AI-Output Verifier

AI is fluent, confident, and sometimes completely wrong — inventing facts, citations, and details in the same authoritative tone as the correct ones. That confidence is exactly what makes unverified trust dangerous. This checks a specific output: which claims are most likely wrong or fabricated, what genuinely needs independent verification, how to verify it, and the tells of hallucination — so you use AI's speed without inheriting its errors.

What This Skill Produces

• A risk read of the output — which specific claims are most likely to be wrong, outdated, or made up (facts, numbers, citations, names, recent events, specifics)
• Verify vs. low-risk split — what genuinely needs independent checking vs. what's low-stakes or self-evident, so you spend effort where it counts
• How to verify each — the concrete way to check the high-risk claims (a primary source, a second tool, a domain expert, testing it)
• The hallucination tells — the signs AI is likely fabricating (oddly specific citations, confident claims about recent/niche facts, plausible-but-unverifiable details)
• A verification habit — how to build appropriate checking into your AI use by default, scaled to the stakes (trust more for low-stakes, verify hard for high-stakes)

Required Inputs

Ask for these if not provided:

• The output — the AI response to check (paste it)
• What it's for — the stakes (a casual question vs. something you'll publish, decide on, or act on)
• The domain — factual/technical/legal/medical/current-events (some are far higher-risk for AI)
• What you'd do with it — trust it, act on it, share it, build on it