fix(retrieval): make decisions findable by name + unhide committee uploads

Root cause of "agent can't find the Agasi decision in the corpus" (CMPA-55):
the decision was fully ingested, but the retrieval layer failed on the
realistic agent query — searching by case name.

- RC-A (#52): lexical tsvector covered only chunk content + halacha text,
  so a bare-name query ("אגסי") matched decisions that *cite* the case, not
  the case itself. Add meta_tsv on case_law(case_name, case_number) (SCHEMA
  V20) and OR it into the lexical halacha/chunk SQL with a match boost, so a
  name/number hit surfaces the case's own rows. Agasi: rank 4 → rank 1.
- RC-B (#53): precedent_library_list hard-defaulted source_kind=external_upload
  and never exposed the param, hiding uploaded ערר/בל"מ (internal_committee)
  decisions. Thread source_kind through service → tool → MCP tool (supports
  'internal_committee' / 'all_committees').
- #54: agent instructions (researcher/analyst/writer) — search-by-name
  protocol: add content/case-number, search both corpora, use all_committees
  before declaring "not in corpus".
- #55: chunker produced tiny fragment chunks ("דיון", "החלטה") from header
  keywords matched mid-sentence. Anchor SECTION_PATTERNS to line start +
  merge sub-min sections; exclude <50-char fragments at query time (484
  existing fragments hidden; full re-chunk tracked as #57).

Tests: scripts/test_retrieval_by_name.py (name ranks case above citer +
substantive regressions); chunker unit checks (0 tiny chunks). New findings
filed as tasks #56 (halacha source_kind leak) and #57 (re-chunk migration).

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

scripts/SCRIPTS.md

@@ -12,6 +12,7 @@
 | `sync_missing_agent_skills.py` | python | סקריפט "אל-כשל" להוספת `paperclipSkillSync` ל-`הגהת מסמכים` ו-`מנתח משפטי` שפיספסו את ה-sync ההיסטורי (Gap #28). תומך `--verify`/`--dry-run`/`--apply`. גיבוי אוטומטי ל-`agents-pre-skill-sync-*.sql`. דורש `PAPERCLIP_BOARD_API_KEY` (Infisical /paperclip ב-nautilus env). idempotent. | חד-פעמי (בוצע 2026-05-04). שמור לרפרנס |
 | `sync_agents_across_companies.py` | python | **סנכרון סוכנים מ-CMP (1xxx, master) ל-CMPA (8xxx, mirror)** — Gap #25. משווה adapter_config (model/timeout/instructions/skills/etc), runtime_config (heartbeat), ושדות top-level (budget/metadata/icon/title/role). מסנן אוטומטית local skills שלא קיימים ב-mirror. לוגיקת subset (mirror יכול להחזיק יותר skills כי ה-API מוסיף required runtime skills). תומך `--verify`/`--dry-run`/`--apply [--only NAME]`. גיבוי אוטומטי. דורש `PAPERCLIP_BOARD_API_KEY`. **להריץ אחרי כל שינוי הגדרות ב-CMP.** **⚠ אם `adapter_type` שונה בין CMP ל-CMPA — הסקריפט מדלג על הסוכן עם warning. בעת מעבר adapter (למשל ל-`deepseek_local`) חובה לעדכן ידנית בשתי החברות לפני sync.** | ידני אחרי כל שינוי |
 | `fix_paperclipai_skills_drift.py` | python | סקריפט חד-פעמי (בוצע 2026-05-04) שניקה drift על `paperclipai/*` skills בין CMP ל-CMPA. הסיר `paperclip-dev` מכל 14 הסוכנים, ודאג ש-`paperclip-converting-plans-to-tasks` קיים רק על CEO ו-analyst. תומך `--apply` (ברירת מחדל: dry-run). דורש `PAPERCLIP_BOARD_API_KEY`. נשמר לרפרנס למקרה שhdrift חוזר. | חד-פעמי (בוצע) |
+| `test_retrieval_by_name.py` | python | בדיקת אחזור-לפי-שם (#52/RC-A) — מאמת ש`search_precedent_library`/`search_internal_decisions` מדרגים את ההחלטה עצמה (אגסי) מעל מי שמצטט אותה, + רגרסיות לשאילתות מהותיות. הרצה: `DOTENV_PATH=/home/chaim/.env DATA_DIR=.../data mcp-server/.venv/bin/python scripts/test_retrieval_by_name.py` (exit 0 = עבר). | ידני אחרי שינוי שכבת חיפוש |
 | `auto-sync-cases.sh` | bash | סנכרון תיקי ערר ל-Gitea — רץ כל דקה | `* * * * *` (cron) |
 | `backup-db.sh` | bash | גיבוי PostgreSQL יומי ל-`data/backups/` (gzip) | לתזמן: `0 2 * * *` |
 | `restore-db.sh` | bash | שחזור DB מגיבוי (companion ל-backup-db.sh) | ידני |

