T1: A Tool-Oriented Conversational Dataset for Multi-Turn Agentic Planning

Large Language Models (LLMs) are impressive intelligent agents, but they frequently struggle with effective multi-step planning, particularly in multi-turn conversations involving dependencies between tool calls. To address this challenge, we introduce T1, a specialized tool-augmented conversational dataset designed to capture and manage these inter-tool dependencies across diverse domains. T1 enables rigorous evaluation of agents' ability to coordinate tool use, integrate short- and long-term memory, and supports dynamic replanning decisions. We will demonstrate results powered by T1-Agent, showcasing its ability to plan and reason in these complex, tool-dependent scenarios, ultimately setting a new standard for building reliable and sophisticated agentic workflows.