travel-trends-mcp

country_tourism_profile

Read-onlyIdempotent

Tourism profile for one EU-27 country — a decade of Eurostat data.

Use this tool for questions about a country's tourism statistics,
seasonality or visitor mix, not for live disruptions.
Pure projection of the published artifacts (countries/<code>.json +
competitiveness.json): yearly nights/arrivals totals with YoY, average
stay, seasonality (peak month and peak-to-mean ratio, formula disclosed),
domestic vs foreign visitor share, recovery vs 2019, growth vs the EU
average, and computed competitiveness insights (each labeled with its
basis). Every number is computed from the same public dataset the site
serves — nothing narrated, nothing estimated; links carry the citable
page + raw JSON. `code` is EU-27 ISO2 (Greece = "EL"). Unknown country ->
{"error": "unknown_country"}; missing artifact -> {"error": "unavailable"}.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`code`	Yes

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint), the description adds critical behavior: it is a 'pure projection of the published artifacts,' discloses that 'every number is computed from the same public dataset,' provides error formats for unknown country ('unknown_country') and missing artifact ('unavailable'), and notes that links carry citable pages plus raw JSON. This is rich contextualization with no contradiction.

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?

The description is information-dense yet each sentence earns its place: purpose, usage guideline, data source, metric list, parameter format, and error handling. It is front-loaded with the primary function and contains no filler or tautology.

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?

Given there is no output schema, the description enumerates all return aspects: YoY totals, average stay, seasonality with peak-to-mean ratio, visitor share, recovery vs 2019, growth vs EU average, and competitiveness insights. It also documents data provenance, error cases, and link details, making it self-sufficient for the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 0%, the description fully compensates by explaining that `code` is an EU-27 ISO2 code and gives the concrete example 'Greece = "EL"'. It also clarifies behavior for invalid or missing artifacts, which helps the agent invoke the tool correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Tourism profile for one EU-27 country — a decade of Eurostat data,' which is a specific verb+resource statement. It also explicitly differentiates from siblings by saying 'Use this tool for questions about a country's tourism statistics, seasonality or visitor mix, not for live disruptions,' making its scope unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly states when to use the tool (for tourism statistics, seasonality, visitor mix) and when not to use it (not for live disruptions). However, it does not name alternative tools for live disruptions, though the sibling list includes candidates like list_events, so the guidance is not fully explicit on alternatives.

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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TDQS

A4.6/5.0

Disambiguation5/5

Every tool has a clearly distinct purpose, with explicit cross-references to differentiate overlapping tools (e.g., get_trip_updates_since vs whats_changed, assess_trip vs watch_trip). There is no ambiguity in when to use each tool.

Naming Consistency2/5

Naming is inconsistent: some tools use verb_noun (assess_trip, list_events, watch_trip), some use noun_noun (country_briefing, country_tourism_profile), and one uses a question phrase (whats_changed). This mixed convention reduces predictability.

Tool Count5/5

8 tools is well-scoped for a travel-trends server, covering trip assessment, monitoring, update retrieval, event browsing, daily briefing, and tourism statistics. Each tool earns its place without unnecessary bloat.

Completeness4/5

The core workflows (assess, watch, get updates, explain silence, list events) are well covered. The only notable gap is the absence of trip lifecycle management, such as an unwatch_trip or list_trips tool, which is a minor omission.

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