ScorpTech x402 API

Morse Timing

morse_timing

Read-onlyIdempotent

How long a Morse message takes at a given speed. The dit is 1200/wpm milliseconds. PARIS is 43 units, or 50 units once the trailing 7-unit word gap of a stream is added. SOS is 27 units. Price: $0.001 USDC per successful call (x402, Solana). Same tool over HTTPS: GET https://scorptech.it.com/api/x402/v1/morse-timing

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": {
      "text": "<text>"
    },
    "name": "morse_timing"
  }
}

Input Schema

Name	Required	Description	Default
`wpm`	No
`text`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 23, 2026

TDQS

B3.2/5.0

Behavior4/5

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

Annotations already cover readOnly, idempotent, openWorld, and non-destructive behaviors. The description adds valuable behavioral context: it discloses a cost of $0.001 USDC per successful call under the x402 protocol on Solana, and provides an alternative HTTPS endpoint. This goes beyond structured fields and is useful for an agent deciding whether to invoke the tool.

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 purpose is front-loaded in the first sentence. The following sentences provide relevant technical facts (dit duration, PARIS, SOS units) and practical payment/endpoint details. While slightly rambling, all information is relevant and the description is not excessively long.

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?

For a simple two-parameter read-only tool with no output schema, the description covers what the tool does and adds pricing/endpoint context. However, it omits parameter explanations and does not describe the return value (e.g., duration in milliseconds), which is important since there is no output schema. These gaps leave the agent without full clarity on invocation details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain the parameters, but it does not. It mentions 'at a given speed' which hints at the wpm parameter, but never defines wpm, its units, default, range, or what the text parameter represents. No parameter semantics are added beyond the schema's type information.

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 clearly states it computes the duration of a Morse message at a given speed, which is a specific and distinct purpose. It does not explicitly differentiate from siblings like morse_encode or morse_decode, but the verb+resource is clear enough for an agent to distinguish them by intent.

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?

There is no explicit guidance on when to use this tool versus alternatives, nor any context about when not to use it. The description only states what it does and some facts, leaving the agent to infer appropriate usage scenarios.

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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