feat: add proactive cron tasks and systemd timers\n\n- 10 proactive tasks: ingest with self-healing & link suggestions, daily summary, health check, archive stale, tag normalizer, predictive links, auto assign review, import context buffer\n- systemd timers for scheduling (02:00/14:00 slots, 30min intervals, weekly)\n- all tasks tested and working\n\nRefs: #1

cron_tasks/import_context_buffer.py

@@ -0,0 +1,102 @@
+#!/usr/bin/env python3
+"""
+Importiert abgeschlossene Topics aus context-buffer/ als Engramme.
+Ein Topic gilt als abgeschlossen, wenn es den Status 'done' oder 'completed' hat.
+"""
+
+from __future__ import annotations
+
+import json
+import sqlite3
+import subprocess
+import sys
+from datetime import datetime, timezone
+from pathlib import Path
+
+BRAIN_DIR = Path("/root/.openclaw/workspace/second-brain")
+WORKSPACE = Path("/root/.openclaw/workspace")
+HANDLER = WORKSPACE / "context-buffer" / "handler.py"
+
+def run():
+    # Hole alle Topics mit status done/completed via handler
+    try:
+        result = subprocess.run(
+            ["python3", str(HANDLER), "search", "--status", "done"],
+            capture_output=True, text=True, timeout=30
+        )
+        if result.returncode != 0:
+            raise Exception(f"Handler error: {result.stderr}")
+        topics = json.loads(result.stdout)
+    except Exception as e:
+        print(json.dumps({"success": False, "error": str(e)}, indent=2, ensure_ascii=False))
+        return
+
+    # Alternative: auch 'completed' suchen
+    try:
+        result2 = subprocess.run(
+            ["python3", str(HANDLER), "search", "--status", "completed"],
+            capture_output=True, text=True, timeout=30
+        )
+        if result2.returncode == 0:
+            topics_completed = json.loads(result2.stdout)
+            topics.extend(topics_completed)
+    except Exception:
+        pass
+
+    if not topics:
+        print(json.dumps({"success": True, "imported": 0, "message": "No completed topics found"}, indent=2, ensure_ascii=False))
+        return
+
+    # Import in Second Brain
+    DB_PATH = BRAIN_DIR / "data" / "brain.sqlite"
+    conn = sqlite3.connect(str(DB_PATH))
+    conn.row_factory = sqlite3.Row
+    c = conn.cursor()
+
+    sys.path.insert(0, str(BRAIN_DIR))
+    from src.store import EngramStore
+    from src.engram import Engram, Grounding
+
+    store = EngramStore(str(DB_PATH))
+    imported = 0
+
+    for topic in topics:
+        topic_id = topic.get("id")
+        title = topic.get("title", "Untitled Topic")
+        content = topic.get("content", "")
+        if not content.strip():
+            continue
+
+        # Tags aus topic-type und status
+        tags = ["context-buffer", topic.get("status", "unknown")]
+        if topic.get("type"):
+            tags.append(topic["type"])
+
+        eg = Engram.create(
+            content=content,
+            source="context-buffer",
+            tags=tags,
+            grounding=Grounding.ASSUMPTION,
+        )
+        eg.metadata.update({
+            "title": title,
+            "context_buffer_id": topic_id,
+            "imported_from": "context-buffer",
+            "original_status": topic.get("status"),
+        })
+        store.save(eg)
+        imported += 1
+
+    conn.close()
+
+    print(json.dumps({
+        "success": True,
+        "time": datetime.now(timezone.utc).isoformat(),
+        "topics_found": len(topics),
+        "imported": imported,
+    }, indent=2, ensure_ascii=False))
+
+if __name__ == "__main__":
+    import sys
+    sys.path.insert(0, str(BRAIN_DIR))
+    run()