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GiantBeaver9

mcp-pop-up

by GiantBeaver9

ask_user

Ask the user for guidance by displaying a desktop pop-up with a question and optional multiple-choice answers, returning their selection or free-text input.

Instructions

Ask the user for guidance via a desktop pop-up and return their answer.

Use this whenever you need a decision, clarification, or direction from the person you are helping instead of guessing. A native window appears with your question and buttons for each answer. An "Other" choice with a free-text box is always added, so the user is never boxed in by your options.

Args: question: The question to show the user. Be specific and self-contained. options: Up to 6 suggested answers. May be empty to ask an open-ended question (the user then answers via the "Other" text box). allow_multiple: If True the user may select several answers (checkboxes); if False they pick exactly one (radio buttons). Default False.

Returns: A short human-readable summary of what the user chose, or a note that the prompt was cancelled.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
optionsNo
questionYes
allow_multipleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully discloses behavior: a pop-up appears, an 'Other' option is always added, and the return is a summary or cancellation note. It also explains UI behavior based on parameters (radio vs checkboxes). This is comprehensive and transparent.

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 yet complete, with a clear structure: a one-sentence summary, a usage note, then a bulleted Args/Returns section. Every sentence adds value, and the information is front-loaded.

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 has 3 parameters, no annotations, and an output schema exists (though not provided), the description covers all necessary aspects: purpose, usage, parameter details, and return value. There are no gaps in context for selecting and invoking this tool.

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

Parameters5/5

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

The input schema only provides names and types (0% coverage), but the description adds valuable semantics: question should be specific and self-contained, options can be up to 6 or empty for open-ended questions, allow_multiple controls checkbox vs radio behavior. This fully compensates for the schema's lack of descriptions.

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 action ('ask the user for guidance via a desktop pop-up') and the resource (the user's answer). It is specific and distinguishes this from guessing, which is the only alternative mentioned. No siblings exist, so differentiation is not required.

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?

Explicitly states when to use: 'whenever you need a decision, clarification, or direction from the person you are helping instead of guessing.' It does not specify when not to use, but given no sibling tools and a clear purpose, this is sufficient. A slight gap in exclusion criteria prevents a 5.

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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