Developer Builds 'Judgment Loop' Tool to Prevent AI From Confidently Answering the Wrong Question

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A developer has released an open-source agent skill called Judgment Loop, designed to address a subtle but critical flaw in AI systems: producing confident, well-structured answers before the actual problem is properly defined. The tool acts as a reasoning guardrail that routes AI responses through five modes — Quick, Decision, Research, Learning, and Review — each tailored to the stakes and uncertainty of a given query. Rather than generating recommendations outright, Judgment Loop prompts the AI to identify what reality needs to change, flag unverified assumptions, and propose the cheapest test to challenge its own conclusions. The skill is intentionally proportional, reserving its full analytical process for high-consequence or uncertain decisions while keeping simpler tasks lightweight. Released under an MIT-0 license, the project includes a runtime file, worked examples, evaluation cases, an OpenAI agent interface, and a Simplified Chinese translation.

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