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Glama

window_input_mode

Determine how a window receives input before posting to it, returning postmessage, uia, focused, or invalid to guide correct input delivery.

Instructions

Classify how a window receives input BEFORE posting to it: postmessage (classic Win32) | uia (WinUI/UWP: focus+SendInput fallback) | focused (already foreground) | invalid (dead window).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hwndYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the output categories, including the 'invalid (dead window)' case, and implies a read-only operation ('Classify') with no side effects. However, it does not explicitly state that it performs no mutation or that it requires a valid handle, though the 'invalid' output suggests handling of dead windows. This is adequate but not rich in behavioral detail.

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 a single, well-structured line with line breaks separating the classification options. It contains zero filler and front-loads the purpose and timing. Every word earns its place.

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

Completeness4/5

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

Given the tool's simplicity (one parameter, an output schema presumably describing the classification results), the description covers the essential context: when to use, what it returns, and edge cases (invalid). It could mention that it is read-only or requires a valid handle, but these are minor gaps for a classification tool.

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?

Schema description coverage is 0%, so the description must compensate. It implies that 'hwnd' refers to the window being classified, but does not explicitly define the parameter or its format. Since the tool name and description make the role of hwnd obvious, a 3 is appropriate, but explicit clarification would improve it.

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 uses a specific verb ('Classify') with a clear resource ('how a window receives input') and explicitly lists the four possible classification values. This makes the tool's purpose unambiguous and distinguishes it from siblings like window_post (which posts input) and focus_window (which focuses).

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 phrase 'BEFORE posting to it' provides clear temporal context, indicating this tool should be called before window_post. The classification values also imply decision logic, but no explicit exclusions or alternatives are mentioned. Still, the guidance is sufficiently clear for an agent to know when to use it.

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