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mcp-server

Mi parada favorita

favorite_stop
Read-onlyIdempotent

Ficha completa de una parada de autobús concreta de Alicante (nombre, coordenadas, líneas) junto con sus próximas llegadas. Las llegadas se extraen SIEMPRE bajo demanda desde la fuente oficial del Ayuntamiento de Alicante / «Alicante se mueve» mediante /api/public/v1/bus/live-arrivals. Si no hay respuesta LIVE, el único fallback es estimated_eta del motor predictivo propio, claramente ESTIMATED; nunca uses llegadas cacheadas antiguas como dato actual.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stopYesCódigo oficial de la parada, p. ej. 1010.

TDQS

A3.7/5.0
Behavior5/5

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

The description adds substantial behavioral detail beyond the readOnly/openWorld/idempotent annotations: it discloses the official live data source (Alicante se mueve API), the on-demand fetching policy, the fallback to a predictive estimated_eta (clearly marked ESTIMATED), and the explicit rule never to use stale cached arrivals. This is exactly the transparency an agent needs to reason about data freshness and reliability.

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?

The description is one dense paragraph that front-loads the core purpose and then covers critical data-freshness and fallback behavior. It is written in Spanish, consistent with the title, and every sentence contributes useful information. It is slightly long but not wasteful.

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 read-only tool with a single parameter and no output schema, the description is quite complete: it specifies the returned fields (name, coordinates, lines, arrivals) and the crucial live-data/fallback policy. It does not detail the exact output structure, but that is acceptable given the tool's simplicity and the schema's clarity.

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?

The input schema fully documents the single 'stop' parameter with a format pattern and an example. The description adds no additional meaning about the parameter beyond what the schema already provides, so the baseline score of 3 applies given the 100% schema description coverage.

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 clearly states the tool retrieves a complete record of a specific bus stop (name, coordinates, lines) along with upcoming arrivals. It specifies the resource and the action, but it does not explicitly differentiate from sibling tools like find_transit_stop or next_departures, so it stops short of a 5.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool over alternatives. The description implies it is for a specific known stop but never says 'use when you already have the stop code' or contrasts with find_transit_stop or next_departures. No exclusions or alternative recommendations are provided.

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

A3.7/5.0
Disambiguation3/5

Several tools overlap in purpose: find_transit_stop and resolve_entity both resolve stops, while get_current_state, next_departures, favorite_stop, parking_availability, and beach_conditions all provide state/arrival information in different forms. The detailed descriptions help, but an agent could easily select the wrong tool when asked for simple arrival or status information.

Naming Consistency3/5

All names use snake_case and are readable, but the pattern is mixed: some are verb-led (find_place, get_current_state, resolve_entity), some are noun phrases (beach_conditions, fuel_prices, flight_status), and others are quirky (whats_on, catch_vehicle_decision). This is not chaotic, but it lacks a strong consistent convention.

Tool Count4/5

With 16 tools, the server is just above the ideal 3-15 range, but the broad Alicante information domain justifies the count. Each tool covers a distinct vertical or query path, and the set feels reasonably scoped rather than bloated.

Completeness4/5

The tool surface covers the main Alicante information domains well: transit, beaches, parking, food, places, flights, fuel, weather, and events, plus discovery/resolution helpers. There are minor gaps such as no direct traffic or bike-sharing tool, but agents can work around them via find_place or search_alicante.

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