GH-AWTrace：GitHub 智能体工作流执行日志大规模数据集
GH-AWTrace: A Large-Scale Dataset of GitHub Agentic Workflow Execution Logs
Jasem Khelifi, Hao Li, Ali Ouni, Mohammed Sayagh, Mohamed Aymen Saied
AI 速读 基于摘要
作者构建并发布了一个将 GitHub 智能体工作流与其运行记录和执行日志关联起来的大规模数据集，用于研究工作流执行过程。
cs.SE
查看原文摘要
Agentic workflows enable AI agents to perform recurring repository tasks on schedules or in response to repository events. Existing studies examine workflow definitions and outputs, but provide limited evidence of what happens during execution. We present GH-AWTrace, a dataset linking 25,014 verified GitHub Agentic Workflows across 5,051 repositories to 4,112,526 run records and 562,877 nonempty execution log archives. The dataset preserves execution evidence subject to GitHub's log-retention limits and links it to repository metadata and generated workflow configurations. Illustrative cases show how the logs expose tool denials, provider failures, changes in an agent's approach, and delegation among agents. These observations enable research on execution failures, tool use, and the relationship between reported run outcomes and visible task progress. Coverage varies across workflows, and the logs provide partial observations rather than complete agent trajectories. Video: https://youtu.be/KIlfmZhHxtA