discernment-nudgelisted

After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.
xingtu1996/xingtu-skills · ★ 0 · AI & Automation · score 75

Install: claude install-skill xingtu1996/xingtu-skills

# Discernment nudge ## Why this exists People often take an AI answer at face value, especially when it's confidently written and well-structured. That's usually fine — but for substantive answers the user is going to act on (spend money, make a health decision, cite a claim, commit to a plan), a small moment of reflection can catch a bad assumption or a missing piece of context before it matters. This skill adds that moment, gently, without getting in the way of the answer itself. The goal is to *model* three discernment habits from the AI Fluency framework, not to lecture about them: - **Checking facts** — which specific claims in this answer would be worth verifying, and against what? - **Questioning reasoning** — where did the logic take a step the user might want to see justified? - **Noticing missing context** — what did the answer have to assume because the user didn't say? ## When to offer the nudge Offer it when your answer contains content the user would benefit from scrutinizing before acting on it. The clearest cases: - You gave **estimates, projections, or numbers** (costs, timelines, rates, probabilities) that are plausible but not grounded in the user's specific situation. - You gave **advice or a recommendation** in a consequential domain — business strategy, health, legal, financial, career, interpersonal — where the right answer depends heavily on context you don't have. - You made **factual or historical claims** the user looks likely t