edge-candidate-agentlisted

# Edge Candidate Agent ## Overview Convert daily market observations into reproducible research tickets and Phase I-compatible candidate specs. Prioritize signal quality and interface compatibility over aggressive strategy proliferation. This skill can run end-to-end standalone, but in the split workflow it primarily serves the final export/validation stage. ## When to Use - Convert market observations, anomalies, or hypotheses into structured research tickets. - Run daily auto-detection to discover new edge candidates from EOD OHLCV and optional hints. - Export validated tickets as `strategy.yaml` + `metadata.json` for `trade-strategy-pipeline` Phase I. - Run preflight compatibility checks for `edge-finder-candidate/v1` before pipeline execution. ## Prerequisites - Python 3.9+ with `PyYAML` installed. - Access to the target `trade-strategy-pipeline` repository for schema/stage validation. - `uv` available when running pipeline-managed validation via `--pipeline-root`. ## Output - `strategies/<candidate_id>/strategy.yaml`: Phase I-compatible strategy spec. - `strategies/<candidate_id>/metadata.json`: provenance metadata including interface version and ticket context. - Validation status from `scripts/validate_candidate.py` (pass/fail + reasons). - Daily detection artifacts: - `daily_report.md` - `market_summary.json` - `anomalies.json` - `watchlist.csv` - `tickets/exportable/*.yaml` - `tickets/research_only/*.yaml` ## Position in Split Workflow Recommend