ScorpTech x402 API

Primorial Prime

primorial_prime

Read-onlyIdempotent

Whether n# + 1 and n# - 1 are prime, where n# is the product of the primes up to n. 5# is 30, and both neighbors are prime. 7# is 210, and only 211 is prime. n runs from 2 to 30. Price: $0.001 USDC per successful call (x402, Solana). Same tool over HTTPS: POST https://scorptech.it.com/api/x402/v1/primorial-prime

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": {
      "n": "<n>"
    },
    "name": "primorial_prime"
  }
}

Input Schema

Name	Required	Description	Default
`n`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 23, 2026

TDQS

A3.9/5.0

Behavior4/5

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

The annotations already declare read-only, idempotent, non-destructive, and open-world behavior, so the description does not need to cover those traits. It adds useful non-schema context: the $0.001 USDC price per successful x402/Solana call, the HTTPS endpoint, and the valid n range. It does not explain return shape or failure behavior, but with annotations present this is meaningful added context.

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?

The core operation and examples are front-loaded, and every sentence contributes useful information. The pricing and endpoint sentence is extra but practical for invocation. The description is appropriately sized with no obvious 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?

For a one-parameter math predicate with no output schema, the description supplies the operation, domain, examples, and access/payment details. It leaves the exact return value format implicit, but the examples make the intended result clear enough for an agent to invoke the tool correctly.

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?

Schema description coverage is 0% for the single parameter, so the description must carry the semantic load. It does so by defining n# as the product of primes up to n, giving concrete examples such as 5# = 30 and 7# = 210, and restating the 2–30 range. That is enough to make the lone parameter understandable.

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 the specific computation: whether n# + 1 and n# - 1 are prime, where n# is the product of primes up to n. It gives concrete examples, so the operation is clear. It does not explicitly name sibling alternatives such as primorial or prime_check, but the unique primorial-neighbor operation is distinguishable.

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 description supplies the valid input range, n runs from 2 to 30, and examples that imply when this tool is relevant. However, it does not say when to use this tool instead of sibling tools like primorial or prime_check, nor does it state exclusions or failure conditions. Usage is therefore implied rather than explicitly guided.

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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