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game_mouse

Control the mouse at normalized screen coordinates to click, move, drag, or scroll, enabling interaction when UI tree inspection fails.

Instructions

Move or click the mouse at normalized screen coordinates.

x/y are 0..1 with the origin at the top left -- exactly the numbers printed on a game_observe(grid=True) capture, so you can read a target off the image and pass it straight in. They are converted to pixels here using the game's real resolution.

action: click, down, up, double, move, setpos, wheel button: L, M, R, T1, T2

This is the fallback that works regardless of how the game builds its UI, when game_ui_click cannot see the widget tree.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xNo
yNo
gridNo
wheelNo
actionNoclick
buttonNoL
observeNo
show_uiNo
durationNo
max_sizeNo
Behavior3/5

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

With no annotations, the description must carry behavioral burden. It does explain the normalized coordinate system and pixel conversion, plus the available actions/buttons. However, it omits any mention of side effects (e.g., whether this moves the OS cursor vs. simulated game input), the effect of 'observe'/'duration', or failure modes. The core behavior is described, but not comprehensively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured logically: first the operation, then the coordinate details, then the parameter lists, then usage context. Every sentence adds information, with no fluff. It could be slightly condensed, but the length is justified given the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a 10-parameter tool with no output schema and no annotations. The description explains only the essential core (x/y and action/button) but leaves many parameters undefined, no return value description, and no explanation of how 'observe' or 'show_ui' affect output. An agent would likely struggle to invoke this correctly for anything beyond basic clicks.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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. It explains x/y normalization and lists action/button values, covering only 4 of the 10 parameters. Parameters like grid, wheel, observe, show_ui, duration, and max_size are entirely unexplained, leaving significant ambiguity for an agent trying to use them correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb ('Move or click') and resource ('the mouse'), and immediately distinguishes itself from the sibling tool 'game_ui_click' by positioning itself as the fallback for when the widget tree is unavailable. This explicit differentiator prevents confusion in tool selection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The final sentence clearly defines when to use this tool: 'when game_ui_click cannot see the widget tree.' It also explains the coordinate system and conversion, giving enough context for an agent to decide between this and alternatives. The 'when-not' is implied by the fallback framing.

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

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