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Bell

bell
Read-onlyIdempotent

The nth Bell number, the number of partitions of a set of n objects. B(0) and B(1) are 1, and B(5) is 52. n runs from 0 to 80. Past 15 digits the value is a decimal string. Price: $0.001 USDC per successful call (x402, Solana). Same tool over HTTPS: POST https://scorptech.it.com/api/x402/v1/bell

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": "bell"
  }
}

Input Schema

NameRequiredDescriptionDefault
nYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the description does not need to cover safety. It does add valuable non-schema behavior: pricing ($0.001 USDC per successful call via x402 on Solana), the alternate HTTPS endpoint, and that values past 15 digits are returned as a decimal string.

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?

Every sentence carries useful information: definition, examples, range, output format, pricing, and alternate endpoint. It is front-loaded with the core meaning and has no filler.

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?

For a one-parameter mathematical tool with no output schema, the description covers semantics, bounds, examples, output representation for large values, and payment mechanics. Nothing material is left ambiguous for an agent to call it 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 coverage is 0% and the single parameter has only min/max bounds in the schema. The description compensates well by explaining that n is the set size, giving the valid range 0–80, concrete examples, and the output format for large results.

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 gives a precise mathematical definition ('nth Bell number, the number of partitions of a set of n objects') and bounds (n from 0 to 80), so the agent knows exactly what is computed. It does not differentiate from related siblings like bell_sum or lynch_bell, which keeps it short of a 5.

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 intended use is implied by the definition and examples (B(0), B(1), B(5)), and the n range is stated. However, there is no explicit guidance on when to choose this over siblings such as bell_sum or lynch_bell, nor any exclusions.

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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