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Carry: spot × perp

carry_spot_perp
Read-onlyIdempotent

Hyperliquid main-dex perps that also have a Hyperliquid spot market (e.g. HYPE, PURR, BTC via UBTC). Returns items[] with base, perp, funding_apr (annualised, now), funding_apr_14d (14-day mean), hours_positive_14d (share of hours with positive funding, 0–1), perp_mark, spot_mark, spot_pair, basis_pct (perp vs spot, %), perp_vol24_usd, spot_vol24_usd, oi_usd, sorted by 14-day funding. Data, not a signal. Requires a Carry key (X-API-KEY), the free trial key, or x402 per call. Use for main-dex perp vs its spot market; for cross-dex HIP-3 pairs use carry_xdex.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows, default 50
min_volNoMinimum perp 24h volume in USD, default 100000

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / limit / description
      Added value: +"Max rows, default 50"
    • addedInput schema / properties / min_vol / description
      Added value: +"Minimum perp 24h volume in USD, default 100000"
  2. Added

TDQS

A4.4/5.0
Behavior4/5

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

Adds substantial context beyond the annotations: auth requirements (Carry key via X-API-KEY, free trial key, or x402 per-call payment), the sort order ('sorted by 14-day funding'), and a full enumeration of returned fields. With no output schema, this field disclosure is genuinely load-bearing. Rate limits or pagination behavior are not mentioned, keeping it short of a 5.

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-loads the scope, then returns, then auth, then routing. The long field enumeration is verbose but justified because no output schema exists to document the response. Slightly dense but nothing wasted.

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?

Given two optional params fully documented by the schema and no output schema, the description compensates by listing the return fields, noting the sort order, stating access/auth modes, and naming the sibling alternative. An agent has everything needed to select and invoke it.

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% for both parameters, including their defaults (limit=50, min_vol=100000), so the schema carries the parameter documentation. The description adds no parameter-level detail, 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 precise verb/resource scope: 'Hyperliquid main-dex perps that also have a Hyperliquid spot market,' with concrete examples (HYPE, PURR, BTC via UBTC). It immediately distinguishes itself from the sibling carry_xdex, which covers cross-dex HIP-3 pairs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes the agent: 'Use for main-dex perp vs its spot market; for cross-dex HIP-3 pairs use carry_xdex.' It also sets expectations with 'Data, not a signal,' telling the agent this returns raw data rather than a trade recommendation.

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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