feat: add info engine MVP pipeline and dashboard page

Introduce a standalone scheduled info-engine worker with SQLite persistence and expose read-only dashboard APIs/UI so curated intelligence items can be collected and viewed with minimal architecture changes.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

info-engine/main.py

@@ -0,0 +1,37 @@
+import asyncio
+import logging
+import os
+
+from collector import collect_sources
+from db import init_db, upsert_items
+from processor import process_items
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s %(name)s %(levelname)s %(message)s")
+log = logging.getLogger(__name__)
+
+COLLECT_INTERVAL_SECONDS = int(os.environ.get("INFO_ENGINE_INTERVAL_SECONDS", "900"))
+
+
+async def run_once() -> int:
+    raw_items = await collect_sources()
+    processed = process_items(raw_items)
+    inserted = await upsert_items(processed)
+    return inserted
+
+
+async def main():
+    await init_db()
+    log.info("Info engine started (interval=%ss)", COLLECT_INTERVAL_SECONDS)
+
+    while True:
+        try:
+            inserted = await run_once()
+            log.info("Info engine cycle complete (inserted=%d)", inserted)
+        except Exception as exc:
+            log.error("Info engine cycle failed: %s", exc)
+
+        await asyncio.sleep(COLLECT_INTERVAL_SECONDS)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())