asking-questions

Solid

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.

Web & Frontend 134 stars 7 forks Updated today MIT

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Skill Content

# 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: 1. **Ambiguous implementation choices** - Multiple valid technical approaches (middleware vs wrapper functions, library selection, architectural patterns) 2. **Missing critical context** - Specific information needed (database type, deployment platform, credential management) 3. **Potentially destructive actions** - Requests that could be interpreted dangerously ("clean up files" = delete vs archive) 4. **Scope clarification** - Vague terms like "refactor," "optimize," or "improve" 5. **Conflicting requirements** - Goals that may work against each other ("make it faster" + "add extensive logging") 6. **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 ...

Details

Author
oaustegard
Repository
oaustegard/claude-skills
Created
9 months ago
Last Updated
today
Language
Python
License
MIT

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