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Liquidation map

liquidation_map
Read-onlyIdempotent

Where the forced orders sit around the current price for one market, from every wallet on the node: liquidation prices (longs below = forced sells, shorts above = forced buys), resting stop-loss / take-profit trigger orders, and order-book depth, summed into price bands either side of the mark price, plus the biggest liquidation clusters.

This is the "liquidation heatmap" question: where would a move run into cascading liquidations, and how much is there. Uses 2 API calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinYesHyperliquid market symbol, e.g. BTC, ETH, HYPE, xyz:SKHX
bandsNoPrice bands per side
range_pctNoHow far either side of price to map, in %

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful context beyond that: the scope ("every wallet on the node") and the cost signal ("Uses 2 API calls"). It does not mention pagination or rate limits, but for a read-only analytical tool this is solid added value.

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?

Front-loaded with the core answer and the parenthetical ("longs below = forced sells, shorts above = forced buys") genuinely aids interpretation rather than padding. It runs slightly long and the "2 API calls" note could sit earlier, but every clause carries meaning.

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?

With no output schema, the description must convey what comes back, and it does: liquidation prices, resting trigger orders, banded order-book depth, and biggest clusters. Combined with the annotations and complete parameter schema, an agent has everything needed to invoke and interpret the result correctly.

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 coin, bands, and range_pct are already fully documented with types, defaults, and bounds. The description explains the output shape (bands either side of the mark price) but adds no syntax or format detail beyond the schema, so baseline 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?

States a specific analytical concept (forced orders / liquidation heatmap for one market) with concrete content: liquidation prices, SL/TP triggers, order-book depth in price bands, and top clusters. An agent can immediately tell this produces a spatial liquidation map, not a history or a total, so it is distinguishable from siblings like recent_liquidations and liquidation_totals without opening any schema.

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?

Frames the exact question it answers ("where would a move run into cascading liquidations, and how much is there"), which gives clear context for when to reach for it. It does not explicitly name or exclude the alternative sibling tools (cascades, liquidation_totals, recent_liquidations), so it stops short of explicit routing.

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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