extract_weather_data_israel

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

With no annotations provided, the description carries the transparency burden. It discloses that extraction targets the main forecast container and removes noise like ads, links, and UI strings. It does not explicitly state whether the operation is read-only or whether it could fail, but the described behavior is reasonably transparent.

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 two concise sentences. The first states the purpose directly; the second adds necessary precondition and behavioral detail. No fluff or redundant wording.

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 description fully covers what the tool does, when it should be used, and what behavior to expect. Since the output schema exists, return format details are not required. The precondition and cleaning behavior make it complete for an agent to invoke correctly.

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 is empty with zero parameters, so the baseline is 4. There are no parameters for the description to explain, and no additional parameter details are needed.

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 clearly states the tool's action ('extract and clean') and target ('visible forecast text from the current page'). It distinguishes itself from sibling tools by specifying that it operates after a forecast page is already loaded, complementing open/search/select actions.

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 explicitly states the precondition: a forecast page must already be loaded, specifically after select_weather_forecast_city_israel. This gives clear when-to-use guidance, though it does not explicitly compare against alternatives beyond that contextual reference.

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