- Add unrealized_pnl_pct_above/below and holding_days_above/below fields
to StockCondition so AI can generate rules like 'P&L > 3% → SELL'
- Evaluate new fields in ScenarioEngine.evaluate_condition() with same
AND-combining logic as existing technical indicator fields
- Include position fields in _build_match_details() for audit logging
- Parse new fields from AI JSON response in PreMarketPlanner._parse_scenario()
- Update prompt schema example to show new position-aware condition fields
- Add 13 tests covering all new condition combinations and edge cases
Closes#171
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Addresses second round of PR #102 review:
- _warn_missing_key(): logs each missing key only once per engine instance
to prevent log spam in high-frequency trading loops
- _build_match_details(): uses _safe_float() normalized values instead of
raw market_data to ensure consistent float types in logging/analysis
- Test: verify warning fires exactly once across repeated calls
- Test: verify match_details contains normalized float values
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
ScenarioEngine evaluates pre-defined playbook scenarios against real-time
market data with sub-100ms execution (zero API calls). Supports condition
AND-matching, global portfolio rules, and first-match-wins priority.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
