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Glama
Hydromancer MCP

Hydromancer MCP

by joshavenue

Funding rate history for a market

hydromancer_funding_history
Read-only

Retrieves hourly funding rates for a Hyperliquid market over time, including average and annualized rates, to assess whether longs pay shorts and evaluate holding costs. Defaults to the last 7 days.

Instructions

Hourly funding rates for a market over time, with the average and annualized rate. Positive funding means longs pay shorts. Default window: last 7 days.

Input Schema

NameRequiredDescriptionDefault
coinYesMarket name, any case: "BTC", "eth", "HYPE", "kPEPE", or a HIP-3 market such as "xyz:TSLA".
sinceNoDefault "7d".
untilNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover read-only and open-world safety, so the description's job is added context — and it delivers: fixed hourly granularity, the meaning of the sign, and the returned aggregates (average, annualized). It stops short of mentioning result limits, pagination, or maximum window length.

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 compact sentences with the core purpose front-loaded, followed by the sign convention and the default window. No filler or repetition.

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 no output schema, the description does a reasonable job naming the returned aggregates, and it covers granularity and the default range. Gaps remain around the `until` parameter and any cap on window size, which an agent would need before calling with arbitrary ranges.

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 67%: coin is fully documented in the schema and the description adds nothing to it, while `since` gets only a restated default ('7d') shared by both sources and `until` is undocumented in both. The description does not clarify the accepted string/number forms for the time parameters.

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 states a specific resource and metric: hourly funding rates for a market, plus the average and annualized rate. It implicitly separates itself from the wallet-scoped sibling hydromancer_wallet_funding by specifying 'for a market,' though it never names that sibling, so the distinction requires the agent to infer it.

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?

It provides the interpretation rule ('positive funding means longs pay shorts') and the default window, which orients usage. But it never says when to pick this over hydromancer_wallet_funding or hydromancer_price_history, and gives no exclusions or prerequisites.

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