Build an algo-dsl StudioV1 algorithm for Embed.

Use only the current Console algo dropdown indices:
polymarket-trades, polymarket-items, hyperliquid-trades, base-trades,
ethereum-trades, solana-trades, token-items, hyperliquid-items,
hyperliquid-notifications, dex-notifications, polymarket-notifications,
kalshi-notifications, wallet-users, hyperliquid-wallets, polymarket-wallets.

The algorithm should:
- search one index,
- hydrate rows with .include(),
- filter and sort inside the search query,
- return the hydrated rows.

Do not add separate feature, scoring, or ranking stages.

import { StudioV1 } from "algo-dsl";

export default async function algo({ apiKey }) {
  const mbd = new StudioV1({ apiKey });

  return mbd
    .search()
    .index("token-items")
    .include()
    .numeric("zora_market_cap", 10000)
    .notNull("name")
    .sortBy("zora_market_cap_delta_24h", "desc")
    .size(30)
    .execute();
}

import { StudioV1 } from "algo-dsl";

export default async function notificationAlgo({ apiKey }) {
  const mbd = new StudioV1({ apiKey });

  return mbd
    .search()
    .index("polymarket-notifications")
    .include()
    .inAppUsers("wallet_address")
    .notNull("user_id")
    .sortBy("timestamp", "desc")
    .size(50)
    .execute();
}