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 does disclose that the tool waits for the dropdown to appear and returns a success or error message. However, it omits important details such as prerequisites (e.g., the page must be open), what happens if the dropdown never appears, and whether the action has side effects beyond entering text.

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 concise and well-structured with Args and Returns sections. It avoids redundancy and is appropriately sized for a tool with a single parameter. The only minor issue is a slight redundancy between the stated returns and the presence of an output schema, but overall it is efficient.

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 one parameter, the description covers the basic action and result, but it lacks workflow context. It does not mention that this is part of a sequence (open → enter → select → get), nor does it specify preconditions such as the search field being visible or the page having been opened. The dropdown appearance condition is stated, but failure modes and prerequisites are lacking.

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 description coverage is 0%, so the description must compensate for the parameter. The Args section adds only a minimal explanation ('Name of the city to search for'), which adds little beyond the schema title 'City Name'. It does not specify acceptable formats, the Israeli city context, or that the input should match a dropdown option.

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 ('Enters city name in the search field') and the resource being acted upon, and it waits for a dropdown. This specific verb+resource structure distinguishes it from sibling tools like 'open,' 'select,' and 'get content,' which represent different actions in the workflow.

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 provides no explicit guidance on when to use this tool versus alternatives. It does not mention that it should follow 'open_weather_forecast_israel' or precede 'select_weather_forecast_city_israel'. The usage context is only implied by the tool name and sibling list, not stated in the description.

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

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 mentions the return value (cleaned text or error) but does not disclose side effects, safety (read-only), or any operational constraints such as the need for a loaded page. This leaves significant behavioral ambiguity.

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 sentences with no redundancy. It front-loads the core purpose and includes a return-value note. 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?

The tool has no parameters and a plausible output schema, and the description states the return behavior. However, it lacks workflow context: it does not explain how it fits with the sibling tools or what conditions must be met before invoking it (e.g., page must be open). This leaves a gap for an agent deciding when to call it.

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?

There are zero parameters in the input schema, and schema coverage is 100% (empty). No parameter explanation is needed, and the baseline for zero parameters is 4. The description adds no param semantics, but none are required.

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 ('extracts and cleans') and identifies the resource ('weather forecast content from the page'), clearly distinguishing it from siblings like open/enter/select weather forecast tools. It is concise and unambiguous.

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?

There is no guidance on when to use this tool or how it relates to the sibling tools. It does not mention prerequisites (e.g., 'after opening the page') or explicitly tell the agent when to prefer this over alternatives. The phrase 'from the page' implied a precondition but is not made explicit.

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

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

With no annotations provided, the description must disclose the tool's behavior itself. It does state that it opens a browser and navigates, and describes the success/error outcomes. However, it lacks any additional behavioral context such as prerequisites (e.g., GUI environment), network reliance, or potential side effects beyond opening the browser. This meets the minimum viable standard but does not go further.

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 extremely concise: one sentence describing the action and a clear 'Returns' section. Every word earns its place, with no redundancy or extraneous information. The structure front-loads the primary purpose immediately.

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 (per context signals), the description covers all essential information: what the tool does and the possible return states. It does not need to explain return values in detail because the output schema presumably handles that. The description is fully adequate for the tool's simplicity.

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, so the input schema is empty. The description correctly adds no parameter information, and the baseline for tools with no parameters is 4. There are no parameter semantics to clarify, so the score reflects that the description appropriately handles the absence of parameters.

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: 'Opens browser and navigates to Israeli weather forecast site.' The verb 'opens' and specific resource ('Israeli weather forecast site') distinguish it from sibling tools that enter/select city or get content, making the purpose unambiguous.

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 provides no guidance on when to use this tool versus the sibling tools (enter_weather_forecast_city_israel, select_weather_forecast_city_israel, get_weather_forecast_content_israel). It simply describes the action, leaving the agent to infer that this is likely the initial step, but no explicit 'when' or alternative guidance is given.

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

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

With no annotations to rely on, the description carries the full burden. It discloses that only the first dropdown item is selected, that it waits for page load, and that it returns a success message with the city name or an error. This is transparent enough for a simple UI action, though it omits any mention of state prerequisites or potential side effects.

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 concise: two sentences plus a return line. Every sentence contributes meaningful detail (action, wait behavior, return format) without redundancy or filler.

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 simple zero-parameter UI action, the description fully explains what the tool does and what it returns. It does not explicitly mention dependencies on earlier steps (e.g., entering a city) or the context of the dropdown, but proximity to siblings and the tool name make these inferable, and the output schema further covers return details.

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?

There are zero parameters, and the input schema is empty, so the baseline is 4. The description correctly avoids inventing parameter details and its mention of 'first item' and the return message is sufficient context for this parameterless tool.

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 selects the first item from the dropdown and waits for the forecast page to load. The specific verb 'selects' and resource 'weather forecast city' combined with the unique behavior ('first item', 'waits') distinguishes it from sibling tools like open, enter, and get 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?

No guidance is provided about when to use this tool versus alternatives. The description does not mention prerequisites, sequencing, or exclusionary cases, leaving the agent to infer usage solely from the tool's name and sibling context.

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