Show HN: An open Add/Search evaluation framework for agent memory (agentmemoryleaderboard.ai)

The Agent Memory Challenge has announced its second public evaluation cycle, focusing on benchmarking AI agents' memory capabilities across textual, coding, and multimodal tasks. Participants, including researchers and commercial teams, are required to host their own Add/Search APIs, enabling a fair comparison of memory systems. The evaluation framework will assess long-context memory, multi-session interactions, retrieval capabilities, and more, while maintaining detailed metric breakdowns and public rankings. This initiative is significant for the AI/ML community as it establishes a standardized approach to evaluate and improve agent memory systems, which are crucial for tasks involving persistent knowledge and contextual understanding. The challenge promotes transparency and competition, offering a total prize pool of RMB 150,000 for top-performing entries in each memory track. Participants will go through a rigorous submission process, ensuring that only those with stable APIs and detailed evaluation protocols will be featured in the public leaderboard, enhancing the reliability of comparisons in this growing field.