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schoeffeljp

deribit-mcp

by schoeffeljp

get_funding_rate_history

Retrieve historical funding rate data for a perpetual instrument, including hourly rates, index prices, and interest rates, to analyze funding costs over a specified time range.

Instructions

Get historical funding rate data for a perpetual instrument. Shows hourly funding rates, index prices, and interest rates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_timestampYesEnd timestamp in milliseconds since epoch
instrument_nameYesPerpetual instrument name (e.g. 'BTC-PERPETUAL')
start_timestampYesStart timestamp in milliseconds since epoch

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It adds useful behavioral context by disclosing the granularity ('hourly') and the data contents (funding rates, index prices, interest rates), but it omits ordering, time-range limits, and response shape — acceptable margin for a low-risk read tool but not rich disclosure.

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?

Two sentences totaling about 22 words with zero filler. The first sentence front-loads the action and resource; the second adds return-data detail. Every word earns its place.

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?

For a simple read-only tool with a fully documented 3-parameter schema, the description covers the essentials: what it does and what data it returns. Since there is no output schema, the description's naming of returned fields is helpful, though the exact response structure is left unspecified.

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 description coverage is 100%, so all three parameters (instrument_name, start_timestamp, end_timestamp) are already documented in the schema. The description adds no parameter-specific detail beyond what the schema provides, so the baseline score of 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 states a specific verb ('Get') with a precise resource ('historical funding rate data') scoped to 'a perpetual instrument.' The second sentence names the returned content (hourly funding rates, index prices, interest rates), which clearly distinguishes it from siblings like get_historical_volatility and get_delivery_prices.

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?

No explicit when-to-use guidance is provided, and no alternatives or exclusions are named. The usage context must be inferred from the tool name and the data promised, which is adequate but left to the agent's judgment.

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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