Hyperliquid Market Scout

The problem

Manually tracking Hyperliquid market data across REST and WebSocket endpoints is tedious and error-prone. Developers often struggle with mapping universe names to asset contexts and calculating real-time spreads or funding deviations.

What it does

• Fetches real-time mid prices for all coins on the Hyperliquid exchange.
• Retrieves L2 order book depth and validates bid-ask spreads.
• Monitors funding rates, oracle prices, and open interest across the universe.
• Inspects account-specific data including margin summaries, open positions, and fill history.
• Aggregates raw JSON into formatted tables highlighting market anomalies.

Frameworks & tools

Hyperliquid API, REST (POST), WebSockets, jq.

Why this beats prompting it yourself

This skill handles the specific structure of Hyperliquid's info endpoint, which requires POST requests for all data types. It automates the complex mapping of asset universes to market contexts, saving you from writing manual join logic in jq or Python.

Use cases

• Review recent trade fills and realized PnL for a specific wallet address.
• Monitor funding rate outliers to identify arbitrage opportunities.
• Audit order book liquidity and spreads for specific pairs before executing.
• Stream live mid-price updates via WebSocket for real-time monitoring.

Known limitations

Does not support order placement or automated execution. OHLCV candle history is not included as it requires a separate endpoint.