Beach forecast for a Spanish beach

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

With no annotations, the description carries the full burden. It discloses that the forecast covers 591 beaches during the bathing season, which hints at a seasonal limitation, and mentions input flexibility (accents optional, code). It does not disclose error handling, availability, or whether the forecast might be empty outside the season, but for a read-only forecast tool these are minor. The description adds some behavioral context beyond the schema, but not exhaustive.

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-organized paragraph that front-loads the core purpose (three-day forecast with specific fields), then covers scope and input options. Every sentence contributes useful information with no fluff or repetition. It is appropriately sized for the tool's complexity.

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?

The description explains the output (sky, wind, waves, temperatures, UV index) and the input methods, covering both what the tool returns and how to specify location. It does not describe the exact return format (e.g., JSON structure) or error cases, but since there is no output schema, the description provides sufficient context for an agent to call it correctly. Minor gaps like units or error handling are not critical.

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%, so the schema already documents all three parameters thoroughly. The description restates the location options (accents, municipality, code) and adds the note that a municipality alone lists beaches, but this is also present in the schema. The description does not add new semantic meaning beyond what the schema provides, so a baseline 3 is appropriate.

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 uses a specific verb ('Returns') and names the exact resource ('AEMET beach forecast') along with the covered period and data fields. It clearly differentiates from siblings like get_mountain_forecast and get_maritime_forecast by specifying 'beach' and 'AEMET', so an agent can identify it without opening other definitions.

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 implies when to use it: for beach forecasts from AEMET. It also explains input options (name, municipality, code) and mentions seasonal coverage. However, it does not explicitly state 'use this for beaches, not mountains or maritime', leaving some inference to the agent. The clear resource name and sibling names make the intended usage obvious, so this is above average.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.