![[2510.03495] AgentHub: A Registry for Discoverable, Verifiable, and Reproducible AI Agents](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2510.03495] AgentHub: A Registry for Discoverable, Verifiable, and Reproducible AI Agents
Summary
AgentHub proposes a registry for AI agents that enhances discoverability, verifiability, and reproducibility, addressing gaps in current AI infrastructure.
Why It Matters
As AI agents proliferate, a structured registry like AgentHub is crucial for ensuring interoperability, trust, and governance. It aims to streamline agent discovery and evaluation, which is essential for fostering innovation and collaboration in AI development.
Key Takeaways
- AgentHub provides a registry layer for AI agents, improving discoverability and governance.
- It includes features like publish-time validation and an append-only lifecycle event log.
- The platform enhances trust and security through structured contracts and evidence.
- Initial results show improved retrieval accuracy using an LLM-as-judge recommendation pipeline.
- AgentHub aims to create a reliable ecosystem for reusable AI agents.
Computer Science > Software Engineering arXiv:2510.03495 (cs) [Submitted on 3 Oct 2025 (v1), last revised 26 Feb 2026 (this version, v2)] Title:AgentHub: A Registry for Discoverable, Verifiable, and Reproducible AI Agents Authors:Erik Pautsch, Tanmay Singla, Parv Kumar, Wenxin Jiang, Huiyun Peng, Behnaz Hassanshahi, Konstantin Läufer, George K.Thiruvathukal, James C. Davis View a PDF of the paper titled AgentHub: A Registry for Discoverable, Verifiable, and Reproducible AI Agents, by Erik Pautsch and 8 other authors View PDF HTML (experimental) Abstract:LLM-based agents are rapidly proliferating, yet the infrastructure for discovering, evaluating, and governing them remains fragmented compared to mature ecosystems like software package registries (e.g., npm) and model hubs (e.g., Hugging Face). Existing efforts typically address naming, distribution, or protocol descriptors, but stop short of providing a registry layer that makes agents discoverable, comparable, and governable under automated reuse. We present AgentHub, a registry layer and accompanying research agenda for agent sharing that targets discovery and workflow integration, trust and security, openness and governance, ecosystem interoperability, lifecycle transparency, and capability clarity with evidence. We describe a reference prototype that implements a canonical manifest with publish-time validation, version-bound evidence records linked to auditable artifacts, and an append-only lifecycle event log whose s...
