| name | alpharank_validation |
| description | AlphaRank validation dashboard: model scorecard with IC/ICIR/PBO/DSR gates, feature importance analysis, overfitting diagnostics, validation checklist tracker, and model comparison |
AlphaRank validation dashboard: model scorecard with IC/ICIR/PBO/DSR gates, feature importance analysis, overfitting diagnostics, validation checklist tracker, and model comparison
Tool Reference
enso_alpharank_validation_scorecard (primary)
Display AlphaRank model validation scorecard with key metrics (IC, ICIR, PBO, DSR, Sharpe, drawdown) and pass/fail gates for each model horizon M1-M12. Accepts metrics as JSON input or reads from a results file. Use when the user says: 'show validation scorecard', 'model metrics', 'how are my models doing', 'validation dashboard', 'AlphaRank scorecard'.
Parameters:
metrics (string): JSON string of model metrics. Each model should have: name, trainIC, testIC, icir, pbo, dsr, sharpe, annualReturn, maxDrawdown. If omitted, reads from state or uses sample data.filePath (string): Path to a JSON results file containing model metrics. Optional.
enso_alpharank_validation_features
View feature importance analysis for AlphaRank models: top features by SHAP/MDI importance, category breakdown, stability scores, and keep/cut recommendations. Accept feature data as JSON input. Use when the user says: 'show feature importance', 'which features matter', 'feature analysis', 'SHAP values'.
Parameters:
features (string): JSON string of feature importance data. Each feature should have: name, importance, category, stability, recommendation. If omitted, uses sample data.model (string): Model name to show features for (e.g. 'M1', 'M6'). Defaults to best model.topN (number): Number of top features to display (default: 20)
enso_alpharank_validation_diagnose
Run overfitting diagnostic analysis: train vs test comparison, IC decay curve, rolling IC, degrees of freedom, and LLM-powered recommendation engine. Use when the user says: 'diagnose overfitting', 'why is my model overfitting', 'overfitting analysis', 'train vs test gap'.
Parameters:
diagnostics (string): JSON string of diagnostic data including train/test metrics over time. If omitted, uses sample data.model (string): Model name to diagnose (e.g. 'M1', 'M6'). Defaults to worst performing model.
enso_alpharank_validation_checklist
Track AlphaRank validation progress: PBO test, CPCV implementation, DSR computation, transaction cost modeling, OOS test, paper trading. Persistent state saved to disk. Use when the user says: 'validation checklist', 'what validation steps remain', 'track validation progress', 'update checklist'.
Parameters:
action (string): Action: 'view' to see checklist, 'update' to change an item's status. Default: view.itemId (string): Checklist item ID to update (e.g. 'pbo_test', 'cpcv', 'dsr', 'txcosts', 'oos_test', 'paper_trading')status (string): New status: 'not_started', 'in_progress', 'done'notes (string): Optional notes for the checklist item
enso_alpharank_validation_compare
Compare two or more AlphaRank model configurations side by side. Show delta in key metrics, highlight which is better. Use when the user says: 'compare models', 'which model is better', 'model comparison', 'A vs B'.
Parameters:
configurations (string): JSON string of model configurations to compare. Each should have: name, testIC, icir, pbo, sharpe, annualReturn, maxDrawdown, features, turnover. If omitted, uses sample data.
