get_forecast

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

With no annotations, the description carries the full behavioral burden, yet it only adds the 'anywhere in the world' scope. It omits the forecast horizon, units, update frequency, and any auth or rate-limit notes, leaving meaningful behavioral gaps.

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?

Front-loads the purpose in the first line, then documents the single argument compactly. No wasted sentences, though the 'Args:' block is mildly redundant for a one-parameter tool.

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?

An output schema exists, so return structure need not be explained, and the sole parameter is illustrated. However, key call-affecting context such as forecast horizon (how many days) and units is absent for what is otherwise a simple 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?

Schema coverage is 0%, so the description must compensate, and it does so usefully by giving format examples ('Delhi', 'New Delhi, India', 'Tokyo') that reveal the accepted granularity from bare city to city-plus-country. That is genuine value the bare string schema lacks.

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?

States a specific verb and resource (get the weather forecast) with a clear global scope ('anywhere in the world'). It implicitly contrasts with the sibling get_air_quality by naming weather specifically, but never explicitly differentiates itself from that sibling.

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?

There is no guidance on when to use this tool versus the sibling get_air_quality, nor any context such as whether it returns current conditions or a multi-day forecast. The agent must infer the trigger from the name alone.

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