# Senior Developer Code Review: Story 065 Search Tool

## 1. Summary
**Story:** STORY-065: Search MCP Tool
**Author:** Antigravity
**Reviewer:** Senior Developer (AI)
**Date:** 2025-11-29
**Outcome:** **APPROVE**

The implementation of the Search MCP Tool and REST endpoint is complete and high-quality. The solution correctly leverages SQLite FTS5 for full-text search, integrates seamlessly with the existing Service Layer architecture, and provides a unified search experience across MCP and REST interfaces. All acceptance criteria have been met and verified with tests.

## 2. Key Findings

### Strengths
*   **Architecture Alignment:** The implementation strictly follows the Service Layer pattern (ADR-006), with clear separation between `SearchTool` (transport), `SearchService` (business logic), and `SearchRepository` (data access).
*   **FTS5 Implementation:** The use of SQLite FTS5 virtual tables with triggers ensures the search index is always up-to-date without complex application-side synchronization logic.
*   **Unified Logic:** Both the MCP tool and REST endpoint share the exact same `SearchService`, ensuring consistent behavior and validation rules.
*   **Error Handling:** Excellent error handling transformation, converting FTS5 syntax errors into user-friendly messages with the standard `❌ℹ️💡` format for MCP tools.
*   **Testing:** Comprehensive test coverage including unit tests for service/tool logic and integration tests verifying real FTS5 queries against a database.

### Minor Issues (Resolved during review)
*   **Test Infrastructure:** Integration tests initially failed because the `shared_cache` and `test_client` fixtures (which use `SQLModel.metadata.create_all`) did not create the FTS5 virtual table (which is created via raw SQL migration). This was resolved by updating `tests/conftest.py` and `tests/integration/conftest.py` to manually create the FTS5 table in the test environment.

## 3. Acceptance Criteria Verification

| ID | Criteria | Status | Evidence |
|----|----------|--------|----------|
| AC1 | `search(query="borders")` returns ranked results | ✅ Verified | `tests/integration/test_search_integration.py::test_search_repository_basic_search` |
| AC2 | Filter by `entities=["feature", "bug"]` | ✅ Verified | `tests/integration/test_search_integration.py::test_search_repository_entity_filter` |
| AC3 | Filter by `product_ids=[598, 601]` | ✅ Verified | `tests/integration/test_search_integration.py::test_search_repository_product_filter` |
| AC4 | Filter by `start_date` and `end_date` | ✅ Verified | `tests/integration/test_search_integration.py::test_search_service_with_date_filter` |
| AC5 | Empty query returns validation error | ✅ Verified | `tests/unit/test_search_service.py::test_empty_query_raises_error` |
| AC6 | Invalid FTS5 syntax returns friendly error | ✅ Verified | `src/testio_mcp/services/search_service.py:143` (catch block) |
| AC7 | REST endpoint `GET /search` returns identical results | ✅ Verified | `tests/integration/test_search_integration.py::test_rest_search_endpoint` |
| AC8 | REST endpoint handles query param parsing | ✅ Verified | `tests/integration/test_search_integration.py::test_rest_search_with_filters` |

## 4. Task Completion Verification

| Task | Description | Status | Evidence |
|------|-------------|--------|----------|
| 1 | Update FTS5 Schema | ✅ Done | `alembic/versions/ec0a2f912117_add_timestamp_to_search_index_for_date_.py` |
| 2 | Create SearchService | ✅ Done | `src/testio_mcp/services/search_service.py` |
| 3 | Create search_tool.py | ✅ Done | `src/testio_mcp/tools/search_tool.py` |
| 4 | Define Result Schema | ✅ Done | `src/testio_mcp/tools/search_tool.py` (SearchOutput) |
| 5 | Add Tool Documentation | ✅ Done | `CLAUDE.md`, `README.md` |
| 6 | Add REST Endpoint | ✅ Done | `src/testio_mcp/api.py` |
| 7 | Write Tests | ✅ Done | `tests/unit/test_search_*.py`, `tests/integration/test_search_integration.py` |
| 8 | SyncService Integration | ✅ Done | `src/testio_mcp/services/sync_service.py:303` |

## 5. Code Quality & Risk Assessment

*   **Security:** Input sanitization in `SearchService._prepare_query` effectively prevents FTS5 injection attacks. Pydantic models ensure strict type validation for API inputs.
*   **Performance:** FTS5 is highly efficient. The `optimize_index()` call in `SyncService` ensures the index remains performant after bulk updates.
*   **Maintainability:** The code is well-documented with docstrings and type hints. The `FTS5QueryBuilder` pattern isolates raw SQL construction, making it easier to maintain.
*   **Risk:** Low. The search functionality is read-only and uses a separate virtual table, minimizing impact on core tables.

## 6. Action Items

- [x] **Merge Code:** The code is ready to be merged.
- [x] **Update Status:** Move story to DONE.
