get_screen_sizeReturn the main screen dimensions in points (width, height) to determine click coordinates for GUI automation.
Return the main screen size in points (width, height) — use it to reason about click coordinates.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the qualifier 'main screen' (implying it ignores secondary displays) and the unit 'points', which are useful behavioral details beyond annotations. However, it doesn't disclose the exact return structure (e.g., object vs tuple), so it does not fully exceed annotation coverage.
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 that states the action, result, and use case with no wasted words. It is highly efficient and immediately actionable.
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 zero-parameter, read-only tool with annotations covering safety, the description is complete. It specifies what is returned (width and height in points) and why to use it, which is all an agent needs to invoke it correctly. No output schema exists, so the description's mention of the result format suffices.
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 schema trivially covers 100% of them. Per the rubric, a baseline of 4 applies for 0-parameter tools. The description does not need to explain parameters, and it doesn't introduce any ambiguity.
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 ('Return') and resource ('main screen size'), and specifies the output format ('in points (width, height)') along with a clear use case ('to reason about click coordinates'). This distinguishes it from sibling tools like get_clipboard or system_info, which serve different purposes.
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 gives a concrete use case ('use it to reason about click coordinates'), indicating when to invoke it. It does not explicitly name alternatives or exclusions, but the tool is unique among siblings and its purpose is clear, so a score of 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.