get_forecast

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

No annotations provided, so description fully discloses behavior: explains modes (daily, hourly, raw), default settings, units system, and that main temperature/wind are always in Fahrenheit/mph due to NWS data.

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?

Well-structured with front-loaded purpose and use cases, but somewhat long. Every sentence adds value, so slight deduction for verbosity.

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?

Given 6 parameters, no required fields, multiple modes, and units system, description covers all aspects. Output schema exists, so output format not needed. Complete.

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 has 0% description coverage; description compensates by explaining each parameter: lat/lon optional, modes, days/hours ranges, and detailed unit overrides. Adds significant meaning.

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?

Clearly states it gets a forecast for US locations, uses specific verb and resource. Differentiates from sibling tools like get_conditions and get_alerts by specifying 'forecast'.

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?

Provides example queries for when to use ('What's the forecast?', 'Will it rain?'). Does not explicitly state when not to use or compare to alternatives, but context signals imply differentiation.

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