代理说完成了，数据库不同意
ThinkingBox用后端终态和副作用评测Agent是否真正完成任务。
为什么重要
为开发者提供一种按真实后端状态评测Agent可靠性的方式。
阅读原文huggingface.co
AI 解读（根据原文生成）
Microsoft与Hugging Face的联合博客介绍ThinkingBox：它把Agent放在隔离的MCP工具会话中运行，并根据终端后端状态与留下的副作用评分，而不是只看最终回复或工具调用是否有效。文章称，该基准覆盖507个有状态业务工作流，每个任务在不同LLM模型上运行20次；还讨论一致性的代价，并说明可通过OpenEnv自行运行基准。
要点（AI 据原文整理，数字均已与原文核对）
- ThinkingBox runs an agent against isolated MCP tool sessions, then grades the terminal backend state and side effects it leaves behind.
- Across 507 stateful business workflows, each run 20 times against various LLM models, it grades agents on terminal backend state and side effects.
- In a common-set ablation covering 121,680 valid trials across 12 LLM models, 79,853 attempts failed the executable checks.
- Of those failures, 67.24% still terminated cleanly, invoked a state-changing tool, and reported no final tool error.
- Executable checks found wrong field values in 77.61% of them, unintended extra effects in 43.30%, and missing required effects in 25.36%.
- The example above is adapted from a benchmark task sandbox_external_retail_group1.py:test_case_ST003_006.
