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Alchemy performance tuning

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/saas-packs/alchemy-pack/skills/alchemy-performance-tuning

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Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill alchemy-performance-tuning

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What its author says it does

Copied from the file, not written here

'Optimize Alchemy SDK performance with caching, batching, and multi-chain parallelism.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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Alchemy Performance Tuning

Performance Targets

OperationTarget LatencyCU Cost
getBlockNumber< 50ms10
getBalance< 100ms19
getTokenBalances< 200ms50
getNftsForOwner< 300ms50
getAssetTransfers< 500ms150
Multi-chain portfolio< 2s~400

Instructions

Step 1: Response Caching with TTL

// src/performance/cache.ts
import { Alchemy, Network } from 'alchemy-sdk';

class BlockchainCache {
  private store = new Map<string, { data: any; expiry: number }>();

  // Different TTLs for different data freshness needs
  private TTL: Record<string, number> = {
    blockNumber: 12000,     // 12s (~1 block)
    balance: 30000,         // 30s
    tokenBalances: 60000,   // 60s
    nftOwnership: 300000,   // 5 min (NFTs transfer less frequently)
    contractMetadata: 3600000, // 1 hour (rarely changes)
    tokenMetadata: 86400000,   // 24 hours (almost never changes)
  };

  async cached<T>(category: string, key: string, fetcher: () => Promise<T>): Promise<T> {
    const cacheKey = `${category}:${key}`;
    const entry = this.store.get(cacheKey);
    if (entry && entry.expiry > Date.now()) return entry.data;

    const data = await fetcher();
    this.store.set(cacheKey, { data, expiry: Date.now() + (this.TTL[category] || 30000) });
    return data;
  }

  invalidate(category: string): void {
    for (const key of this.store.keys()) {
      if (key.startsWith(`${category}:`)) this.store.delete(key);
    }
  }
}

const cache = new BlockchainCache();
export { cache };

Step 2: Parallel Multi-Chain Fetching

// src/performance/parallel-fetch.ts
import { Alchemy, Network } from 'alchemy-sdk';
import { cache } from './cache';

const CHAINS = [
  { name: 'ethereum', network: Network.ETH_MAINNET },
  { name: 'polygon', network: Network.MATIC_MAINNET },
  { name: 'arbitrum', network: Network.ARB_MAINNET },
  { name: 'base', network: Network.BASE_MAINNET },
];

async function multiChainBalance(address: string) {
  const results = await Promise.allSettled(
    CHAINS.map(chain =>
      cache.cached('balance', `${chain.name}:${address}`, async () => {
        const client = new Alchemy({ apiKey: process.env.ALCHEMY_API_KEY, network: chain.network });
        const bal = await client.core.getBalance(address);
        return { chain: chain.name, balance: (parseInt(bal.toString()) / 1e18).toFixed(6) };
      })
    )
  );

  return results
    .filter((r): r is PromiseFulfilledResult<any> => r.status === 'fulfilled')
    .map(r => r.value);
}

Step 3: Batch NFT Metadata (Reduce CU)

// src/performance/batch-nft.ts
import { Alchemy, Network } from 'alchemy-sdk';

const alchemy = new Alchemy({ apiKey: process.env.ALCHEMY_API_KEY, network: Network.ETH_MAINNET });

// SLOW: Individual calls = 50 CU each
// async function slowGetMetadata(tokens) {
//   return Promise.all(tokens.map(t => alchemy.nft.getNftMetadata(t.contract, t.tokenId)));
// }

// FAST: Batch call = 50 CU total for up to 100 tokens
async function fastGetMetadata(tokens: Array<{ contractAddress: string; tokenId: string }>) {
  return alchemy.nft.getNftMetadataBatch(tokens);
}

Step 4: WebSocket for Real-Time Data

// src/performance/realtime.ts
import { Alchemy, AlchemySubscription, Network } from 'alchemy-sdk';

const alchemy = new Alchemy({ apiKey: process.env.ALCHEMY_API_KEY, network: Network.ETH_MAINNET });

// Use WebSocket subscriptions instead of polling
function watchAddress(address: string, onActivity: (tx: any) => void) {
  alchemy.ws.on(
    {
      method: AlchemySubscription.PENDING_TRANSACTIONS,
      toAddress: address,
    },
    (tx) => onActivity(tx)
  );
}

// Auto-reconnect on disconnect
alchemy.ws.on('close', () => {
  console.log('WebSocket disconnected — reconnecting in 5s');
  setTimeout(() => alchemy.ws.connect(), 5000);
});

Output

  • TTL-based response cache matching data freshness requirements
  • Parallel multi-chain fetching (4 chains in < 2s)
  • Batch NFT metadata (100x CU reduction)
  • WebSocket subscriptions replacing polling

Resources

Next Steps

For cost optimization, see alchemy-cost-tuning.

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