hive-market-research

hive-market-research — Market Research

Answer live price, liquidity, exchange, OHLC, order-book, derivatives, and trading-context questions with sourced, timestamped market data.

Task toolset and identifiers

Toolset: market_research. Read hive://toolsets/market_research before execution; it is authoritative for the current output schema, material-call budget, phases, fallback condition, and stop conditions.

For tokenized real-world-asset perps (stock/pre-IPO/ETF/index/commodity/FX perps — funding, rollover carry, cross-venue markets), route to rwa_perp_analysis instead and read hive://toolsets/rwa_perp_analysis; its rows carry funding_mechanism (a funding_plus_borrow rollover is never sign-comparable with a funding transfer), is_delisted, and is_price_suspect fields that must be respected in the answer.

• Required: asset (token id, symbol, or contract address) and quote currency (usually usd).
• Venue/exchange id when the request is order-book, ticker, or derivatives specific.
• Time window and candle interval for OHLC or trend questions.

Ask for missing venue or chain details when the choice changes the answer. For general price questions, choose a broad market-data tool and state the source.

Before choosing endpoints, select exactly one matching entry from the exact workflow's routes[]. Follow its ordered steps, use a fallback only under that step's published condition, stop at four material calls, and preserve the selected route_id in the typed result. The broad coverageCatalog is discovery coverage, not an execution plan.

Procedure

1. Resolve ambiguous symbols first — call search_tools with the asset and intent.
2. Call get_api_endpoint_schema for each market endpoint before calling it.
3. Prefer focused calls: price, ticker, OHLC, order book, or funding data — not everything at once.
4. For derivatives questions, include funding/open-interest context when available.
5. For Hyperliquid perp questions, filter discovery to Hyperliquid, inspect the typed endpoint schema, and bound time-series calls by time range and pagination limits. Continue from the returned timestamp when a funding scan reports an incomplete range.
6. Return freshness with every number, and avoid trading conclusions without liquidity context.