select_weather_forecast_city_israel

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states two behaviors: selecting the first suggestion and opening the forecast page. It does not disclose potential edge cases (e.g., empty list) but for a simple parameterless action, this is adequate.

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 description is a single, front-loaded sentence ('Select the first city suggestion...') with no filler. Every word contributes to understanding the tool's action and effect.

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 the tool has 0 parameters and an output schema exists, the description adequately covers the tool's behavior. It could mention a prerequisite (e.g., 'after entering a city name, suggestions will appear'), but the context from sibling tools implies this. Overall, it is complete enough for a simple selection action.

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 input schema has zero parameters, so there is no parameter meaning to explain. The baseline for 0-parameter tools is 4, and the description adds no unnecessary parameter-related details.

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 uses a specific verb ('Select') and clearly identifies the target resource ('the first city suggestion from the autocomplete list') and the subsequent action ('open its forecast page'). This distinguishes it from sibling tools like enter_weather_forecast_city_israel (entering text) or get_weather_page_content (reading content).

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 implies usage context: it is meant to be invoked when an autocomplete list is available. However, it does not explicitly mention alternatives or when not to use it, such as 'Use this after entering a city name' or 'Prefer open_weather_forecast_israel if the city is already known.'

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