重构主控编排与运行时预热链路，统一工作区提示词/专家调度协议并补齐 wiki 记忆注入与写回闭环。

同时收敛启动与运维脚本默认行为（含 wiki worker）、更新 Admin 可观测性与相关测试，降低首轮时延并提高运行稳定性。

Made-with: Cursor

openclaw/extensions/open-prose/skills/prose/examples/40-rlm-self-refine.prose

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+# RLM: Self-Refinement
+# Recursive improvement until quality threshold
+
+input artifact: "The artifact to refine"
+input criteria: "Quality criteria"
+
+agent evaluator:
+  model: sonnet
+  prompt: "Score 0-100 against criteria. List specific issues."
+
+agent refiner:
+  model: opus
+  prompt: "Make targeted improvements. Preserve what works."
+
+block refine(content, depth):
+  if depth <= 0:
+    output content
+
+  let eval = session: evaluator
+    prompt: "Evaluate against: {criteria}"
+    context: content
+
+  if **score >= 85**:
+    output content
+
+  let improved = session: refiner
+    prompt: "Fix the identified issues"
+    context: { artifact: content, evaluation: eval }
+
+  output do refine(improved, depth - 1)
+
+output result = do refine(artifact, 5)