Show HN: HermesBench – workflow reliability evals for personal AI agents (verkyyi.github.io)

HermesBench, a new evaluation tool for personal AI agents, has been released, aiming to benchmark complete configurations of the Hermes Agent rather than just individual models. This innovative platform assesses various aspects including prompts, models, tools, and safety. The initial public baseline score is 78.2 based on 27 recipes, with the option to inspect redacted traces. The evaluative approach emphasizes transparency, linking scoring outcomes to defined scenarios and methodology, highlighting its role as an initial baseline rather than a comprehensive leaderboard. The significance of HermesBench lies in its focus on reliability and practical utility in personal AI workflows. The tool encourages user-driven feedback on setup ease and scoring accuracy, aiming to enhance the benchmarking process. Its scoring philosophy asserts that effective agents should perform safely and efficiently, penalizing imbalances in capability and safety. Users are invited to contribute by sharing improved configurations or proposing new recipes, cultivating a collaborative environment for the development of personal AI technologies. With comprehensive coverage across everyday use cases like scheduling and communication, HermesBench positions itself as a vital resource in advancing the reliability of AI agents in real-world applications.