初始化：独立 oclaw 仓库首提交

- 在 oclaw/ 下重新初始化 Git 仓库
- 补齐子仓库 .gitignore，避免提交本地运行态数据（_local、node_modules、logs 等）
- 提交当前工程代码与配置

Made-with: Cursor

orchestration/evaluation.py

@@ -0,0 +1,62 @@
+from __future__ import annotations
+
+from collections import defaultdict
+from typing import Any
+
+from oclaw.platform.persistence.sqlite_store import SqliteStore
+
+
+def log_eval_event(
+    store: SqliteStore,
+    *,
+    session_id: str,
+    specialist: str,
+    task_kind: str,
+    success: bool,
+    latency_ms: int,
+    cost_hint: float = 0.0,
+    notes: str = "",
+) -> None:
+    store.add_agent_eval_log(
+        session_id=session_id,
+        specialist=specialist,
+        task_kind=task_kind,
+        success=success,
+        latency_ms=latency_ms,
+        cost_hint=cost_hint,
+        notes=notes,
+    )
+
+
+def eval_summary(store: SqliteStore, *, limit: int = 200) -> dict[str, Any]:
+    rows = store.list_agent_eval_logs(limit=limit)
+    if not rows:
+        return {"total": 0, "success_rate": 0.0, "p95_latency_ms": 0}
+    success_cnt = sum(1 for r in rows if bool(r.get("success")))
+    lats = sorted(int(r.get("latency_ms") or 0) for r in rows)
+    idx = max(0, int(len(lats) * 0.95) - 1)
+    by_specialist: dict[str, dict[str, Any]] = defaultdict(lambda: {"total": 0, "ok": 0, "lat": []})
+    plan_rows = 0
+    for r in rows:
+        sp = str(r.get("specialist") or "unknown")
+        by_specialist[sp]["total"] += 1
+        by_specialist[sp]["ok"] += 1 if bool(r.get("success")) else 0
+        by_specialist[sp]["lat"].append(int(r.get("latency_ms") or 0))
+        if "manager_plan_generated" in str(r.get("notes") or ""):
+            plan_rows += 1
+    specialist_metrics: dict[str, dict[str, Any]] = {}
+    for sp, m in by_specialist.items():
+        l = sorted(m["lat"])
+        p95_idx = max(0, int(len(l) * 0.95) - 1)
+        specialist_metrics[sp] = {
+            "total": m["total"],
+            "success_rate": round((m["ok"] / m["total"]) if m["total"] else 0.0, 4),
+            "p95_latency_ms": l[p95_idx] if l else 0,
+        }
+    return {
+        "total": len(rows),
+        "success_rate": round(success_cnt / len(rows), 4),
+        "p95_latency_ms": lats[idx],
+        "plan_events": plan_rows,
+        "by_specialist": specialist_metrics,
+    }