feat(bulletins): catalog monthly "עו"ד על נדל"ן" bulletins into the radar (X12)

עלון חודשי רב-נושאי (פרסום נפרד מהיומון היומי) → מתפצל ל-N שורות digest באותה
טבלה (publication='עו"ד על נדל"ן', לא קורפוס מקביל — G2):
- bulletin_splitter (LLM local-only, tools=""): מפצל ל-cases[]+articles[];
  עדכוני-חקיקה מדולגים (החלטת יו"ר).
- bulletin_library.ingest_bulletin: כל מצביע-פסיקה → digest_kind='decision'
  + embedding + autolink (כולל X13 court-fetch); כל מאמר → digest_kind='article'
  (טקסט-מלא + embedding, רקע בלבד — INV-DIG1 חל).
- content_hash per-item הוא מפתח-הדדאפ (yomon_number ריק) → אידמפוטנטי.
- db.create_digest: פרמטר digest_kind (זורם ל-INSERT + upsert).
- scripts/ingest_bulletins.py (host, venv) לעיבוד הארכיון.
- spec X12 §2.1.

אומת (dry-run, ללא DB): עלון 180 → 4 cases+1 article · עלון 201 → 4 cases
(כולל ערר-197) +1 article. עדכוני-חקיקה דולגו. claude_session נשאר local-only.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

scripts/ingest_bulletins.py

@@ -0,0 +1,56 @@
+"""Ingest the monthly "עו"ד על נדל"ן" bulletin archive into the digests radar (X12).
+
+Each staged bulletin PDF (data/bulletins/incoming) is split by LLM into case-law
+pointers (digest_kind='decision') + articles (digest_kind='article'), all tagged
+publication='עו"ד על נדל"ן'. Idempotent — per-item content_hash dedup, so re-runs
+only add new items. Runs on the HOST (LLM is local-only), with the mcp-server venv:
+
+    mcp-server/.venv/bin/python scripts/ingest_bulletins.py [--dir PATH] [--limit N]
+"""
+import argparse
+import asyncio
+import sys
+import time
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "mcp-server" / "src"))
+
+from legal_mcp.services import db, bulletin_library  # noqa: E402
+
+DEFAULT_DIR = Path(__file__).resolve().parent.parent / "data" / "bulletins" / "incoming"
+
+
+async def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--dir", default=str(DEFAULT_DIR), help="folder of bulletin PDFs")
+    ap.add_argument("--limit", type=int, default=0, help="process at most N files (0=all)")
+    args = ap.parse_args()
+
+    folder = Path(args.dir)
+    files = sorted(p for p in folder.glob("*.pdf"))
+    if args.limit:
+        files = files[: args.limit]
+    total = len(files)
+    print(f"ingesting {total} bulletins from {folder}", flush=True)
+
+    await db.get_pool()
+    agg = {"cases": 0, "articles": 0, "created": 0, "skipped": 0, "linked": 0}
+    t0 = time.time()
+    for i, f in enumerate(files, 1):
+        try:
+            r = await bulletin_library.ingest_bulletin(str(f))
+            for k in agg:
+                agg[k] += r.get(k, 0)
+            print(f"[{i}/{total}] {r['file']}: cases={r['cases']} articles={r['articles']} "
+                  f"created={r['created']} skipped={r['skipped']} linked={r['linked']}", flush=True)
+        except Exception as e:  # one bad bulletin must not abort the batch
+            print(f"[{i}/{total}] FAIL {f.name}: {type(e).__name__}: {e}", flush=True)
+
+    print(f"\nDONE {total} bulletins in {(time.time()-t0)/60:.1f}min | "
+          f"cases={agg['cases']} articles={agg['articles']} created={agg['created']} "
+          f"skipped={agg['skipped']} linked={agg['linked']}", flush=True)
+    await db.close_pool()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())