Clarify underspecified requests
SkillAI & modelsAsk the minimum clarifying questions before implementing when scope, constraints, or success criteria are unclear. Use when a request has multiple plausible interpretations, missing acceptance criteria, or ambiguous environment constraints.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Clarify underspecified requests skill
What this skill tells your AI
The instructions your AI receives, as published by charlieviettq/awesome-agent-skill in .claude/skills/clarify-underspecified/SKILL.md and read by ahel’s review.
When to use
- Multiple plausible interpretations exist.
- Objective, scope, constraints, or "done" criteria are missing.
- Quick read-only discovery cannot resolve the ambiguity.
When not to use
- Request is already specific enough to proceed.
- A short repo/config read answers the open questions.
Workflow
- Decide if the request is underspecified (objective, scope, constraints, environment, safety).
- Ask 1-5 questions max; prefer multiple-choice with a
defaultsfast path. - Separate need to know vs nice to know.
- Do not run mutating commands or commit to a detailed plan until must-have answers arrive.
- If the user asks to proceed without answers, state assumptions explicitly and get confirmation.
Question format
1) Scope?
a) Minimal change (default)
b) Broader refactor in the same area
c) Not sure - use default
Reply: defaults (or 1a 2b)
Anti-patterns
- Do not ask what a quick read of repo/docs already answers.
- Do not ask open-ended questions when a yes/no or A/B choice is faster.
Output
Restate requirements in 1-3 sentences (constraints + success criteria), then start work.
Signals
- GitHub stars
- 26
- Forks
- 9
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
clarify-underspecified- Source
- github.com/charlieviettq/awesome-agent-skill