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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently reveals the output structure: twelve monthly means and the months exceeding 20°C, including the temperature threshold. It does not discuss error handling or edge cases, but for a simple read-only query tool this is reasonable.

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 two sentences with no filler. It front-loads the core output (twelve monthly means, threshold months) and then supplies the motivating question, making it easy for an agent to quickly grasp the tool's purpose.

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 single-parameter tool with no output schema, the description adequately covers what the tool returns and why an agent would use it. The input schema already documents the parameter, so nothing critical is missing for correct invocation.

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%, with id_or_name fully described as 'Beach id, Wikidata Q-id or name'. The description adds minimal semantic value beyond reinforcing that the tool targets one beach, so the baseline score of 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 clearly states what the tool returns: twelve monthly mean temperatures for a single beach plus the months reaching 20°C. It also frames the tool around a concrete question ('when is it warm enough there?'), which distinguishes it from siblings like warmest_beaches_in_month, which compares beaches rather than a single beach across a year.

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 the appropriate use case: checking the year-round temperature profile for one specific beach. It does not explicitly mention alternatives or exclusion conditions, but the emphasis on 'one beach' and 'whole year' gives enough contextual guidance to avoid confusion with search_beaches or warmest_beaches_in_month.

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