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SOL and BTC positioning

get_positioning
Read-onlyIdempotent

SOL+BTC positioning on Hyperliquid: open interest with 1h/24h change and the top 250 accounts' net-long share (whale crowding). Costs 0.005 USDC per call (x402, USDC on Solana, Base, Polygon, Arbitrum or Arc).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesthe get_positioning payload; a real captured example is free at https://x402.ochinimus.app/api/sample/get_positioning
toolYesthe tool that produced this payload

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "data": {
+      "additionalProperties": {},
+      "description": "the get_positioning payload; a real captured example is free at https://x402.ochinimus.app/api/sample/get_positioning",
+      "propertyNames": {
+        "type": "string"
+      },
+      "type": "object"
+    },
+    "tool": {
+      "const": "get_positioning",
+      "description": "the tool that produced this payload",
+      "type": "string"
+    }
+  },
+  "required": [
+    "tool",
+    "data"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful non-annotation context: the 0.005 USDC per-call cost and the x402 payment rails (USDC on Solana, Base, Polygon, Arbitrum, Arc), which is important for an agent deciding whether to spend on a call.

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?

A single tight sentence that front-loads the returned data and ends with cost/payment. Every clause earns its place, with no filler.

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?

With a zero-param schema and an output schema present, the description need not explain return values. It covers what the tool computes and its cost/payment requirements, leaving only cross-tool routing to the reader.

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?

The tool takes no parameters, so there is nothing for the description to disambiguate; the zero-param baseline of 4 applies.

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?

States a specific resource and scope: SOL+BTC positioning on Hyperliquid, broken down into open interest with 1h/24h change and the top 250 accounts' net-long share. An agent knows exactly what data it returns. It does not, however, distinguish itself from closely overlapping siblings like get_open_interest or get_hl_whales, so it stops short of a 5.

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

Usage Guidelines2/5

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

The description never says when to reach for this tool versus the many sibling tools that surface open interest or Hyperliquid whale data. It states what the tool produces but provides no usage context or exclusions.

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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