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 explains the data source (National Weather Service), the forecast type (multi-day), and geographic constraints, but omits potential behaviors like error handling for invalid coordinates, data update frequency, or specific return format. This is adequate but not rich.

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 concise and well-structured: a purpose statement, a sentence on scope/source, and a clear Args section. Every sentence earns its place without redundancy. It is front-loaded with the core verb and resource.

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 is simple (2 numeric parameters) and has an output schema, so return value documentation is not needed. The description covers purpose, geographical scope, and parameter examples, making it complete for typical use. It lacks details on error behavior or units, but these are not critical for a straightforward forecast tool.

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 schema provides only type and title for latitude and longitude, with zero description coverage. The tool description compensates fully by explaining each parameter with concrete examples (e.g., 38.8894 for Washington DC), adding meaning well beyond the schema. The Args section is directly informative.

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 ('Get') and resource ('weather forecast') with clear location parameters, distinguishing it from sibling tools like get_alerts and get_alert_detail, which focus on alerts. The scope is explicitly stated as a multi-day National Weather Service forecast, providing a precise purpose.

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 clearly states the tool works only for locations within the United States and its territories, providing an implicit exclusion for international locations. It does not explicitly contrast with sibling alert tools, but the purpose is so distinct that usage context is clear. No explicit 'when not to use' guidance is given.

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