zby/llm-do/ask-questions-if-underspecified

Claude Code and agent skill by zby/llm-do

Trust tier 3
  • community
Source check pending

Checking that the SKILL.md file is still in the repository.

Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.

Install

npx vskill@latest install zby/llm-do/ask-questions-if-underspecified

SKILL.md

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
1) Scope?
a) Minimal change (default)
b) Refactor while touching the area
c) Not sure - use default
2) Compatibility target?
a) Current project defaults (default)
b) Also support older versions: <specify>
c) Not sure - use default
Reply 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.

Security

  • Security scanPassed, 98 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

7-day trend score
0

Not refreshed yet.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex
  • Gemini CLI
  • Cline
  • Amp
  • Roo Code
  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
Embed badge
vskill VERIFIED badge
[![vskill VERIFIED](https://verified-skill.com/api/v1/skills/zby/llm-do/ask-questions-if-underspecified/badge)](https://verified-skill.com/skills/zby/llm-do/ask-questions-if-underspecified)

Something wrong with this skill or its page? Tell us.