select_weather_forecast_city_israel

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states the immediate action and does not explain what selecting the city does, whether it mutates state, or how it connects to the forecast workflow. The phrase 'autocomplete suggestion list' adds some context, but the effects and sequencing remain undisclosed.

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 with no redundancy or filler. Every word contributes to the meaning, and it is appropriately sized for a simple zero-argument selection action.

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?

The tool is simple: no parameters and an output schema exists, so return-value documentation is not needed. However, the description lacks workflow context and behavioral detail, such as when this tool should be invoked relative to its siblings. This makes it minimally viable but incomplete for an agent that must reason about the overall weather-forecast interaction sequence.

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 description coverage is 100%. Per the baseline for zero-parameter tools, the description does not need to add parameter-level meaning, and it does not need to compensate for any schema gaps.

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 ('Select') and a specific resource ('the first city from the autocomplete suggestion list'). This clearly differentiates the tool from siblings like `enter_weather_forecast_city_israel` and `get_weather_forecast_content_israel`. It does not explicitly frame the action within the larger forecast flow, so it stops short of a 5.

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 implicitly tells the agent when to act: when an autocomplete suggestion list is presented and the first city should be chosen. However, it gives no explicit guidance about prerequisites, such as needing to call `enter_weather_forecast_city_israel` first, nor does it name alternatives or when not to use this tool.

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