beach_conditionsBandera vigente y estado de las playas de Alicante (y municipios próximos) con su ficha: servicios, accesibilidad y URL canónica. Acota por nombre de playa o municipio.
| Name | Required | Description | Default |
|---|---|---|---|
| beach | No | Nombre de la playa, p. ej. «Postiguet». | |
| limit | No | Resultados (máx. 10). | |
| municipality | No | Municipio, p. ej. «Alicante». |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, idempotent, and open-world. The description adds useful behavioral context by specifying that it returns current flag/state and a beach record with services, accessibility, and canonical URL, which goes beyond the annotations without contradicting them.
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 two tight sentences with no filler. It front-loads the core purpose, lists the relevant record contents, and ends with a clear filtering instruction.
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?
For a simple read-only tool with no required parameters and no output schema, the description is complete: it states the geographic scope, the data included, the filtering options, and the currency of the data. An agent has enough to invoke it correctly.
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?
Schema coverage is 100%, with each parameter already described in Spanish with examples. The description adds only the framing that beach and municipality act as filters, which is a modest enhancement over the schema baseline.
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 resource (beaches in Alicante and nearby municipalities) and the content returned (current flag/status, services, accessibility, canonical URL). It is narrowly scoped and easily distinguished from generic siblings like find_place or search_alicante.
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 gives clear context: this tool is about beach status in Alicante and nearby municipalities. It also states the filtering mechanism ('Acota por nombre de playa o municipio'), though it does not explicitly name sibling alternatives or when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.