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Tape — Hyperliquid Analytics

Hyperliquid Markets Radar

tape_markets_radar
Read-onlyIdempotent

Rank live Hyperliquid perpetual markets by funding rate, funding APR, open interest, 24h volume or 24h change. Covers every listed perp including HIP-3 builder markets. Default: the 25 markets with the most extreme funding APR, concise fields. Ask for limit, sort, coins or DETAILED only when you need them — the full set is ~13k tokens. Result carries provenance (upstream endpoint, request, fetch time).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dirNoDirection; `asc` on fundingAprPct surfaces the most negative funding first.
sortNoRanking key. Funding, premium and change sort by magnitude by default.
coinsNoRestrict to symbols, e.g. ["BTC","ETH"]. No -PERP suffix.
limitNoRows to return (default 25).
response_formatNoCONCISE (default): coin, mark, fundingAprPct, oi, vol. DETAILED: every field.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful behavior beyond that: default 25 most extreme funding APR rows, concise fields, ~13k token scale warning, and provenance metadata in the result. It does not discuss freshness or failure modes, but for this read-only radar tool the extra context is solid.

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?

Four tight sentences with no fluff. The main action and default behavior lead, and the scale/provenance warnings follow naturally. Every sentence contributes useful operational information.

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 description covers purpose, defaults, scope, caveats, and result provenance, which is enough for an agent to call it correctly without an output schema. It could add a bit more about row semantics for non-default sorts, but the schema already enumerates the sort keys and response formats.

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?

Schema coverage is 100%, so the baseline is 3. The description adds extra decision-supporting meaning: the default is 25 concise rows, asking for optional params should be deliberate because of the ~13k token scale, and DETAILED maps to a heavier result. This goes beyond simply restating schema fields.

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 action and resource: 'Rank live Hyperliquid perpetual markets' by multiple explicit metrics. It also clarifies coverage ('every listed perp including HIP-3 builder markets'), which distinguishes it from sibling tools focused on analytics, alerts, or wallet data.

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?

It gives clear situational context: use it when a ranked market view is needed scan. It also explains the default behavior and cautions when to ask for optional parameters ('Ask for limit, sort, coins or DETAILED only when you need them'). It does not explicitly name alternatives or list when-not conditions, slightly limiting the score.

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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