parking_availabilityEstado de los aparcamientos públicos de Alicante: plazas libres cuando hay observación de sensores vigente, y ficha (capacidad, dirección, tarifa) cuando solo existe catálogo. dataType declara si el dato es LIVE o CATALOG.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already indicate a read-only, idempotent, open-world operation. The description adds meaningful behavioral context by explaining that the result shape depends on whether a live sensor observation is current or only a catalog entry exists, and it explicitly mentions the `dataType` field distinguishing LIVE from CATALOG.
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 compact and front-loaded: the first clause states the core purpose, followed by a concise explanation of the conditional response and the key dataType field. No sentences are wasted, and the structure is easy to parse.
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 tool with no output schema, the description gives enough information to understand the general response shape, including plausible fields such as capacity, address, and tariff. It could be more explicit about what happens when no sensor observation and no catalog entry exist, but the core calling context is adequately covered.
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 the baseline is 4. The description does not need to explain input semantics and adds relevant context about the output's dataType indicator, which is useful even though it is not an input parameter.
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 states that the tool returns the status of public parking in Alicante, including free spaces under live sensor observation and catalog details when only catalog data exists. It is specific about the resource and scope, though it uses a noun phrase rather than a strong imperative verb and does not explicitly differentiate itself from sibling tools.
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 intended use case is implied through the domain-specific content about Alicante parking availability, so an agent can infer when to use it. However, there is no explicit guidance about when not to use this tool or what alternative to choose, leaving usage selection to inference.
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.