Major improvements:
- Fixed all 42 broken tests (database connection leaks)
- Added db_connection() context manager for proper cleanup
- Created comprehensive test suites for undertested modules
New test coverage:
- tools/general_tools.py: 26 tests (97% coverage)
- tools/price_tools.py: 11 tests (validates NASDAQ symbols, date handling)
- api/price_data_manager.py: 12 tests (85% coverage)
- api/routes/results_v2.py: 3 tests (98% coverage)
- agent/reasoning_summarizer.py: 2 tests (87% coverage)
- api/routes/period_metrics.py: 2 edge case tests (100% coverage)
- agent/mock_provider: 1 test (100% coverage)
Database fixes:
- Added db_connection() context manager to prevent leaks
- Updated 16+ test files to use context managers
- Fixed drop_all_tables() to match new schema
- Added CHECK constraint for action_type
- Added ON DELETE CASCADE to trading_days foreign key
Test improvements:
- Updated SQL INSERT statements with all required fields
- Fixed date parameter handling in API integration tests
- Added edge case tests for validation functions
- Fixed import errors across test suite
Results:
- Total coverage: 84.81% (was 61%)
- Tests passing: 406 (was 364 with 42 failures)
- Total lines covered: 6364 of 7504
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Update unit tests to mock CallToolResult objects instead of plain dicts,
matching actual MCP tool behavior in production.
Changes:
- Add create_mcp_result() helper to create mock CallToolResult objects
- Update all mock handlers to return MCP result objects
- Update assertions to access result.structuredContent field
- Maintains test coverage while accurately reflecting production behavior
This ensures tests validate the actual code path used in production,
where MCP tools return CallToolResult objects with structuredContent
field containing the position dict.
Resolves issue where sell proceeds were not immediately available for
subsequent buy orders within the same trading session.
Problem:
- Both buy() and sell() independently queried database for starting position
- Multiple trades within same day all saw pre-trade cash balance
- Agents couldn't rebalance portfolios (sell + buy) in single session
Solution:
- ContextInjector maintains in-memory position state during trading session
- Position updates accumulate after each successful trade
- Position state injected into buy/sell via _current_position parameter
- Reset position state at start of each trading day
Changes:
- agent/context_injector.py: Add position tracking with reset_position()
- agent_tools/tool_trade.py: Accept _current_position in buy/sell functions
- agent/base_agent/base_agent.py: Reset position state daily
- tests: Add 13 comprehensive tests for position tracking
All new tests pass. Backward compatible, no schema changes required.
