCombinedApy7d !== null)
  .sort((a, b) => (b.avgCombinedApy7d || 0) - (a.avgCombinedApy7d || 0));

console.log("Top Aggressive Pools by APY on Arbitrum:");
sortedByApy.slice(0, 5).forEach((pool) => {
  console.log(`\n${pool.poolName} (${pool.protocolName})`);
  console.log(`  APY: ${pool.avgCombinedApy7d?.toFixed(2)}% | Trend: ${pool.apyTrend}`);
  console.log(`  Health: ${pool.healthScore} | Risk: ${pool.riskLevel}`);
  console.log(`  Liquidity: ${pool.liquidityDepth} | Consistency: ${pool.yieldConsistency}`);
});

// Find aggressive pools with rising yields and acceptable risk
const risingOpportunities = arbAggressiveStatus.filter(
  (pool) =>
    pool.apyTrend === "rising" &&
    pool.riskLevel !== "high" &&
    pool.liquidityDepth !== "shallow"
);

console.log(`\nFound ${risingOpportunities.length} rising opportunities with manageable risk`);

// Get all aggressive pool status across chains
const allAggressiveStatus = await sdk.getAggressivePoolStatus();

// Risk distribution analysis
const riskDistribution = {
  low: allAggressiveStatus.filter(p => p.riskLevel === "low").length,
  medium: allAggressiveStatus.filter(p => p.riskLevel === "medium").length,
  high: allAggressiveStatus.filter(p => p.riskLevel === "high").length,
};

console.log("\nRisk Distribution:", riskDistribution);
```

## Notes

* This method internally calls `getActiveAggressiveOppsRisk()` and derives status indicators
* Aggressive pools typically have higher APYs but also higher risk profiles compared to conservative pools
* "Medium" risk and "moderate" health scores are common and may still be acceptable depending on risk tolerance
* Always consider liquidity depth for position sizing - shallow liquidity limits withdrawal capacity
* Volatile yield consistency is expected in aggressive strategies with changing incentive programs
* Compare `apyTrend` across multiple pools to identify the best entry timing
* High utilization (>90%) in aggressive pools may indicate withdrawal delays during market stress