Use when working on dataset materialization, model training, backtesting, scan-edge signals, paper-trading workflows, or experiment artifacts in polymarket-tmax-lab.
Use this skill for the research and trading simulation loop.
AGENTS.md.docs/agent-skills/research-loop.mddocs/codebase/modeling.mddocs/codebase/backtest-execution.mdbuild-dataset MUST use --markets-path configs/market_inventory/full_training_set_snapshots.json.
Running without it rebuilds with only 12 example rows (destroys training data).historical_training_set* / historical_backtest_panel overwrite requires --allow-canonical-overwrite.--output-name values for experiments and rely on the automatic artifacts/recovery/ backup when promoting canonical output.scan-edge MUST include --min-model-prob 0.05 --max-model-prob 0.95.scripts/run_price_check.shlogs/price_check.loguv run python scripts/log_gamma_prices.pytrain-advanced --model-name lgbm_emos --variant <variant>.uv run python scripts/quick_eval.py (champion baseline + OOF variants).observation-report, observation-shadow, observation-daemon, approve-live-candidate.exact_public intraday -> documented research intraday -> METAR fallback, target-day only.station-dashboard, station-dashboard-daemon.station-cycle, station-daemon.pmtmax-autoresearch when you are exploring new lgbm_emos candidates around recency_neighbor_oof.data/workspaces/historical_real/parquet/gold/historical_training_set.parquetartifacts/workspaces/<workspace>/models/v2/artifacts/public_models/champion.jsonartifacts/workspaces/ops_daily/signals/v2/scan_edge_latest.jsonartifacts/workspaces/ops_daily/signals/v2/live_pilot_queue.jsonartifacts/workspaces/ops_daily/signals/v2/forward_paper_trades.jsonlogs/daily_experiment.logscripts/run_price_check.shlogs/price_check.log