get_growing_degree_days

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

With no annotations provided, the description carries the burden well: it discloses the modified-average clamping behavior, daily versus weekly aggregation, ERA5 archive versus forecast data sourcing, and merging behavior. It does not discuss error handling, authentication, or rate limits, but the core behavioral traits are unusually transparent.

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 dense and front-loaded: it leads with the core operation, then documents date rules, units, method behavior, aggregation, data sources, and an example. Every sentence adds practical information without redundancy.

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 tool has an output schema, so return-value details need not be fully repeated. The description still covers date limits, units, aggregation granularity, and data sourcing, but it omits possible method alternatives and any limitations around coordinate validity or errors.

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 description coverage is 0%, so the description must compensate, and it does for most parameters: date format and range, temperature units, base/cap semantics, and the modified-average method. It does not explain possible values for the method parameter beyond the default method's behavior, leaving a small gap.

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 states a specific verb and resource: "Calculate accumulated growing degree days from daily temperatures." This clearly identifies the agricultural metric and distinguishes it from sibling tools such as get_frost_risk or get_water_balance.

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 provides useful operating constraints, such as an inclusive date range of at most 366 days and daily versus weekly output. However, it does not explicitly state when to choose this tool over siblings or when not to use it; usage is implied rather than directly guided.

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