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ask-questions-if-underspecified — how to use ask-questions-if-underspecified how to use ask-questions-if-underspecified, what is ask-questions-if-underspecified, ask-questions-if-underspecified alternative, ask-questions-if-underspecified vs clarification skills, ask-questions-if-underspecified install, ask-questions-if-underspecified setup guide, clarification techniques for AI agents, avoiding wrong work in AI implementation

v1.0.0
GitHub

About this Skill

Ideal for Conversational AI Agents like Claude or AutoGPT needing to clarify user requests and avoid misinterpretation. ask-questions-if-underspecified is a skill that enables AI agents to determine when a request is unclear and prompts them to ask necessary questions to clarify objectives and requirements.

Features

Identifies underspecified requests by exploring work requirements
Asks minimum set of clarifying questions to avoid wrong work
Delays implementation until must-have questions are answered or user approves stated assumptions
Treats requests as underspecified if objectives or requirements are unclear
Prompts AI agents to ask questions to define the objective and identify what should change or stay the same

# Core Topics

mento-protocol mento-protocol
[0]
[0]
Updated: 3/6/2026

Quality Score

Top 5%
33
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add mento-protocol/frontend-monorepo/ask-questions-if-underspecified

Agent Capability Analysis

The ask-questions-if-underspecified MCP Server by mento-protocol is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use ask-questions-if-underspecified, what is ask-questions-if-underspecified, ask-questions-if-underspecified alternative.

Ideal Agent Persona

Ideal for Conversational AI Agents like Claude or AutoGPT needing to clarify user requests and avoid misinterpretation.

Core Value

Empowers agents to identify underspecified requests and ask targeted clarifying questions, ensuring accurate implementation and reducing errors by leveraging objective definition and workflow efficiency protocols.

Capabilities Granted for ask-questions-if-underspecified MCP Server

Automating request clarification for complex tasks
Generating targeted questions for user confirmation
Debugging underspecified objectives to ensure correct outcomes

! Prerequisites & Limits

  • Requires clear user interaction protocols
  • Dependent on agent's ability to understand request context
Project
SKILL.md
3.5 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

[No tags]
SKILL.md
Readonly

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.

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