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by io.github.seekdaseek
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Funding extremes

get_funding_extremes
Read-onlyIdempotent

Funding rate extremes across every Bybit USDT perp: the most positive and most negative funding with annualized %, 24h price move and open interest. The most crowded trades in the market — crowded shorts are squeeze candidates. Costs 0.02 USDC per call (x402, USDC on Solana or Base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNotop N each side, 1-25, default 10
min_turnover_usdNoliquidity floor, default 1M

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesthe get_funding_extremes payload; a real captured example is free at https://x402.ochinimus.app/api/sample/get_funding_extremes
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_funding_extremes payload; a real captured example is free at https://x402.ochinimus.app/api/sample/get_funding_extremes",
+      "propertyNames": {
+        "type": "string"
+      },
+      "type": "object"
+    },
+    "tool": {
+      "const": "get_funding_extremes",
+      "description": "the tool that produced this payload",
+      "type": "string"
+    }
+  },
+  "required": [
+    "tool",
+    "data"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations by disclosing the 0.02 USDC cost, x402 payment mechanism, and that USDC is accepted on Solana or Base. This is meaningful behavioral information the annotations do not convey.

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?

Three concise sentences, each earning its place: scope and return fields, interpretation/use case, and cost. The most decision-relevant information is front-loaded with no filler or repetition.

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?

Given the tool's simplicity (0 required parameters) and the presence of an output schema, the description covers the essential context: what is returned, what it means, and the cost. It does not explicitly route to sibling tools, but nothing an agent needs to correctly invoke 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%; both 'limit' and 'min_turnover_usd' are already fully described in the schema with defaults and ranges. The description does not add parameter-specific meaning beyond that, so the baseline score of 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?

Description opens with a concrete action and resource: 'Funding rate extremes across every Bybit USDT perp'. It explicitly lists the returned metrics (annualized %, 24h price move, open interest), making the tool's scope and output unmistakable and distinct from generic funding-rate tools.

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?

The description clearly states the intended use case: surfacing the most crowded trades, with 'crowded shorts are squeeze candidates'. This gives an agent strong context for when to use it, though it does not explicitly name sibling alternatives or state when not to use it.

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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