feat: add internal committee decisions corpus (source_kind='internal_committee')

Three-layer separation: style learning (style_corpus), appeals-committee decisions
(internal_committee), and court rulings (external_upload).

- SCHEMA_V10: chair_name + district columns on case_law and cases, partial indexes
- create_internal_committee_decision() DB upsert function
- search_precedent_library_semantic() now accepts source_kind/district/chair_name params
- search_precedent_library_hybrid() passes through new params
- services/internal_decisions.py: ingest_internal_decision, migrate_from_style_corpus,
  migrate_from_external_corpus (identifies rows via source_type='appeals_committee')
- search_internal_decisions() MCP tool (server.py + tools/search.py)
- internal_decision_migrate() MCP admin tool
- Web endpoints: POST /api/internal-decisions/upload, POST /api/internal-decisions/migrate,
  GET /api/internal-decisions
- ingest_final_version auto-ingests finalized decisions into internal corpus
- SKILL.md updated: agents now search internal + external in parallel, present separately

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

mcp-server/src/legal_mcp/services/hybrid_search.py

@@ -88,8 +88,15 @@ async def search_precedent_library_hybrid(
     is_binding: bool | None = None,
     subject_tag: str = "",
     include_halachot: bool = True,
+    source_kind: str = "external_upload",
+    district: str = "",
+    chair_name: str = "",
 ) -> list[dict]:
-    """Hybrid wrapper for precedent-library search."""
+    """Hybrid wrapper for precedent-library search.
+
+    source_kind='external_upload'    → court rulings (default)
+    source_kind='internal_committee' → appeals-committee decisions
+    """
     fetch_k = max(limit, config.VOYAGE_RERANK_FETCH_K) if config.MULTIMODAL_ENABLED else limit
 
     async def _base(limit: int) -> list[dict]:
@@ -103,6 +110,9 @@ async def search_precedent_library_hybrid(
             subject_tag=subject_tag,
             limit=limit,
             include_halachot=include_halachot,
+            source_kind=source_kind,
+            district=district,
+            chair_name=chair_name,
         )
 
     text_results = await rerank.maybe_rerank(