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by io.github.seekdaseek
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Squeeze score

get_squeeze_score
Read-onlyIdempotent

Short squeeze score and long flush score, 0-100, for any USDT perp. Composite of the funding rate, long/short crowding, 24h open-interest build, and liquidation skew from our own tape. One number for whether a trade is crowded and about to hurt someone. Costs 0.1 USDC per call (x402, USDC on Solana or Base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNoUSDT perp symbol e.g. SOLUSDT, BTCUSDT (default SOLUSDT)

Output Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / symbol / description
      Previous value: -"USDT perp symbol e.g. SOLUSDT"New value: +"USDT perp symbol e.g. SOLUSDT, BTCUSDT (default SOLUSDT)"
    • removedInput schema / required
      Removed value: -[
-  "symbol"
-]
  2. 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_squeeze_score payload; a real captured example is free at https://x402.ochinimus.app/api/sample/get_squeeze_score",
+      "propertyNames": {
+        "type": "string"
+      },
+      "type": "object"
+    },
+    "tool": {
+      "const": "get_squeeze_score",
+      "description": "the tool that produced this payload",
+      "type": "string"
+    }
+  },
+  "required": [
+    "tool",
+    "data"
+  ],
+  "type": "object"
+}
  3. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower, yet the description adds meaningful non-obvious context: a paid x402 call at 0.1 USDC on Solana or Base. That cost/auth detail is exactly the kind of behavior annotations cannot convey. It stops short of noting rate limits or what happens on unsupported symbols.

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 tight sentences: what the score is, what it composites, and what it costs. No redundancy, and the core definition is front-loaded before the pricing note.

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?

With an output schema present, return values need not be explained. The description supplies the score range, the composite inputs, the use-case framing, and the payment terms, leaving no material gap for invoking correctly.

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 sole optional symbol parameter is documented in the schema with an example and default. The description adds only 'any USDT perp' as scope, so 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 resource (short squeeze score / long flush score, 0-100) and scope (any USDT perp), and names the exact inputs feeding the composite. An agent can distinguish it from single-metric siblings like get_funding_rate or get_long_short because it declares itself a composite derived from those signals.

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

Usage Guidelines3/5

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

The line 'One number for whether a trade is crowded and about to hurt someone' implies the decision context, but there is no explicit when-to-use vs when-not, and no routing to or away from siblings such as get_positioning despite overlapping signal. Usage is inferable but not spelled out.

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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