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Aleva open data

Guest nights per county and year

guest_nights_by_county
Read-onlyIdempotent

Guest nights per county and year. Returns a list of records; pass next_cursor to get the next page. Fields: year (integer); county_code (varchar); county (varchar); nights (bigint); foreign_share (double).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoYear (equals)
limitNoHow many rows to return
cursorNonext_cursor from the previous result, for the next page
year_gteNoYear (at least)
year_lteNoYear (at most)
county_codeNoCounty code (equals)
county_code_inNoCounty code (any of)

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 readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description earns credit by adding pagination behavior (cursor-based paging) and a full return-field list, which is meaningful given the absence of an output schema.

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?

Front-loaded purpose statement followed by pagination mechanics and a compact field list, with no filler. The dense semicolon-separated field enumeration is slightly list-like but every element is informative given no output schema.

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 paginated read-only aggregation endpoint with no output schema, the definition covers what is returned (five named fields with types) and how to page. Filtering semantics are fully delegated to the schema, which is complete, so nothing critical is missing.

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 description coverage is 100%, so the schema already documents all seven parameters including year filters and county_code_in. The description adds no parameter syntax or semantics beyond that; its field list describes return values rather than inputs. Baseline 3 is appropriate.

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 a clear resource and grouping dimension: 'Guest nights per county and year.' An agent can distinguish it from guest_nights (unaggregated) and guest_nights_by_country, though the description never names those siblings explicitly, so differentiation relies on the agent inferring from the name.

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 pagination instruction ('pass next_cursor to get the next page') is a concrete invocation guideline. However, there is no guidance on when to choose this over guest_nights or guest_nights_by_country, and no prerequisites or constraints are stated, leaving sibling 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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