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Lazy Caterer

lazy_caterer
Read-onlyIdempotent

The lazy caterer number, the most pieces of a pancake cut by n straight cuts: n*(n+1)/2 + 1. Zero cuts give 1, three give 7, and five give 16. n runs from 0 to 10000000. Price: $0.001 USDC per successful call (x402, Solana). Same tool over HTTPS: POST https://scorptech.it.com/api/x402/v1/lazy-caterer

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": "lazy_caterer"
  }
}

Input Schema

NameRequiredDescriptionDefault
nYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, so the safety profile needs no restating. The description adds genuinely non-structured context: a $0.001 USDC charge per *successful* call via x402 on Solana, plus an equivalent HTTPS endpoint. It omits only minor details like output shape, which is implied by the integer formula.

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?

Four compact segments — definition+formula, examples, domain range, pricing/endpoint — with the core meaning front-loaded. The worked examples are a small luxury but serve a verification purpose; nothing is padded.

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?

No output schema exists, so the description carries that burden, and the formula plus concrete examples effectively communicate the integer return value. Domain bounds, cost, and transport alternative are all present. An agent has everything needed to call it correctly; only explicit sibling differentiation is missing.

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% — the schema only says 'integer, 0..10000000'. The description compensates by explaining that n is the number of straight cuts and restating the allowed range, plus worked examples (0→1, 3→7, 5→16) that let an agent sanity-check its input. Good compensation for a single undocumented parameter.

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?

States precisely what is computed — the lazy caterer number, defined as the maximum pieces of a pancake from n straight cuts, with the closed form n*(n+1)/2 + 1. That formula makes the operation unambiguous to an agent. It does not, however, address the very similarly-named sibling cake_number, which is the one real disambiguation risk in this catalogue.

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 implied usage (call this to get the lazy caterer value for a given cut count) is clear, and the domain constraint n ∈ [0, 10000000] is stated. There is no explicit guidance on when to prefer this over an alternative, and the near-duplicate sibling cake_number is never mentioned.

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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