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Glama

desktop

Get a semantic snapshot of the Hyprland desktop, listing monitors, workspaces, windows with geometry and addresses, active window, cursor, and layers. Call this first to obtain targets for actions.

Instructions

Semantic desktop snapshot: monitors, workspaces, windows (address, class, title, at + size in global coords), active window, cursor, and layers: launchers (wofi/rofi), bars, notification popups, and on-screen keyboards are NOT windows and appear only there, with a best-effort kind and global geometry you can screenshot by region or click into. A listed layer is one the compositor tracks, not one you can see: it may be transparent or dormant, so screenshot when visibility matters. Call first; act on the addresses it returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.11.0

TDQS

A4.9/5.0
Behavior5/5

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

Since no annotations are provided, the description carries the full burden. It reveals important behavioral nuances: layers are not windows and may be invisible, and the snapshot returns geometry for screenshotting or clicking. It also notes that 'a listed layer is one the compositor tracks, not one you can see,' which is critical for correct interpretation. This is rich, non-obvious context beyond what a schema could convey.

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 concise but information-dense. It front-loads the core purpose ('Semantic desktop snapshot') and then provides necessary details about layers and action points without fluff. Every sentence adds value: the layer clarification, the visibility caveat, and the directive to call first. The structure is logical, progressing from what, to nuances, to usage.

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?

Given the tool's complexity (snapshot of multiple desktop elements) and the absence of annotations, the description provides sufficient detail for correct invocation and interpretation. It explains the distinction between windows and layers, mentions best-effort 'kind' for layers, and advises on screenshot when visibility matters. The output schema likely details the return format, so the description complements it well.

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

Parameters4/5

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

The tool has zero parameters, so the description adds value by explaining what the output contains (the snapshot details). Even though there's no parameter to document, the description clarifies the structure of the returned data, which is essential for the agent. Since there are no parameters, the description complements the lack of input schema with domain context.

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 clearly states that this tool takes a semantic snapshot of the desktop environment, enumerating specific entities (monitors, workspaces, windows, active window, cursor) and their properties (address, class, title, geometry). It distinguishes itself from siblings like 'screenshot' and 'click_ui' by emphasizing the returned addresses and the semantic layer, making its purpose unambiguous.

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?

Explicit instructions are given on when to use this tool: 'Call first; act on the addresses it returns.' It also provides guidance on handling layers, noting that they may be transparent or dormant, and advises to screenshot when visibility matters, which helps the agent decide between using this snapshot tool versus a screenshot tool.

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