get_weather

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

No annotations are provided, so the description carries the full behavioral burden, and it does disclose the most important trait: output is always fixed at 77°F/sunny regardless of input. It does not mention error behavior for unknown cities, input validation, or any side effects, which keeps it short of a 5.

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?

Two short sentences, zero filler, and the core capability plus its key caveat are front-loaded in that order. Every clause earns its place.

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 values need no explanation, and the description additionally warns that those values are constant. For a one-parameter mock utility this is nearly complete; only invalid-input behavior is left unstated.

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. Saying weather is fetched 'for a city' maps the single parameter to the right concept, but gives no format guidance (city name vs. country-qualified string) and, crucially, does not note that the value does not affect the result.

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 weather for a city') and immediately clarifies the tool's nature as a deterministic mock rather than a real data source. No sibling tool does weather, so there is nothing to confuse it with, and the second sentence prevents an agent from treating it as a live API.

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?

Usage is implied by the purpose ('get weather for a city') and there is no competing alternative to route against. However, there is no explicit statement of when to use it (e.g., for demos/tests rather than real forecasts) or when not to.

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