A replayable A2A jury for tracing how agents influence decisions
Build autonomous Python agents with native Agent-to-Agent (A2A) communication - protolink/examples/ai_courtroom at main · nMaroulis/protolink
In plain words
A replayable jury simulation tool that places autonomous Python agents inside a fictional liability tribunal to observe how they communicate and influence each other's decisions. Built on ProtoLink, it demonstrates Agent-to-Agent communication by running deterministic cases offline and generating JSON results, execution traces, public transcripts, and interactive HTML reports. Designed for developers and researchers studying multi-agent interaction and decision-making processes.
written from the facts on this page · September 2026
From the sources
Can AI agents talk themselves into a better answer, or a worse one? This ProtoLink showcase puts autonomous agents inside a fictional liability tribunal and makes their communication observable. The case is memorable, but the case is not the product. The product is the interaction: The default run is deterministic and offline. It produces JSON results, ProtoLink traces, a public transcript, and standalone interactive HTML reports. Everything and everyone in this example is fictional. It is a software experiment, not legal analysis, legal advice, or a validated safetyfrom github.com
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