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ScorpTech x402 Tools

Heron Area

heron_area
Read-onlyIdempotent

Exact area data for a strict integer triangle. sixteen is 16 times the squared area. When sixteen is a perfect square, area is the reduced value of its square root over 4. A degenerate triple is rejected. Price: $0.001 USDC per successful call (x402, Solana). Same tool over HTTPS: POST https://scorptech.it.com/api/x402/v1/heron-area

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": {
      "a": "<a>",
      "b": "<b>",
      "c": "<c>"
    },
    "name": "heron_area"
  }
}

Input Schema

NameRequiredDescriptionDefault
aYes
bYes
cYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the description is free to add genuinely new context: a degenerate triple is rejected (error behavior), each successful call costs $0.001 USDC via x402 on Solana, and an equivalent HTTPS endpoint is offered. The payment requirement is critical pre-call knowledge rarely surfaced elsewhere; only the exact output shape is left implicit.

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?

The computation semantics are front-loaded in the first sentence, followed by error behavior, pricing, and an alternate transport. Dense but nearly every clause carries information; the 'sixteen is 16 times the squared area' phrasing is slightly awkward but functional.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of describing returns, and it only partially does: it defines the 'sixteen' field and the square-root-over-4 area rule, but leaves the actual response shape (numeric type, fraction versus decimal representation, extra fields) unclear for a tool with three required parameters.

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 0%, so the description must carry parameter meaning. It conveys that a, b, c are the sides of a strict integer triangle (implying integer type and the triangle inequality, with degenerate triples rejected), but never mentions the 1..1,000,000 bounds present in the schema, so compensation is partial.

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?

The description states a concrete operation: exact area data for a strict integer triangle with sides a, b, c, and explains the 'sixteen' quantity it reports. It is clear what the tool computes, though it never uses 'Heron's formula' nor distinguishes itself from nearby siblings like triangle_shape, cosine_law, or pythag_check.

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?

It gives no explicit when-to-use or when-not guidance relative to the many geometry siblings in this catalog. The only usage-shaped information is the implicit constraint that the input must be a non-degenerate integer triple, leaving the agent to infer selection criteria.

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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