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dzulfiikar

human-loop-mcp

by dzulfiikar

show_confirmation_dialog

Prompt a human operator to confirm or cancel an action via a browser dialog, enabling human-in-the-loop approval for AI agent tasks.

Instructions

Ask the user to confirm or cancel an action in the browser.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
messageYes
cancel_labelNo
confirm_labelNo
Behavior2/5

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

No annotations are provided, so the description carries full burden. It does not disclose whether the dialog is blocking, what it returns, if it requires user interaction, or any side effects. The description only states it 'asks', lacking essential behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence (8 words), front-loading the core purpose. It is efficient with no fluff, though it sacrifices depth for brevity.

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

Completeness2/5

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

Given 4 parameters, no output schema, and no behavioral annotations, the description is incomplete. It does not explain return values, prerequisites, or how the dialog interacts with the browser (e.g., blocking nature). Agent lacks critical info for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0%, and the description adds no information about parameters (title, message, cancel_label, confirm_label). While parameter names are somewhat self-explanatory, the description does not clarify their roles or link them to the dialog behavior, leaving a gap.

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 the tool's action: asking the user to confirm or cancel an action. It uses a specific verb ('Ask') and resource ('confirm or cancel'), distinguishing it from sibling tools like 'get_user_input' (open text) or 'get_user_choice' (multiple options).

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?

No explicit guidance on when to use this tool versus alternatives. The description implies it is for binary confirmations, but does not mention when not to use it or how it differs from sibling tools like 'show_info_message' or 'get_human_loop_prompt'.

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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