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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals the data source (Frost archive) and the depth of history (100+ years), which informs expectations about temporal coverage. However, it does not disclose output format, pagination, units, error handling, or any access limitations—gaps that are material for an agent.

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 sentence that front-loads the core action ('Daily historical observations') and immediately follows with useful context (Frost archive, 100-year span) and a practical pointer (find_weather_stations). Every word earns its place with no redundant or vague wording.

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?

With no output schema and no annotations, the description is sparse. It covers the purpose and prerequisite but omits return-value details (e.g., units, format, whether data is aggregated daily) and error behavior (e.g., missing data handling). While the schema explains parameters, an agent still lacks enough information to confidently interpret the tool's response.

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 input schema provides 100% coverage with descriptive text for all four parameters, including defaults for 'elements' and pattern constraints for dates. The description adds no extra parameter-level meaning beyond pointing to find_weather_stations for station_id, which is already implied in the schema. The baseline of 3 is appropriate when schema covers everything.

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 the core function: 'Daily historical observations from a weather station.' It specifies the data source (Frost archive) and historical depth (over 100 years), which distinguishes it from sibling tools like get_forecast and get_nowcast. The purpose is unambiguous and correctly frames the tool's scope.

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 explicitly instructs to use find_weather_stations to locate station ids, providing a clear prerequisite for use. It implies historical usage via the word 'historical' but does not explicitly contrast with forecast/nowcast tools. The guidance is helpful but could be more explicit about when not to use this tool.

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