Show HN: Legal Action Boundary Eval for agentic legal workflows

Category: ai-ml

Tags: ai-safety, legal-tech, evaluation-framework

Score: 6.5/10 (Innovation: 7, Technical: 6, Documentation: 8, Utility: 5)

A public proxy evaluation suite for legal AI workflows that measures safety at the 'action boundary'—where AI systems execute high-impact legal decisions like accepting clauses or routing documents—rather than just assessing comprehension. It's interesting because it focuses on a critical, under-evaluated risk point in agentic systems by comparing a baseline against the 'VerifiedX' safety system across realistic negotiation and compliance scenarios.

Target audience: data engineers, backend devs

Repository: https://github.com/bigkan8/legal-action-boundary-eval · Python

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