Automated summary
This skill enables an AI agent to ask clarifying questions before executing an ambiguous request to avoid incorrect work.
Strengths
- Reduces misinterpretation errors by soliciting essential details.
- Provides structured, compact options for easy user responses.
- Handles assumptions explicitly when the user wants to proceed without full answers.
- Saves time by eliminating unnecessary work branches through targeted questions.
Limitations
- May slow down initiation if questions are not well prioritized.
- Not suitable for trivial tasks where clarification is unnecessary.
- Relies on the user's ability to provide precise answers.
Best for complex, ambiguous, or multi-interpretation requests given to an AI agent.
Avoid for simple, well-defined, or urgent tasks where clarification would cause unnecessary delay.
Security analysis
SafeThe skill only provides conversational guidance for clarifying requirements; it contains no instructions to execute commands, access external resources, or perform any destructive or risky operations.
No concerns found
How this analysis is madeExamples
Implement user authentication for my web app.Add a search feature to the API.Refactor the database module to improve performance.Skill file:
name: ask-questions-if-underspecified description: Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.
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
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/ask-questions-when-underspecified-mrwakfty/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/ask-questions-when-underspecified-mrwakfty' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/ask-questions-when-underspecified-mrwakfty/download' --output '.skill-downloads/ask-questions-when-underspecified-mrwakfty/SKILL.md.part' && mv '.skill-downloads/ask-questions-when-underspecified-mrwakfty/SKILL.md.part' '.skill-downloads/ask-questions-when-underspecified-mrwakfty/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
This file does not provide a usable name/description header for this native procedure. It remains available to download and inspect; use the manual method below.
Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/ask-questions-when-underspecified-mrwakfty/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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