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Hyperliquid Liquidation Risk Index

Hyperliquid liquidation risk index

get_liquidation_risk

Real-time Hyperliquid BTC/ETH perpetual futures liquidation risk index: notional at risk if leveraged price moves ±1%/3%/5%, position closest to liquidation, funding rate. Built from real on-chain position data. Free via MCP; the same data is also available pay-per-call at https://hlrisk.paidapis.net/api/hl-liquidation-risk 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
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It states the tool is free via MCP and discloses the data source (real on-chain data), which is useful. However, it does not describe potential side effects (though this is likely read-only) or any rate limits, and it mixes a promotional link to a paid API which may distract from the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is a single sentence with no wasted words on purpose, but it appends a promotional URL and a note about a paid API that is not essential for tool invocation. This could be considered extra content that might distract the agent. It is front-loaded with the core purpose, but the marketing text takes away from clarity.

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?

The tool is a simple read-only data query with no parameters and no output schema, so the description's explanation of what the index includes is sufficient for an agent to invoke it correctly. The absence of an output schema is not a gap given the description provides the key data points. The mention of the paid API is extra but does not leave the agent needing more.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters accepted and zero required, so the description does not need to document parameters. The schema coverage is 100%, but an empty schema means the description's role in parameter semantics is nil. Given the absence of parameters, a score of 5 is appropriate because there is nothing else needed.

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 the tool computes a real-time liquidation risk index for Hyperliquid BTC/ETH perpetual futures. It lists the specific data points (notional at risk, closest position, funding rate) and notes it uses real on-chain data. It is clear enough to distinguish from its sibling, get_recent_liquidations, which focuses on past liquidation events, though it does not explicitly name the sibling.

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 implies the tool is for checking current liquidity risk, and mentions the data source and paid alternative but does not explicitly state when to use this tool over the sibling or any prerequisites.

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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