实验报告聚合 · Experiment Report Aggregator

它解决什么问题

团队进行了许多实验，但结果分散在工作表和文档中，这使得比较结果和提取决策变得困难。

这个技能做什么

• 将多个实验报告合并为一份结构化摘要。
• 提取结论、证据、风险和下一步行动。
• 建立跨实验的比较表。
• 标记丢失的数据并在得出结论之前询问它。

为什么比裸提示词强

它强制执行固定的聚合框架，因此您可以获得可比较的、可供决策的输出，而不是模糊的重写。

典型用例

• 跨冲刺整合 A/B 测试结果。
• 为利益相关者总结 ML 实验。
• 建立每周实验摘要。

局限

需要原始实验数据或注释作为输入；它本身不运行实验。

English · 英文介绍

The problem

Teams run many experiments, but results stay scattered across sheets and docs, making it hard to compare findings and extract decisions.

What it does

• Merges multiple experiment reports into one structured summary.
• Extracts conclusions, evidence, risks, and next actions.
• Builds a comparison table across experiments.
• Flags missing data and asks for it before concluding.

Why this beats prompting it yourself

It enforces a fixed aggregation framework so you get comparable, decision-ready output instead of a vague rewrite.

Use cases

• Consolidating A/B test results across sprints.
• Summarizing ML experiments for stakeholders.
• Building a weekly experiment digest.

Known limitations

Requires raw experiment data or notes as input; it does not run experiments itself.