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Everything on one Hyperliquid perp

perp_full
Read-only

One call, one payment for everything on a Hyperliquid perpetual: crowd state with base rates for what usually followed (as /v1/crowd/perp), smart-money positioning (as /v1/smart/perp) and liquidation levels with order-book depth (as /v1/liq/perp), each with its own as_of. Cheaper than buying the three separately. Signed. Not investment advice. Price: $0.03 USDC per call via x402 (Base or Solana).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "coin": "<coin>"
    },
    "name": "perp_full"
  }
}

Input Schema

NameRequiredDescriptionDefault
coinYesHyperliquid perp symbol, for example BTC, ETH, SOL, HYPE, kPEPE (case-sensitive)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds material context beyond that: the response is 'Signed,' it is 'Not investment advice,' each sub-block carries its own 'as_of' timestamp, and it costs $0.03 USDC via x402 on Base or Solana — all non-obvious behavioral facts an agent needs.

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 core value proposition ('One call, one payment for everything') and then packs the component list, pricing, and signing note into a tight paragraph. It is dense to the point of being run-on, but every clause carries information, so no waste.

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 tool that fans out to three data sets with no output schema, the description adequately explains what comes back (crowd state with base rates, smart-money positioning, liquidation levels with order-book depth, per-block as_of) plus payment and signing mechanics. It could say more about the combined response shape, but nothing essential to invoking it is missing.

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%, and the single 'coin' parameter is fully documented in the schema (symbol examples, case-sensitivity). The description adds no additional parameter meaning, so the baseline 3 is appropriate.

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 action (one call aggregating everything) on a specific resource (a Hyperliquid perpetual) and explicitly enumerates the three bundled payloads, mapping each to the sibling endpoint it mirrors (/v1/crowd/perp, /v1/smart/perp, /v1/liq/perp). An agent can immediately distinguish this from the standalone crowd_perp, smart_perp and liq_perp siblings.

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?

Gives clear context for choosing this tool: 'One call, one payment for everything' and 'Cheaper than buying the three separately,' which routes the agent here when it needs all three data sets at once. It stops short of an explicit exclusion (e.g. 'if you only need one, call that specific tool instead'), so it earns a 4 rather than a 5.

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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