refactor(core): remove Vulture-confirmed dead code

src/basic_memory/mcp/tools/move_note.py

@@ -148,49 +148,6 @@ def _format_cross_project_error_response(
         """).strip()
 
 
-def _format_potential_cross_project_guidance(
-    identifier: str, destination_path: str, current_project: str, available_projects: list[str]
-) -> str:
-    """Format guidance for potentially cross-project moves."""
-    other_projects = ", ".join(available_projects[:3])  # Show first 3 projects  # pragma: no cover
-    if len(available_projects) > 3:  # pragma: no cover
-        other_projects += f" (and {len(available_projects) - 3} others)"  # pragma: no cover
-
-    return (  # pragma: no cover
-        dedent(f"""
-        # Move Failed - Check Project Context
-
-        Cannot move '{identifier}' to '{destination_path}' within the current project '{current_project}'.
-
-        ## If you intended to move within the current project:
-        The destination path should be relative to the project root:
-        ```
-        move_note("{identifier}", "folder/filename.md")
-        ```
-
-        ## If you intended to move to a different project:
-        Cross-project moves require switching projects first. Available projects: {other_projects}
-
-        ### To move to another project:
-        ```
-        # 1. Read the content
-        read_note("{identifier}")
-
-        # 2. Create note in target project
-        write_note("Title", "content", "folder", project="target-project-name")
-
-        # 3. Delete original if desired
-        delete_note("{identifier}", project="{current_project}")
-        ```
-
-        ### To see all projects:
-        ```
-        list_memory_projects()
-        ```
-        """).strip()
-    )
-
-
 def _format_move_error_response(error_message: str, identifier: str, destination_path: str) -> str:
     """Format helpful error responses for move failures that guide users to successful moves."""
 

src/basic_memory/mcp/tools/recent_activity.py

@@ -332,7 +332,12 @@ async def recent_activity(
                 return _extract_recent_rows(activity_data)
 
             # Format project-specific mode output
-            return _format_project_output(active_project.name, activity_data, timeframe, type, page)
+            return _format_project_output(
+                active_project.name,
+                activity_data,
+                timeframe,
+                page=page,
+            )
 
 
 async def _get_project_activity(
@@ -480,7 +485,6 @@ def _format_project_output(
     project_name: str,
     activity_data: GraphContext,
     timeframe: str,
-    type_filter: Union[str, List[str]],
     page: int = 1,
 ) -> str:
     """Format project-specific mode output as human-readable text."""

src/basic_memory/repository/search_repository_base.py

@@ -25,7 +25,6 @@
     VectorChunkRecord,
     build_entity_fingerprint,
     build_vector_chunk_records,
-    compose_row_source_text,
     split_text_into_chunks,
 )
 from basic_memory.repository.semantic_errors import (
@@ -424,15 +423,6 @@ def _assert_semantic_available(self) -> None:
                 "and set semantic_search_enabled=true."
             )
 
-    def _compose_row_source_text(self, row: SemanticSourceRow) -> str:
-        """Build the text blob that will be chunked and embedded for one search_index row.
-
-        For entity rows we use title, permalink, and content_snippet (the actual
-        human-readable content).  content_stems is an FTS-optimised variant that
-        includes word-boundary expansions and would dilute embedding quality.
-        """
-        return compose_row_source_text(row)
-
     def _build_chunk_records(self, rows: Iterable[SemanticSourceRow]) -> list[VectorChunkRecord]:
         chunk_build = build_vector_chunk_records(rows)
         if chunk_build.duplicate_chunk_keys:
@@ -584,28 +574,6 @@ async def _prepare_entity_vector_jobs_window(
             entity_ids,
         )
 
-    async def _prepare_entity_vector_jobs(
-        self,
-        entity_id: int,
-    ) -> _PreparedEntityVectorSync:
-        """Prepare chunk mutations and embedding jobs for one entity."""
-        return await semantic_vector_sync.prepare_entity_vector_jobs(self, entity_id)
-
-    async def _prepare_entity_vector_jobs_prefetched(
-        self,
-        *,
-        entity_id: int,
-        source_rows: list[Any],
-        existing_rows: list[VectorChunkState],
-    ) -> _PreparedEntityVectorSync:
-        """Prepare one entity using prefetched window rows."""
-        return await semantic_vector_sync.prepare_entity_vector_jobs_prefetched(
-            self,
-            entity_id=entity_id,
-            source_rows=source_rows,
-            existing_rows=existing_rows,
-        )
-
     async def _upsert_scheduled_chunk_records(
         self,
         session: AsyncSession,
@@ -1011,32 +979,6 @@ def _log_vector_summary() -> None:
         _log_vector_summary()
         return ranked_rows[offset : offset + limit]
 
-    async def _fetch_entity_rows_by_ids(self, entity_ids: list[int]) -> dict[int, SearchIndexRow]:
-        """Fetch entity-type search_index rows by their entity_id values."""
-        placeholders = ",".join(f":id_{idx}" for idx in range(len(entity_ids)))
-        params: dict[str, Any] = {
-            **{f"id_{idx}": eid for idx, eid in enumerate(entity_ids)},
-            "project_id": self.project_id,
-            "item_type": SearchItemType.ENTITY.value,
-        }
-        sql = f"""
-            SELECT
-                project_id, id, title, permalink, file_path, type, metadata,
-                from_id, to_id, relation_type, entity_id, content_snippet,
-                category, created_at, updated_at, 0 as score
-            FROM search_index
-            WHERE project_id = :project_id
-              AND type = :item_type
-              AND entity_id IN ({placeholders})
-        """
-        result: dict[int, SearchIndexRow] = {}
-        async with db.scoped_session(self.session_maker) as session:
-            row_result = await session.execute(text(sql), params)
-            for row in row_result.fetchall():
-                search_row = SearchIndexRow.from_mapping(row._asdict())
-                result[row.entity_id] = search_row
-        return result
-
     async def _fetch_search_index_rows_by_ids(
         self, row_ids: list[int]
     ) -> dict[SearchIndexKey, SearchIndexRow]:

tests/mcp/test_tool_recent_activity.py

@@ -254,7 +254,7 @@ def test_recent_activity_format_project_output_no_results():
     )
 
     out = recent_activity_module._format_project_output(
-        project_name="proj", activity_data=empty, timeframe="7d", type_filter="", page=1
+        project_name="proj", activity_data=empty, timeframe="7d", page=1
     )
     assert "No recent activity found" in out
 
@@ -321,7 +321,6 @@ def test_recent_activity_format_project_output_renders_all_entities_and_relation
         project_name="proj",
         activity_data=activity,
         timeframe="7d",
-        type_filter=["entity", "relation"],
         page=1,
     )
 
@@ -367,7 +366,6 @@ def test_recent_activity_format_project_output_includes_observation_truncation()
         project_name="proj",
         activity_data=activity,
         timeframe="7d",
-        type_filter="observation",
         page=1,
     )
     assert "Recent Observations" in out
@@ -568,7 +566,6 @@ def test_format_project_output_has_more_pagination_guidance():
         project_name="proj",
         activity_data=activity,
         timeframe="7d",
-        type_filter="entity",
         page=1,
     )
     assert "Use page=2 to see more" in out
@@ -606,7 +603,6 @@ def test_format_project_output_no_more_pages():
         project_name="proj",
         activity_data=activity,
         timeframe="7d",
-        type_filter="entity",
         page=1,
     )
     assert "1 items found." in out