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Cruise regions

list_cruise_regions
Read-onlyIdempotent

Every region cruise ships sail (oceans, then rivers), what a cruise there is usually like, how many ships on Cruises Frog sail it, and its page.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_cruise_regions"
  }
}

Input Schema

NameRequiredDescriptionDefault
kindNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world, and non-destructive, so the safety profile is covered. The description adds value beyond that by disclosing what each entry contains (cruise character, ship count on Cruises Frog, page link) and an ordering rule (oceans, then rivers), which is real behavioral context. It stops short of saying whether the list is paginated or stable across calls.

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?

One front-loaded sentence that packs scope, contents, and ordering with no filler. The phrasing 'how many ships on Cruises Frog sail it, and its page' is slightly convoluted and the brand name reads oddly mid-clause, costing a point on polish rather than substance.

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-optional-param read-only list tool with no output schema, the description covers purpose, entry contents, and ordering well enough to call it confidently. The only meaningful gap is that the effect of the 'kind' filter is never stated, so an agent cannot predict whether passing it changes the result set or merely the sort.

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 coverage is 0%, so the description must compensate, and it largely does not: the single optional 'kind' parameter with enum ocean/river is never mentioned as a filter. The parenthetical '(oceans, then rivers)' reads as an output ordering note rather than an explanation that kind narrows the result set. The enum values are self-explanatory, keeping this at a viable but unhelpful-for-the-param 3.

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 names a specific verb+resource pair implicitly (listing cruise regions) and enumerates the fields each region carries: cruise style, ship count, and page. It distinguishes itself from siblings like list_cruise_ports or list_cruise_lines by scope, though it never names those siblings explicitly to sharpen the boundary.

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?

Usage is only implied: an agent can infer this is the browse/discovery entry point for cruise geography, but there is no explicit statement of when to call it versus list_cruise_lines, list_cruise_ports, or list_cruise_ships. No exclusions or prerequisites are given, which is tolerable for a zero-required-param list tool but leaves routing to inference.

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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