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Hyperliquid Liquidation Risk Index

Hyperliquid backstop liquidations

get_recent_liquidations

Hyperliquid BTC/ETH perpetual futures backstop liquidations in the last hour: total USD, count, biggest single event. Free via MCP; the same data is also available pay-per-call at https://hlrisk.paidapis.net/api/hl-liquidations for production use.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the data source and time window but does not state whether authentication is required, whether data is live or cached, any rate limits, or explicitly confirm it is a read-only operation (though the name implies it).

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 single sentence that is dense with relevant information (market, time window, metrics) and front-loads the core data. It includes a promotional URL and pricing note that are not strictly necessary for tool invocation, but the overall length is acceptable.

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 zero-parameter read tool, the description explains what data is returned and its scope. It lacks details on output format or edge cases (e.g., empty results), but given the tool's simplicity, it is mostly complete. The absence of an output schema is compensated by listing the three metrics explicitly.

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 tool takes zero parameters; the schema is an empty object with 100% coverage trivially. Since there are no parameters to document, the description correctly omits parameter details. Per rubric, zero parameters earns a baseline of 4.

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 precisely states the resource (Hyperliquid BTC/ETH perpetual futures backstop liquidations), the time window (last hour), and the exact metrics returned (total USD, count, biggest single event). It is specific and clearly differentiates from a generic liquidation risk tool, even though it does not name the sibling explicitly.

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 description explicitly contrasts the free MCP access with a paid production API, providing some guidance on when to use which. However, it does not mention the sibling tool 'get_liquidation_risk' or provide conditions for choosing between them, leaving usage guidance incomplete.

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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