Tencent WorkBuddy Bench: A Multi-Domain Coding-Agent Benchmark with Contamination-Resistant Task Construction
Authors: name: Tencent WorkBuddy Bench Team, name: Siqi Cai, name: Shaopeng Chen, name: Xiang Fei, name: Yong Mao, name: Zihan Xu, name: Zhiheng Lyu, name: Zhijian Shao, name: Yuchen Shi, name: Shuwen Zhang, name: Chaofan Qiu, name: Linjie Che, name: Xiaoxi Zhao, name: Feng Wu, name: Kai Zhang, name: Chaofan Zhu, name: Yubin Qi, name: Xiaoyun Liang, name: Peijie Dong, name: Yunhao Zhang, name: Yuanjie Zhu, name: Ling Jiang, name: Xianjun Zhang, name: Zhehang Chu, name: Anyuan Sang, name: Zhen Feng, name: Sen Nie, name: Shi Wu, name: Yuanzhen Xu, name: Xin Li, name: Ning Yang, name: Zhiqiang Dong, name: Hande Dong, name: Qiang Lin, name: Yi Liu, name: Yunsheng Wu, name: Ke Li, name: Xing Sun
Organization: Tencent

We introduce Tencent WorkBuddy Bench, a multi-domain evaluation suite for coding agents; this report documents its construction methodology, scoring protocol, and a cross-model leaderboard. At its core is a unified evaluation framework for constructing and running distribution-informed coding-agent tasks across four work domains - Code, Web, Office, and Security. Rather than adapting public issue text, every task is reverse-engineered from a real commit, pull request, or business scenario and rewritten as a short, colloquial, role-played request, so that a task's prompt is not recoverable by web-searching the underlying issue, pull request, or commit thread. Because the dataset is released openly - task directories, environment images, evaluation harness, tests, and reference solutions - contamination resistance rests on this construction together with dataset versioning rather than on secrecy. The four subsets - repository-level engineering, front-end development, office and business workflows, and red-/blue-team security - probe complementary facets of real work, each with its own verification style. All are packaged in a uniform task-directory format and run, under a uniform and reproducible protocol, on two agent harnesses (CodeBuddy Code and Claude Code); the full open release makes the benchmark reproducible end to end and directly auditable, since any third party can re-run each task and inspect its content. Because each subset uses a different scoring instrument, scores are not comparable across subsets and the suite reports no suite-wide average. We report a cross-model leaderboard across several model families.