getCabinDetailOne specific cabin by ship and room number: deck, side and position, category with size and how many it sleeps, connecting cabin, known issues (obstructed view, noise, long walk) and what cruisers who stayed there said. "No issues recorded" is not a guarantee of none.
| Name | Required | Description | Default |
|---|---|---|---|
| ship | Yes | Ship name, e.g. "Allure of the Seas" | |
| cabin | Yes | Cabin number, e.g. "9318" or "D126" |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
While annotations already declare read-only, idempotent, and closed-world behavior, the description adds a valuable caveat that 'No issues recorded' is not a guarantee of none, disclosing data completeness limitations. It also clarifies that 'known issues' include categories like obstructed view, noise, and long walk, giving the agent accurate expectations about data quality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the core purpose and then enumerates the returned fields. It is efficient, contains no filler, and the appended caveat earns its place as meaningful additional context. Minor structural improvements are possible, but it remains compact and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Since there is no output schema, the description takes on the burden of explaining return contents, and it covers deck, side, position, category, size, occupancy, connecting cabin, known issues, and cruiser feedback. For a two-parameter read-only lookup, this is sufficiently complete for an agent to invoke the tool correctly and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully covers both parameters with descriptions, examples, and patterns (100% coverage). The description only restates 'by ship and room number' without adding new semantic detail, so a baseline score of 3 is appropriate per the rubric.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as retrieving details for one specific cabin, identified by ship and cabin number. It lists the exact information returned (deck, side, position, category, size, occupancy, connecting cabin, issues, cruiser feedback), which distinguishes it from sibling tools like getShipCabins that likely handle broader cabin listings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a single-cabin lookup through 'One specific cabin by ship and room number,' but it does not explicitly state when to use this tool over alternatives. It also does not mention getShipCabins or other siblings, so the guidance is implicit rather than explicit.
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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