asking-questions
Skill158 starsChanged 8 months agoMITView on GitHub
Guidance for asking clarifying questions when user requests are ambiguous, have multiple valid approaches, or require critical decisions. Use when implementation choices exist that could significantly affect outcomes.
1 other project uses a version of this.
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- timmo001/skillstheir own version, first seen Nov 7, 2026
Other versions1 project uses a version of this.
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Wrote their own version · 1
- timmo001/skills★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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- CLAUDE.mdCLAUDE.md
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The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Ask clarifying questions when the answer materially changes what you'll build.
- Distinctive: line 27
Don't ask when:
- Distinctive: line 109
Proceed immediately: - Don't ask if they want you to continue
- Distinctive: line 110
Apply preferences: - If they chose "security first" once, lean that direction for similar future choices
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Asking Questions
Purpose
Ask clarifying questions when the answer materially changes what you'll build. This skill helps identify when to ask, how to structure questions effectively, and when to proceed autonomously.
When to Use
Ask questions for:
- Ambiguous implementation choices - Multiple valid technical approaches (middleware vs wrapper functions, library selection, architectural patterns)
- Missing critical context - Specific information needed (database type, deployment platform, credential management)
- Potentially destructive actions - Requests that could be interpreted dangerously ("clean up files" = delete vs archive)
- Scope clarification - Vague terms like "refactor," "optimize," or "improve"
- Conflicting requirements - Goals that may work against each other ("make it faster" + "add extensive logging")
- Technical trade-offs - Solutions with different costs/benefits depending on priorities
When NOT to Use
Don't ask when:
- Request is clear and unambiguous - One obvious implementation path
- You can determine the answer from context - Codebase patterns, project structure, existing conventions
- Over-clarification - Questions that don't materially affect implementation
- Standard engineering practices - Established patterns already in the codebase
Question Structure
Template
[Context: What you found/analyzed]
[Present 2-5 specific options with brief trade-offs]
[Direct question asking for preference]
[Optional: Offer to make reasonable default choice]Guidelines
- Acknowledge understanding first - Show you've analyzed the situation
- "I found your API endpoints and see you're using Express..."
- Present clear options - Offer 2-5 specific choices with brief context
I can implement this in several ways: 1. **Global middleware** - Catches all errors centrally (simplest) 2. **Wrapper functions** - More granular control per endpoint 3. **Custom error classes** - Typed errors with status codes - Ask directly - Clear question that guides decision
- "Which approach fits your needs?"
- Offer autonomy (optional) - For less critical decisions
- "I can implement option 2 as it's the safest, or let me know if you prefer something else."
Progressive Disclosure
Layer questions instead of asking everything upfront:
Good ✓
- First: "For real-time updates, should I use WebSockets, Server-Sent Events, or polling?"
- Then: "For WebSockets, do you want Socket.io (easier) or native (lighter)?"
Bad ✗
- "For real-time updates should I use WebSockets or SSE or polling and if WebSockets should I use Socket.io or native and should I implement reconnection and what about authentication and..."
Examples
Good ✓
"I see you're using JWT authentication. To add refresh tokens, I can:
- httpOnly cookies - More secure, harder to XSS
- localStorage - Simpler, works with mobile apps
- In-memory only - Most secure, lost on refresh
What works best for your use case?"
Bad ✗
"How should I implement the authentication refresh token storage mechanism considering security implications, XSS vulnerabilities, mobile compatibility, UX impacts, and compliance considerations?"
Too verbose, no clear options, asks everything at once
Good ✓
"You mentioned 'clean up migrations.' Do you want me to archive them to /old-migrations or delete them entirely? (Note: deletion can break databases that haven't run them yet)"
Bad ✗
"What do you mean by clean up?"
Too vague, doesn't guide the decision
After Receiving an Answer
- Acknowledge - Confirm you understood their choice
- Proceed immediately - Don't ask if they want you to continue
- Apply preferences - If they chose "security first" once, lean that direction for similar future choices
Key Principle
Ask only when the answer materially changes what you'll build. Avoid building the wrong thing, not asking questions for the sake of asking.
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