AI Process Manager

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get_taskbar

Read-only

Retrieve taskbar data as structured JSON: pinned and running apps with window titles, enabling AI agents to monitor processes without screenshots.

Instructions

Human view of the taskbar: pinned apps and running apps grouped with window titles.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_taskbar"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.5.0Jul 31, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare this as a safe, read-only operation (readOnlyHint: true, destructiveHint: false). The description adds valuable behavioral context by specifying the output structure (pinned apps, running apps, window titles) and the 'human' formatting aspect. It does not contradict the read-only hint, and it provides more concrete behavioral detail than the annotations alone.

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, front-loaded sentence that immediately states the purpose and key output details. Every word earns its place—no filler, no redundancy. It is an ideal length for the tool's simplicity.

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 simplicity (no parameters, no output schema), the description is fully sufficient for an agent to know what the tool returns and when to use it. It describes the taskbar's composition (pinned apps, running apps, window titles) sufficiently well within its context.

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, and the schema coverage is 100% (identical). Per the rubric, a baseline of 4 is appropriate since there are no parameter semantics to clarify. The description does not need to add parameter info because there are none.

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 identifies the resource (taskbar) and the specific content (pinned apps, running apps, grouped window titles). The term 'Human view' implies a user-friendly representation, distinguishing it from sibling tools like list_windows or get_ui_tree that serve different UI introspection purposes.

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

Usage Guidelines3/5

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

The description implies usage for obtaining a taskbar-centric view, but it does not explicitly state when to use this tool versus alternatives such as list_windows or get_ui_tree. There are no explicit exclusions, alternative tool names, or prerequisite conditions, so guidance is only inferred.

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