Use this skill for feature engineering, modeling, and backtesting work.
Hard constraints
- Follow the modeling order exactly:
- FP2 / FP3 head-to-head
- constructor / team fastest lap
- driver outright fastest lap
- red flag / safety car
- Every predictive dataset must be built from an explicit as-of snapshot.
- Use time-aware walk-forward splits only.
- Backtests must use executable bid/ask or orderbook depth, not midpoint-only evaluation.
- The agent layer explains and retrieves results; it is not the primary forecaster.
Workflow
- Inspect existing feature registry, model stage definitions, experiments, and storage contracts.
- Add or update features only if they can be reproduced from saved cutoffs.
- Persist dataset version, config, seed, metrics, and calibration artifacts together.
- Prefer simpler baselines before more complex ML or DL models, and justify any added complexity.
- Include error analysis by season, circuit, team, and market/liquidity bucket.