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lowlevel-computer-use-mcp

mouse_click

Click a mouse button at exact coordinates or on background windows without focus disruption. Supports double-click and multi-click with configurable intervals.

Instructions

Click a mouse button, optionally at a specific coordinate.

Use clicks=2 for a double-click. If x/y are omitted the click happens at the current cursor position.

BACKGROUND TARGETING: set hwnd or window_title to click a specific window WITHOUT bringing it to the foreground (Win32 PostMessage). In that mode x/y are client coordinates of the target window and the deepest child control at that point receives the click.

Args: params (ClickInput): position, button, click count, interval, optional target.

Returns: str: JSON describing the click that was performed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Beyond the annotations, the description discloses important behaviors: omitted x/y result in a click at the cursor, background targeting uses Win32 PostMessage without bringing the window to the foreground, and the deepest child control at the given client coordinate receives the click. This adds meaningful behavioral context beyond the minimal annotations.

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

Conciseness5/5

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

The description is compact and well-structured, with a clear main-action sentence, a background-targeting paragraph, and a brief Args/Returns section. Every sentence contributes useful information without redundancy.

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

Completeness5/5

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

For a tool with 10 parameters and two distinct targeting modes, the description plus the schema is highly complete. It covers the return format (JSON string), foreground vs background behavior, coordinate semantics, and leaves detailed parameter specifics to the schema, which is present and thorough.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description summarizes the params as 'position, button, click count, interval, optional target' and adds semantic notes about x/y omission and clicks=2. However, it does not mention display, instant_move, move_duration, or confirm_focus_disruption; the detailed nested schema descriptions carry that weight, so the description adds only marginal value over the schema.

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 opens with 'Click a mouse button, optionally at a specific coordinate', using a specific verb and resource that clearly distinguishes it from sibling tools like mouse_move, mouse_drag, and mouse_scroll. The background-targeting section further clarifies scope by introducing window handles/titles as alternative targets.

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

Usage Guidelines4/5

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

The description gives clear usage context: clicks=2 for double-click, omitting x/y for current cursor position, and using hwnd/window_title for background targeting. It does not explicitly name alternative tools for when-not-to-use, but the context is strong enough for an agent to infer appropriate usage.

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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