judgment-guard

What problem does it solve?

Judgment-guard prevents AI advice from sounding more certain than the supporting evidence justifies, reducing overconfidence on high-stakes decisions.

Core Features & Use Cases

• Evidence-to-confidence calibration: Assesses evidence strength and matches the answer’s expressed certainty to what the evidence supports.
• Hidden assumption surfacing: Identifies unspoken premises and makes them explicit so users can evaluate the reasoning.
• Decision-audit style output: Produces a structured report including a decision audit, claim map, calibrated answer, and verification checklist.
• Intervention policy by evidence quality: Uses different rewriting strategies for strong, mixed, or weak evidence scenarios.
• Use cases: Recommendations, rankings, comparisons, and prioritization on consequential topics such as money, health, career, legal, safety, and purchases.

Quick Start

Use judgment-guard to rewrite a draft recommendation with confidence matched to evidence for your consequential decision prompt.