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Ironflow: Hyperliquid data

Candles (OHLCV)

get_candles
Read-only

OHLCV candles for one Hyperliquid market, built from every trade: open, high, low, close, volume and trade count per candle, oldest first. Returns the latest 24 candles by default (up to 500), at 1m to 1d intervals. Use it for price history, ranges and charts. For only the current price use get_price; for individual trades use get_recent_trades.

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of candles to return (1-500, default 24)
marketYesMarket: BTC-PERP, xyz:NVDA-PERP, HYPE/USDC, or a Hyperliquid name (BTC, @107, xyz:NVDA)
intervalNoCandle interval (1m, 5m, 15m, 1h, 4h, 1d). Default: 1h

Output Schema

NameRequiredDescriptionDefault
dataNoOHLCV candles
noticeNoPresent when the API added a note: how a market name was read, that data starts later than asked because of the history window, or a next step such as a free key
paginationNoCursor pagination

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered; the description still adds real behavior beyond that — candles are built from every trade (completeness guarantee), results are ordered oldest first, and the default fetch is the latest 24 with a 500 cap. It does not mention pagination or gaps for illiquid intervals, but with an output schema present the return shape needn't be spelled out.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences with no filler: the payload contents come first, then the default/size behavior, then usage plus sibling disambiguation. Every clause carries information an agent would otherwise have to infer.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-market read tool with only three fully documented parameters, an output schema and read-only annotations, nothing essential is missing. The description covers what the data is derived from, ordering, sizing defaults and the alternative tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and each parameter already carries its own description including the 1-500 range, the 24 default and the interval enum. The description restates the default window and interval span but adds no new syntax or constraint beyond the schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource and verb shape: OHLCV candles for one Hyperliquid market, built from every trade, with the exact fields (open, high, low, close, volume, trade count). It also names the scope limit (one market) so an agent can immediately distinguish it from portfolio- or wallet-level siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives positive usage guidance ("use it for price history, ranges and charts") and explicitly routes two adjacent needs to named siblings: get_price for the current price and get_recent_trades for individual trades. Both the when and the when-not are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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