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hyperliquid-agent-gateway

hyperliquid-agent-gateway

by alekskram
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Order Book

order_book
Read-only

Retrieves aggregated bid and ask liquidity for a specified coin, with configurable depth levels and total liquidity per side.

Instructions

Aggregated order book for one coin from l2Book: depth levels per side (default 10, max 100), aggregated by the book's nSigFigs precision (default taken from the response levels), with total liquidity (sum px*sz) per side. Example: order_book(coin="ETH", depth=20)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "coin": "<coin>"
    },
    "name": "order_book"
  }
}

Input Schema

NameRequiredDescriptionDefault
coinYes
depthNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already indicate read-only and non-destructive behavior. The description adds meaningful behavioral detail beyond those annotations: depth levels per side with default and max, nSigFigs-based aggregation, and per-side total liquidity sum (px*sz). It does not mention pagination or rate limits, but these are not required given the safety annotations and output schema. No contradiction with annotations.

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

Conciseness4/5

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

The description is compact and front-loaded with the core resource before adding precision and liquidity details. The nSigFigs terminology is somewhat technical but not wasted. The example at the end earns its place by showing a realistic invocation.

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

Completeness4/5

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

With an output schema present and safety annotations covering side effects, the description sufficiently covers the essential call semantics: required coin, optional depth with default and max, and aggregation behavior. It does not specify coin formats or error behavior, but the example and defaults make the tool adequately callable.

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

Parameters4/5

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

Schema coverage is 0%, so the description must compensate. It explains 'depth' clearly (levels per side, default 10, max 100) and illustrates 'coin' with an ETH example. The coin parameter itself is only described as 'one coin', which is thin, but the example largely removes ambiguity.

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

Purpose4/5

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

The description identifies a specific resource (l2Book order book for a single coin) and states what is delivered: depth levels per side, aggregation precision, and total liquidity per side. It is clear and distinct from the other market-data siblings, though it does not explicitly name or contrast them.

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

Usage Guidelines3/5

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

Usage context is implied: if you need an aggregated order book for one coin, this is the tool. The example call gives concrete invocation guidance, but the description does not explicitly say when to use this tool versus alternatives like market_overview, quote, or trades, nor does it state exclusions.

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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