AI Answer Reality Checker

The problem

AI answers can sound confident, detailed, and complete even when important claims are unsupported, outdated, inferred, or simply wrong. Fluency can make weak information feel more trustworthy than it is.

What it does

• Separates factual claims from inference, interpretation, prediction, and recommendation.
• Flags unsupported specificity, hidden assumptions, missing context, and possible hallucination risk.
• Identifies claims that depend on current information and should be independently verified.
• Checks whether confidence matches the available evidence.
• Traces the cost if a weak claim is wrong, including financial, legal, health, relationship, or reputational consequences.
• Shows what new evidence would strengthen, weaken, or overturn the answer.

Why use this skill

General-purpose AI can produce persuasive answers faster than users can verify them. This skill is designed to slow that process down where it matters. It does not assume AI is wrong; it distinguishes what has earned confidence from what merely sounds convincing.

Use cases

• Checking a ChatGPT, Claude, Gemini, or other AI response before acting on it.
• Auditing business, career, legal, financial, technical, or health-related AI claims.
• Testing whether an AI relationship or workplace interpretation is evidence-based or overly validating.
• Finding which parts of a long AI answer actually need external verification.
• Comparing a revised AI response after the model has been challenged.

Known limitations

This skill can evaluate reasoning and claim quality from the information provided, but it cannot independently verify every external fact without access to appropriate sources. High-stakes medical, legal, financial, tax, immigration, or safety claims should still be checked with qualified sources or professionals.