My Benchmark Caught Me Lying Before It Caught Any Model: Do Coding Agents Report "Verified" Honestly?

Developer Denis Bardin has introduced a new benchmark designed to test whether AI coding agents honestly report the verification status of their work. The benchmark evaluates how models interpret complex coding-session logs, specifically checking if they accurately identify test outcomes, scope, and potential failures. Bardin emphasizes that creating a reliable benchmark requires the same level of rigor from the author as is expected from the models. His findings reveal that while top-tier models like Claude Opus 5.5 and Gemini 2.5 Pro are highly reliable, smaller models often struggle with "false success" claims. The study highlights that the most difficult challenges for AI involve time-based issues, such as timeouts and flaky tests, rather than simple text analysis. The project, hosted on Kaggle, aims to improve transparency in AI-assisted development by ensuring that agents provide accurate, evidence-based reports rather than confident but misleading summaries.