aif-grounded

To ensure AI responses are grounded with evidence, this skill enforces a strict reliability gate that only delivers final answers when confidence is 100/100 based on available evidence. It prevents guessing by flagging uncertain outputs and listing necessary evidence sources.

When evidence is incomplete for critical queries, the model returns a concise checklist of unknowns and prescribes a path to reach 100% confidence. It does not guess; instead, it notes exactly what is needed to fulfill the evidence-based certainty requirement.

Yes, you can use evidence-based verification for policy-critical or medical questions. This approach is specifically designed for high-stakes applicability where guessing is unacceptable, ensuring outputs are strictly backed by verified sources.

The model handles uncertainty by listing evidence sources and explicitly noting unknowns. It applies a confidence scoring mechanism that requires a 100/100 threshold based on available evidence before providing any final answer.

The best way to prevent AI guessing in high-stakes environments is to apply a strict reliability gate that blocks unverified outputs. This skill ensures only evidence-backed responses are delivered, flagging any uncertain outputs for review.

You need an evidence-grounded response system for high-stakes questions where evidence-based certainty is required, such as security, legal, medical, or policy-critical scenarios. It ensures outputs are strictly backed by verified sources rather than guesses.