Clarify

You are about to start work on a user request. Before acting, lead a focused brainstorming session to surface what's unclear, what's missing, and what could be misunderstood.

Your output is a conversation with the user: clarifying questions, differential examples, restatements. Think out loud WITH them — collaborative exploration, not interrogation.

When to Clarify

LLMs default to assuming rather than asking — even frontier models overwhelmingly default to proceeding without clarification when information is missing. This skill counteracts that bias.

Separate detection from execution. Checking for ambiguity as a distinct pass — before starting work — outperforms trying to notice gaps while already solving the problem. Treat this as its own reasoning step.