ask-user

Collects structured user input via predefined questions and options for AI workflows.

56|12|Updated Apr 26, 2026
One-click install
npx skills add https://github.com/Neuron-Mr-White/UniPi --skill ask-user-neuron-mr-white
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ask-user
Source: https://github.com/Neuron-Mr-White/UniPi/tree/main/packages/ask-user/skills/ask-user
Command: npx skills add https://github.com/Neuron-Mr-White/UniPi --skill ask-user-neuron-mr-white

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

The ask-user skill addresses the need for a structured and interactive approach to gather user input, especially for high-impact or ambiguous decisions, without interrupting the workflow.

Core Features & Use Cases

  • Structured User Input: Collects data in a structured manner through predefined questions, multiple-choice options, and freeform responses.
  • Decision Support: Assists in making informed decisions by providing a clear interface for user confirmation and feedback.
  • Workflow Integration: Seamlessly integrates into larger workflows, allowing agents to proceed with certainty based on user input.

Quick Start

To ask a simple yes/no question, use: ask_user(question: "Do you want to proceed?", options: [{label: "Yes", value: "yes"}, {label: "No", value: "no"}]).

Frequently Asked Questions about ask-user

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add user confirmation steps to an AI workflow?▼

The ask-user skill facilitates structured user input for AI workflows by collecting data through predefined questions, multiple-choice options, and freeform responses, enabling explicit decision-making and validation steps without interrupting the overall process.

What is structured user input in AI interaction?▼

Structured user input in AI interaction is a method of collecting data through predefined questions, multiple-choice options, and freeform responses to support explicit decision-making and validation steps within automated workflows.

When do I need decision gates for ambiguous requirements?▼

You need decision gates for ambiguous requirements when handling high-impact scenarios like architectural trade-offs or user preferences, ensuring explicit user interaction and input validation before the AI agent proceeds with certainty.

How do I collect multiple-choice responses from users during an AI task?▼

You collect multiple-choice responses by defining a question with labeled options, such as `ask_user(question: "Do you want to proceed?", options: [{label: "Yes", value: "yes"}, {label: "No", value: "no"}])`, to capture explicit user decisions.

Can I use structured user input for architectural trade-offs and user preferences?▼

Yes, structured user input is ideal for architectural trade-offs and user preferences, providing a clear interface for user confirmation and feedback so agents can proceed with certainty based on validated data.

Does user input validation require explicit interaction to proceed?▼

Yes, user input validation requires explicit user interaction, ensuring that high-impact or ambiguous decisions are confirmed by the user before the AI workflow proceeds with the next steps.