extract_weather_forecast_israel

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

With no annotations, the description carries the burden. It discloses that the tool reads the current page, returns clean markdown, and that defaults include current conditions plus three days of hourly forecast. It also explains the consequence of shrinking the window and parameter clamps. It doesn't mention error handling or exact output schema, but the output schema exists to cover that.

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 well-structured: a one-line action, then workflow context, then default behavior, then parameter details. Every sentence earns its place, and the warning about shrinking the window is concise yet impactful. No redundancy or fluff.

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 situates the tool in its workflow, explains the default return content, and specifies how parameters affect output. Since an output schema exists, return value details are covered. It also gives clear prerequisites (page open, after select step). No significant gaps.

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?

Schema coverage is 0%, but the description fully compensates. It explains each parameter's purpose ('Days of hourly forecast'), when to leave unset, and clamping ranges. It also adds strategic guidance: 'Shrinking the window costs you the data you are about to be asked about.' This is rich, actionable semantics beyond the bare schema.

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 starts with a specific verb-resource pair: 'Read the forecast off the page that is currently open, as clean markdown.' This clearly states what the tool does and distinguishes it from siblings like open_weather_forecast_israel or select_weather_forecast_city_israel by tying it to the current page and markdown output.

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?

It explicitly states when to use it: 'Call this after select_weather_forecast_city_israel.' It also tells the agent to call it with NO arguments and warns against shrinking the window, providing clear context. Parameter guidance ('Leave unset unless the user explicitly asks about several days ahead') further clarifies usage.

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