3.4 Review 与归档：怎么才算做完

"做完了"是项目中最大的谎言。很多时候，你说做完了，对方一检查，发现还有问题。更常见的是，你说做完了，然后没有人检查，任务就永远悬在那里。

AI Context Workspace 要求：每个 L2/L3 任务完成前，必须经过 Review。

Review 不是走过场，它有一个明确的检查清单，每项检查有证据，每项证据可追溯。

三种 Review 结论：

PASS——所有完成标准都有充分证据。任务可以归档。这是最常见、最理想的结论。

REVIEW——存在需要人类复核的项目。AI 可能已经做了合理的判断，但涉及高风险或主观判断，需要人类确认。如果用户接受当前结果，写入接受记录后也可以归档。

BLOCKED——存在失败项、关键证据缺失或未解决问题。任务不能归档，必须继续处理并重新 Review。

Review 不是扣分，是消除不确定性。

AI 的优点是执行力强，缺点是有时候会"自信地犯错"。Review 机制就是为 AI 的"自信犯错"准备的保险。它不假设 AI 一定会犯错，但假设 AI 有可能犯错，并且通过检查来发现错误。

归档：完结不是结束

归档是任务的最终状态。归档后的任务不可原地修改，只能查阅。归档操作包括：

  1. 在 artifact.json 中写入最终状态和 outcome
  2. 生成 archive/summary.md，记录任务摘要、完成情况和关键决策
  3. 从 artifacts/index.json 的活跃列表移除
  4. 将 Artifact 目录移入 _archived/ 子目录

归档的价值不在于"结束"，而在于"可恢复"。

半年后你需要回顾一个决策，打开归档的 Artifact，读 archive/summary.md，看当时的 Review 结论，理解决策的上下文。你不需要问任何人"当时为什么这么选"，文件会告诉你。

这就是归档的意义：把经验从人的记忆转移到文件系统。 人不会永远记得，但文件会。

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