ask-questions-if-underspecified — community ask-questions-if-underspecified, frontend-monorepo, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Perfect for Conversational Agents needing advanced clarification capabilities to avoid misinterpretation. All Mento UIs

mento-protocol mento-protocol
[0]
[0]
Updated: 3/5/2026

Agent Capability Analysis

The ask-questions-if-underspecified skill by mento-protocol is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for Conversational Agents needing advanced clarification capabilities to avoid misinterpretation.

Core Value

Empowers agents to generate targeted clarifying questions, ensuring accurate understanding of objectives and requirements through protocols like must-have questions and user-approved assumptions, thereby avoiding wrong work.

Capabilities Granted for ask-questions-if-underspecified

Automating requirements gathering
Debugging underspecified user requests
Generating minimum sets of clarifying questions

! Prerequisites & Limits

  • Requires natural language understanding capabilities
  • Dependent on user engagement for feedback and approval
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ask-questions-if-underspecified

Install ask-questions-if-underspecified, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with...

SKILL.md
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Ask Questions If Underspecified

Goal

Ask the minimum set of clarifying questions needed to avoid wrong work; do not start implementing until the must-have questions are answered (or the user explicitly approves proceeding with stated assumptions).

Workflow

1) Decide whether the request is underspecified

Treat a request as underspecified if after exploring how to perform the work, some or all of the following are not clear:

  • Define the objective (what should change vs stay the same)
  • Define "done" (acceptance criteria, examples, edge cases)
  • Define scope (which files/components/users are in/out)
  • Define constraints (compatibility, performance, style, deps, time)
  • Identify environment (language/runtime versions, OS, build/test runner)
  • Clarify safety/reversibility (data migration, rollout/rollback, risk)

If multiple plausible interpretations exist, assume it is underspecified.

2) Ask must-have questions first (keep it small)

Ask 1-5 questions in the first pass. Prefer questions that eliminate whole branches of work.

Make questions easy to answer:

  • Optimize for scannability (short, numbered questions; avoid paragraphs)
  • Offer multiple-choice options when possible
  • Suggest reasonable defaults when appropriate (mark them clearly as the default/recommended choice; bold the recommended choice in the list, or if you present options in a code block, put a bold "Recommended" line immediately above the block and also tag defaults inside the block)
  • Include a fast-path response (e.g., reply defaults to accept all recommended/default choices)
  • Include a low-friction "not sure" option when helpful (e.g., "Not sure - use default")
  • Separate "Need to know" from "Nice to know" if that reduces friction
  • Structure options so the user can respond with compact decisions (e.g., 1b 2a 3c); restate the chosen options in plain language to confirm

3) Pause before acting

Until must-have answers arrive:

  • Do not run commands, edit files, or produce a detailed plan that depends on unknowns
  • Do perform a clearly labeled, low-risk discovery step only if it does not commit you to a direction (e.g., inspect repo structure, read relevant config files)

If the user explicitly asks you to proceed without answers:

  • State your assumptions as a short numbered list
  • Ask for confirmation; proceed only after they confirm or correct them

4) Confirm interpretation, then proceed

Once you have answers, restate the requirements in 1-3 sentences (including key constraints and what success looks like), then start work.

Question templates

  • "Before I start, I need: (1) ..., (2) ..., (3) .... If you don't care about (2), I will assume ...."
  • "Which of these should it be? A) ... B) ... C) ... (pick one)"
  • "What would you consider 'done'? For example: ..."
  • "Any constraints I must follow (versions, performance, style, deps)? If none, I will target the existing project defaults."
  • Use numbered questions with lettered options and a clear reply format
text
11) Scope? 2a) Minimal change (default) 3b) Refactor while touching the area 4c) Not sure - use default 52) Compatibility target? 6a) Current project defaults (default) 7b) Also support older versions: <specify> 8c) Not sure - use default 9 10Reply with: defaults (or 1a 2a)

Anti-patterns

  • Don't ask questions you can answer with a quick, low-risk discovery read (e.g., configs, existing patterns, docs).
  • Don't ask open-ended questions if a tight multiple-choice or yes/no would eliminate ambiguity faster.

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is ask-questions-if-underspecified?

Perfect for Conversational Agents needing advanced clarification capabilities to avoid misinterpretation. All Mento UIs

How do I install ask-questions-if-underspecified?

Run the command: npx killer-skills add mento-protocol/frontend-monorepo. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for ask-questions-if-underspecified?

Key use cases include: Automating requirements gathering, Debugging underspecified user requests, Generating minimum sets of clarifying questions.

Which IDEs are compatible with ask-questions-if-underspecified?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for ask-questions-if-underspecified?

Requires natural language understanding capabilities. Dependent on user engagement for feedback and approval.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add mento-protocol/frontend-monorepo. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use ask-questions-if-underspecified immediately in the current project.

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