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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

A4.1/5.0
Behavior5/5

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

Beyond the readOnlyHint/openWorldHint/idempotentHint annotations, the description discloses the live official source endpoint, mandatory on-demand retrieval, the estimated_eta fallback when live data is unavailable, and an explicit prohibition against using old cached arrivals as current data. This materially shapes behavior without contradicting the annotations.

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?

Two front-loaded sentences: the first states the purpose and card contents, the second details freshness and fallback behavior. Every clause carries operational weight with no filler.

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?

With one fully documented parameter and annotations covering safety, the description supplies the remaining essential context: output contents, live-source behavior, fallback semantics, and a staleness warning. No output schema exists, but the description gives enough shape—stop fields plus arrivals—to invoke the tool correctly.

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 100%: the stop parameter is fully described as an official code with an example and a numeric pattern. The description adds no additional parameter nuance beyond referring to a concrete stop, so 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?

The description names a concrete resource—a complete Alicante bus stop card with name, coordinates, lines, and next arrivals—and a clear retrieval purpose. It does not explicitly contrast this tool with siblings such as next_departures, so it stops short of full differentiation.

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 context is implied: use it when you need a full stop card plus current arrivals, and the description instructs that arrivals must always be fetched live. However, it provides no explicit when-to-use versus alternatives or exclusions, so an agent must infer tool selection from sibling names.

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

Most tools map cleanly to distinct domains (beach, fuel, weather, events, flights), but several transit tools overlap: find_transit_stop, favorite_stop, next_departures, get_current_state, and resolve_entity all deal with finding stops/stations and/or retrieving arrivals. Descriptions provide flow hints, so an agent can often disambiguate, but the boundaries are not crisp.

Naming Consistency3/5

Names mix verb-led patterns (find_*, resolve_entity, get_current_state) with noun-led patterns (beach_conditions, fuel_prices, parking_availability) and oddities like favorite_stop and whats_on. The style is readable and mostly snake_case, but there is no consistent verb_noun convention.

Tool Count3/5

16 tools is at the heavy end, and the travel-info surface could be consolidated (e.g., favorite_stop vs next_departures vs get_current_state). That said, Alicante's broad scope—transit, parking, beaches, food, weather, fuel, flights, events—makes the count defensible.

Completeness4/5

The set gives agents discovery (search_alicante, discover_capabilities), entity resolution (resolve_entity), and live/catalog state across transport, parking, beaches, weather, fuel, food, POIs, and events. Minor gaps exist (no general route planning, no editing/persistence beyond 'favorite'), but core informational workflows are well covered.

Resources