weather_nowTiempo actual en Alicante (temperatura, viento, humedad, UV), previsión, temperatura del mar y altura de ola, junto con los avisos meteorológicos oficiales de AEMET vigentes.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, idempotent, and open-world, so the safety profile is covered. The description adds useful output context (current conditions, forecast, sea state, warnings) but does not disclose details like update frequency, units, or data recency.
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 a single sentence that front-loads the essential scope and then lists the specific output categories without any filler or repetition. Every clause contributes useful information.
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 zero-parameter read-only tool, the description adequately conveys what data will be returned and which official source is used. It does not specify units or forecast horizon, but these are not strictly required for an agent to invoke the tool 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?
The tool has zero parameters, so there is nothing for the description to add beyond the schema. The baseline of 4 applies because parameter semantics are not relevant.
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 (weather in Alicante) and the specific data included: temperature, wind, humidity, UV, forecast, sea temperature, wave height, and AEMET warnings. It lacks an explicit action verb and does not differentiate itself from sibling tools like beach_conditions, which could overlap on sea state data.
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?
No guidance is provided about when to prefer this tool over alternatives. Given siblings like beach_conditions, which may cover sea temperature and wave height more specifically, the agent must infer the right choice from the tool name and description alone.
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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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.