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matthewdcage

macOS Automation MCP Server

by matthewdcage

choose_from_list

Displays a list selection dialog for users to choose one or multiple items, with optional custom title and prompt for context.

Instructions

Show a list selection dialog.

Args: items: List of items to choose from title: Dialog title prompt: Optional prompt message multiple: Allow multiple selections

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes
titleNoChoose an item
promptNo
multipleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are present, so the description must disclose behavioral traits. It only says 'Show a list selection dialog' and does not mention blocking behavior, cancellation semantics, return value flow, or whether multiple selections affect interaction. This is a significant gap.

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 and front-loaded with the core statement. The Args list is well-structured and adds value without unnecessary prose. Every sentence and item earns its place.

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

Completeness3/5

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

Given the tool's simplicity and the presence of an output schema, some details (like return format) are covered by structured data. However, the description omits critical behavioral context such as whether the dialog blocks, how selections are returned, and what happens on cancel. This makes it only minimally complete.

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?

Although schema coverage is 0%, the description's Args section adds practical meaning to each parameter (e.g., 'items: List of items to choose from', 'prompt: Optional prompt message'). This compensates for the bare schema and helps an agent understand parameter usage.

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

Purpose4/5

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

The description clearly states 'Show a list selection dialog' with a specific verb and resource. It distinguishes itself from sibling tools, which are system/file/task utilities, by focusing on user interaction. However, it does not explicitly mention what the tool returns, leaving some purpose ambiguity.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention exclusions or context. The usage is only implied by the name and the one-line description, which is insufficient for an agent deciding between this and other tools.

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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