Despite a growing ecosystem of tools supporting Systematic Literature Reviews (SLRs), integrating them into user-friendly workflows remains challenging. The Streamlined Workflow for Automating Machine-Actionable Systematic Literature Reviews (SWARM-SLR) unified the tool annotation and provided a cohesive yet modular workflow, but faced scalability and usability issues. We introduce the SWARM-SLR AIssistant, a unified framework that combines the SWARM-SLR's structured methodology with an agent-based assistant that integrates research tools in a modular interface. The first SWARM-SLR stage is integrated, enabling conversational, LLM-guided support and persistent data storage. To address the tool assessment bottleneck, we propose a centralized tool registry that allows developers to annotate and register tools autonomously using a shared metadata schema. Preliminary evaluation shows improved usability, but challenges remain in balancing efficiency, accessibility, and transparency. Further development is needed to realize scalable SLR automation.

翻译：尽管支持系统性文献综述（SLR）的工具生态系统日益壮大，但将其集成到用户友好的工作流中仍具挑战。用于自动化机器可操作系统性文献综述的简化工作流（SWARM-SLR）统一了工具注释并提供了内聚且模块化的工作流，但在可扩展性和可用性方面存在问题。我们提出了SWARM-SLR AIssistant，这是一个统一框架，将SWARM-SLR的结构化方法与基于智能体的助手相结合，在模块化界面中集成研究工具。首个SWARM-SLR阶段已集成，支持基于对话的LLM引导式帮助及持久化数据存储。为解决工具评估瓶颈，我们提出集中式工具注册表，允许开发者使用共享元数据模式自主注释和注册工具。初步评估显示可用性有所提升，但在平衡效率、可访问性和透明度方面仍存在挑战。需进一步发展以实现可扩展的SLR自动化。