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Build agents that actually solve data problems using DataHub's metadata, lineage, governance and quality context. Four challenge categories; supports MCP and the Agent Context Kit.
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Describe a data incident in one sentence and the agent traces and proves the root cause in the DataHub graph, repairs the pipeline, verifies the fix and writes the result back to DataHub. Won first place overall.
Data tools rank problems by how broken something is. Paracelsus ranks them by how much harm can actually reach someone, then writes the verdict back into DataHub. The dose makes the poison.
When an upstream column is renamed, retyped or dropped, this agent uses DataHub's column-level lineage to find exactly what breaks, repairs the code, and ships the fix as a reviewed pull request.
The on-call agent that gets cheaper every time it runs: it files each postmortem inside DataHub, so the next incident starts from the last one. Measured: 20 tool calls cold, 15 warm.
A stack trace for model decay. Give it a degraded model and a vague complaint, and it walks DataHub's ML lineage to the column that broke it, prices the damage in dollars, and opens the PR.
The full original listing below is in Chinese, as published in the Hack123 newsletter.
用 DataHub 的元数据、血缘、治理和质量上下文，构建真正能处理数据问题的 Agent。
看点：四类挑战；支持 MCP 与 Agent Context Kit；现在报名只剩两天
奖金：$20,500
截止日期：8月10日（线上）
Summarized from the Chinese “Beginner Hackathon Series” newsletter. Eligibility, dates and prizes are subject to the organizer’s official page.