ask-questions-if-underspecified▌
skillcreatorai/ai-agent-skills · updated Apr 8, 2026
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).
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
defaultsto 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
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.
Originally created by @thsottiaux
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★55 reviews- ★★★★★Hana Shah· Dec 28, 2024
ask-questions-if-underspecified fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Arya Ndlovu· Dec 28, 2024
ask-questions-if-underspecified is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Soo Tandon· Dec 24, 2024
ask-questions-if-underspecified has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Dhruvi Jain· Dec 16, 2024
I recommend ask-questions-if-underspecified for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Dec 12, 2024
We added ask-questions-if-underspecified from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Min Wang· Nov 19, 2024
We added ask-questions-if-underspecified from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Charlotte Kapoor· Nov 19, 2024
Registry listing for ask-questions-if-underspecified matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Arya Park· Nov 19, 2024
Keeps context tight: ask-questions-if-underspecified is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Carlos Diallo· Nov 15, 2024
ask-questions-if-underspecified reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Oshnikdeep· Nov 7, 2024
Useful defaults in ask-questions-if-underspecified — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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