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get_beach_data_uv

Retrieve beach forecasts or UV index data from AEMET for any Spanish beach by name or ID, with up to 4 days of forecast.

Instructions

Query information on beaches or UV index from AEMET.

Args: name_or_code: Partial or full name of the beach, or its BEACH_ID. Also accepts 'list' or 'list:'. dias_frc: Number of forecast days, starting form 0, which means 0 days from today, to 4, which means 4 days from today. query_type: 'beach' for forecast, 'UV_index' for UV index, must be in english.

Returns: Requested information or list of matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nombre_o_codigoYes
dias_frcYes
tipo_consultaNoplaya
Behavior3/5

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

With no annotations, the description bears full burden. It mentions query_type options and return type ('Requested information or list of matches'), but does not disclose side effects, authentication needs, rate limits, or error conditions. It is moderately transparent but incomplete.

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?

The description is concise—three short sentences for purpose and parameters, plus a returns line. It is front-loaded and free of extraneous text, earning its space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 3 params and no output schema. Description explains all params and return type generically, but does not specify output format or handling of missing data. Additionally, parameter names in the schema are in Spanish while description uses English, potentially causing confusion.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It explains each parameter: name_or_code can be partial name, BEACH_ID, or 'list:<province>'; dias_frc range 0-4; query_type values 'beach' or 'UV_index' with English requirement. This adds significant meaning beyond the schema's minimal field names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool queries information on beaches or UV index from AEMET, with specific verb and resource. It distinguishes from siblings like get_station_data and get_daily_forecast which cover different weather data.

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?

The description explains parameters and their use (e.g., 'list' for listing, query_type for beach vs UV), but does not explicitly state when to avoid this tool or point to alternatives among siblings. No exclusions are provided.

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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