scripts/test_retrieval_by_name.py

@@ -0,0 +1,89 @@
+#!/usr/bin/env python
+"""Repro + regression test for retrieval-by-name (RC-A, tasks #52).
+
+Bug: searching the precedent corpus by a bare case NAME ("אגסי") fails to
+surface the decision itself, because the lexical tsvector covers only chunk
+content + halacha text — not case_name / case_number. A name query therefore
+matches decisions that *cite* the case, not the case.
+
+Run with the MCP venv:
+    DOTENV_PATH=/home/chaim/.env DATA_DIR=/home/chaim/legal-ai/data \
+      mcp-server/.venv/bin/python scripts/test_retrieval_by_name.py
+
+Exit 0 = all assertions pass. Non-zero = failure (prints what was found).
+"""
+import asyncio
+import sys
+
+sys.path.insert(0, "/home/chaim/legal-ai/mcp-server/src")
+
+from legal_mcp.services import embeddings, hybrid_search  # noqa: E402
+
+AGASI_ID = "1a87efe5-6e13-4ed4-a9ec-3f2f7d61e4ec"
+# Vinfeld CITES Agasi (its halacha quote names אגסי) but is NOT Agasi.
+# An exact name match must rank the case itself above any case citing it.
+VINFELD_ID = "bd5d849c-c15f-43c3-96ab-d44337af9cb5"
+NAME_QUERY = "אגסי"
+SUBSTANTIVE_QUERY = 'פטור היטל השבחה לפי סעיף 19(ג)(1) שתי דירות 140 מ"ר אחת מושכרת'
+
+
+def _ids(rows):
+    return [str(r.get("case_law_id")) for r in rows]
+
+
+def _rank_of(rows, cid):
+    for i, r in enumerate(rows, 1):
+        if str(r.get("case_law_id")) == cid:
+            return i
+    return None
+
+
+async def _search(query, source_kind, limit=10):
+    query_emb = await embeddings.embed_query(query)
+    return await hybrid_search.search_precedent_library_hybrid(
+        query,
+        query_emb,
+        source_kind=source_kind,
+        limit=limit,
+        include_halachot=True,
+    )
+
+
+async def main():
+    results = {"pass": [], "fail": []}
+
+    # 1) THE BUG: bare-name query must rank the case ITSELF (Agasi) above any
+    #    case that merely CITES it (Vinfeld), and within the top 3.
+    rows = await _search(NAME_QUERY, "internal_committee", limit=10)
+    a_rank = _rank_of(rows, AGASI_ID)
+    v_rank = _rank_of(rows, VINFELD_ID)
+    ok = bool(a_rank) and a_rank <= 3 and (v_rank is None or a_rank < v_rank)
+    msg = (f"[name/internal] query='{NAME_QUERY}' -> Agasi rank={a_rank}, "
+           f"Vinfeld(citer) rank={v_rank} (top ids: {_ids(rows)[:5]})")
+    (results["pass"] if ok else results["fail"]).append(msg)
+
+    # 2) REGRESSION: substantive query must still find Agasi with a real score.
+    rows = await _search(SUBSTANTIVE_QUERY, "internal_committee", limit=10)
+    rank = _rank_of(rows, AGASI_ID)
+    top_score = float(rows[0]["score"]) if rows else 0.0
+    msg = f"[substantive/internal] Agasi rank={rank}, top_score={top_score:.3f}"
+    (results["pass"] if rank and rank <= 8 else results["fail"]).append(msg)
+
+    # 3) REGRESSION: substantive query in the full precedent library still works
+    #    (Vinfeld/נווה שלום etc. should surface; just assert non-empty + has betterment content).
+    rows = await _search(SUBSTANTIVE_QUERY, "external_upload", limit=10)
+    msg = f"[substantive/external] returned {len(rows)} rows (top ids: {_ids(rows)[:3]})"
+    (results["pass"] if len(rows) >= 3 else results["fail"]).append(msg)
+
+    print("\n=== PASS ===")
+    for m in results["pass"]:
+        print("  ✓", m)
+    print("=== FAIL ===")
+    for m in results["fail"]:
+        print("  ✗", m)
+
+    return 1 if results["fail"] else 0
+
+
+if __name__ == "__main__":
+    sys.exit(asyncio.run(main()))