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hyperliquid-agent-gateway

hyperliquid-agent-gateway

by alekskram
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Funding History

funding_history
Read-only

Fetch hourly funding history for any coin, including the current premium, with funding rate, premium, and timestamp per record. Specify coin and an optional limit up to 500 for newest-first results.

Instructions

Hourly funding history for coin (fundingHistory) plus the CURRENT premium from metaAndAssetCtxs (premium_now): rows carry fundingRate (hourly), premium, time (ms). Newest-first, capped at limit (max 500). Example: funding_history(coin="BTC", limit=48)

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": "funding_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
coinYes
limitNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already mark it as read-only, open-world, and non-destructive. The description adds valuable behavioral details beyond the annotations: results are newest-first, capped at `limit` with a maximum of 500, and the premium is a current snapshot rather than part of the historical series. 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.

Conciseness5/5

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

The description packs all essential information into one dense sentence plus an example: data source, output fields, ordering, cap, and a usage illustration. No filler or redundant phrasing; every clause earns its place.

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 tool with only two parameters and an output schema, the description covers the key aspects: what data is returned, field names and units, ordering, and limit behavior. The annotations handle safety and world assumptions. Nothing critical is missing for an agent to call it correctly.

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 description coverage is 0%, so the description must compensate. It names `coin` and `limit`, clarifies that `limit` caps results and has a max of 500, and gives a concrete example (funding_history(coin="BTC", limit=48)). It could add that `limit` defaults to 100, but the example and cap clarification provide solid guidance.

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 states exactly what the tool returns: hourly funding history for a coin plus the current premium, with specific row fields (fundingRate, premium, time in ms). It clearly distinguishes this from general market tools by naming the internal data sources (fundingHistory, metaAndAssetCtxs) and ordering behavior.

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

Usage Guidelines4/5

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

The description provides clear context for when to use it: when you need hourly funding data and the current premium for a coin. It does not explicitly name alternatives or exclusions relative to siblings like funding_carry_screener, but the purpose is specific enough that an agent can infer the appropriate use case.

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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