Scanners and strategies are 1:1 in the current codebase — separate folder
was artificial. Each scanner file now captures both implementation and thesis.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds daily /iterate and weekly /research-strategy cron workflows to the
spec — full autonomous loop with PR-gated merges, no auto-merge to main.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Defines /iterate and /research-strategy skills + docs/iterations/ folder
structure for a generic learn-improve-repeat cycle, demonstrated with the
trading agent discovery pipeline.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Documents the approved plan to fix signal quality issues in all 9
existing scanners and add 3 new scanners (analyst upgrades, technical
breakout, sector rotation).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Major additions:
- ML win probability scanner: scans ticker universe using trained
LightGBM/TabPFN model, surfaces candidates with P(WIN) above threshold
- 30-feature engineering pipeline (20 base + 10 interaction features)
computed from OHLCV data via stockstats + pandas
- Triple-barrier labeling for training data generation
- Dataset builder and training script with calibration analysis
- Discovery enrichment: confluence scoring, short interest extraction,
earnings estimates, options signal normalization, quant pre-score
- Configurable prompt logging (log_prompts_console flag)
- Enhanced ranker investment thesis (4-6 sentence reasoning)
- Typed DiscoveryConfig dataclass for all discovery settings
- Console price charts for visual ticker analysis
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Youssef Aitousarrah