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

No annotations are provided, so the description carries the burden of behavioral disclosure. It indicates a read-only 'current weather' lookup, but it does not disclose units, data source, freshness, or error behavior. With an output schema present, some gaps are mitigated, but the description adds little beyond the tool name.

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 core description is a single, front-loaded sentence with no wasted words. However, the '[COST: ]' prefix is an empty placeholder that adds noise rather than useful information, preventing a perfect score.

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?

For a zero-parameter, single-city weather lookup with an output schema, the description is almost sufficient. It identifies the exact location and data type, and the output schema supplies return-value details. The missing cost placeholder and lack of any extra behavioral notes are minor given the tool's simplicity.

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 tool has zero parameters, and the schema confirms this. The description does not need to explain parameter semantics because there are none to document; the baseline of 4 applies.

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: 'Get current weather in NYC.' This clearly differentiates it from sibling tools like get_london_weather or get_berlin_weather by naming the city, so an agent can immediately understand its scope.

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 makes the usage context clear: use this tool when current NYC weather is needed. It does not explicitly name alternatives or say when not to use it, but the geographic scope is obvious from both the name and description, so no exclusion is strictly necessary.

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