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hyperliquid-agent-gateway

hyperliquid-agent-gateway

by alekskram
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Spot Overview

spot_overview
Read-only

Get a spot market overview of top pairs sorted by daily volume, with HIP-1/ERC-20 token names resolved.

Instructions

Spot market overview (~326 pairs) from spotMeta + spotMetaAndAssetCtxs: pair rows (name, mark, day volume, OI where published) with HIP-1 <-> ERC-20 links resolved - '@{index}' spot coin names are mapped to token names via spotMeta.tokens. Sorted by day volume descending, capped at limit (max 100). Example: spot_overview(limit=10)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "spot_overview"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo

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?

The description discloses the data sources (spotMeta + spotMetaAndAssetCtxs), the token-name mapping, sorting by day volume descending, and the limit cap with a max of 100. This adds meaningful behavioral context beyond the readOnlyHint/openWorldHint annotations, though it does not mention edge-case behavior such as what happens when limit exceeds the maximum.

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 a compact, front-loaded sentence that covers purpose, data sources, content, sorting, and cap, followed by a simple example. It contains no fluff, though the long opening sentence packs several ideas together and could be split for even easier reading.

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?

Given the presence of an output schema and safety annotations, the description covers the essential behavioral context: what data is included, how names are resolved, ordering, and limit semantics. Minor details like full field definitions or invalid-limit handling are omitted but are unlikely to prevent correct invocation.

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?

The input schema provides only a type and default for limit with no description, so the description compensates by explaining that limit caps the result count and has a maximum of 100, plus a concrete example. This is sufficient for the single parameter.

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 clearly states that the tool returns a spot market overview of ~326 pairs and enumerates the fields (name, mark, day volume, OI) and the HIP-1 to ERC-20 link resolution. This identifies the resource and content well, though it does not explicitly contrast it with sibling market_overview or use a direct verb, so it stops short of a 5.

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?

The example call spot_overview(limit=10) demonstrates usage, and the tool's purpose is inferable from the name and description. However, there is no explicit guidance about when to choose this tool over alternatives like market_overview, nor any exclusions, so the usage context is only implied.

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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