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 readOnlyHint=true, openWorldHint=true, and idempotentHint=true, so the safety profile is covered. The description adds useful context about AEMET official warnings and the breadth of data, but it does not disclose freshness, update cadence, or any limitations beyond the annotation coverage.
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 well-structured sentence that front-loads the core information and packs each listed data category with meaning. No filler or redundancy is present.
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 no-parameter, read-only tool with annotations covering behavior, the description is largely complete: it names all major output categories and the official warning source. It could be strengthened by clarifying how weather_now differs from beach_conditions, but nothing essential to invoking it correctly is missing.
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 no parameter burden for the description to carry. The baseline of 4 applies, and the description appropriately focuses on what the tool returns rather than input semantics.
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 enumerates the resource (current weather in Alicante) and the data categories it returns (temperature, wind, humidity, UV, forecast, sea state, AEMET warnings), so an agent can infer the tool's purpose. However, it lacks an explicit action verb and does not directly contrast itself with the overlapping sibling beach_conditions, which may also cover sea temperature and wave height.
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 no guidance on when to use this tool versus alternatives like beach_conditions or search_alicante. An agent must infer that weather_now is the right choice for general weather plus official warnings, which is not ideal given the potential overlap with beach_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.
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.
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.
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.
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.