select_weather_forecast_city_israel

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

With no annotations, the description fully discloses the key behavioral traits: it selects from dropdown or falls back to pressing Enter. It does not detail behavior with multiple matches or failure cases, but for a simple UI action it is transparent enough.

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?

Single sentence of 14 words conveys all necessary information with no redundancy. Every word 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?

For a tool with no parameters and an output schema present, the description sufficiently explains the tool's action. It covers the primary behavior and fallback, making it complete for an agent to use.

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?

No parameters are defined, and schema coverage is 100% (since none exist). Baseline score of 4 applies as the description does not need to add parameter info.

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 selects the city from an autocomplete dropdown, with a fallback to pressing Enter. Verb 'Selects' and resource 'city from autocomplete dropdown' are specific, and the description distinguishes from sibling 'enter_weather_forecast_city_israel' (which likely types the city).

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 context on when to use the fallback (press Enter if dropdown not present), implying the tool is used after typing a city name. However, it does not explicitly compare to alternatives or state when not to use it.

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