docs: finish hierarchy rescan after rebase

packages/guard/repeat-tool-guard/README.i18n.yaml

@@ -2,5 +2,5 @@
 # side as of the last confirmed-consistent state. Both languages carry equal authority;
 # after editing either side, bring the other along and re-record with:
 #   pnpm run verify-translation-pairing --write packages/guard/repeat-tool-guard/README.md
-README.md: 226dba10239031e8e79bd5698e77c213688ce579
-README.zh.md: 004c463d8b3b6d3ed6f215e86e59b02fec27cf3f
+README.md: be3686cbae76a5ced6e448c7516090757513565a
+README.zh.md: dd161f5cb1cfd3a9691333f67ece35594a61316d

packages/guard/repeat-tool-guard/README.md

@@ -34,10 +34,6 @@ The chain key is `(tool name, canonical arguments)` — canonicalization is a de
 
 Reminders ride the post-execute decision's `additionalContexts` (source `{kind: 'plugin', plugin: 'repeat-tool-guard'}`), never a `content` replacement: the `tool/result` event stays the tool's own output for audit. The loop buffers the context and appends it as an injected `user/message` after the step's tool results, which the session renders as a plain synthetic user message — so the reminder is model-visible, source-attributed, and reconstructable from the session log with no new session event. The guard always delegates via `next()` and prepends its reminder to the downstream decision's context array (both variants — a blocked call still gets the nudge); every entry retains its own source and metadata.
 
-## Testing
-
-Unit suites drive a real agent loop against a mock adapter (no network) and cover the chain semantics above to per-file 100%. The snapshot tier owns the transcript surface: a scripted-replay scenario repeats a call five times and pins both reminder tiers (gentle at 3, detailed at 5) as injected `user/message`s in the ACP transcript.
-
 ## Model Experience
 
 ### First-threshold context message

packages/guard/repeat-tool-guard/README.zh.md

@@ -34,10 +34,6 @@
 
 提醒通过 post-execute 决策中的 `additionalContexts`（来源为 `{kind: 'plugin', plugin: 'repeat-tool-guard'}`）传递，绝不替换 `content`；用于审计的 `tool/result` 事件仍保留工具自己的输出。循环会缓冲这段上下文，并在该步骤的工具结果之后将其作为注入的 `user/message` 追加；会话会将它渲染为普通的合成用户消息。因此，提醒对模型可见、带有来源归属，并且无需增加会话事件即可从会话日志重建。guard 始终通过 `next()` 委派，并将自己的提醒放在下游决策的上下文数组之前（两种结果都适用：被阻止的调用也会收到提醒）；每个条目保留自己的来源和元数据。
 
-## 测试
-
-单元测试使用 mock 适配器（无网络）驱动真实 agent loop，并对上述链语义实现逐文件 100% 覆盖率。快照层负责 transcript（文本记录）接口：脚本化回放场景会将同一调用重复 5 次，并在 ACP（Agent Client Protocol）的 transcript 中固定两个提醒层级，即第 3 次的温和提醒和第 5 次的详细提醒；二者均为注入的 `user/message`。
-
 ## 模型体验
 
 ### 首个阈值的上下文消息