Discover Business skills, compare source repositories and read the instructions for each workflow.
Provides expert Nixtla forecasting using TimeGPT, StatsForecast, and MLForecast. Generates time series forecasts, analyzes trends, compares models, performs cross-validation, and recommends best practices. Acti...
Forecasts multiple time series in parallel batches using TimeGPT API. Optimizes throughput with rate limiting and supports portfolio aggregation. Use when processing 10-100+ contracts or needing efficient multi...
Generate production-ready TimeGPT forecasting pipeline code from requirements. Use when scaffolding a pipeline with validation, logging, visualization, and repeatable runs. Trigger with "create TimeGPT pipeline...
Analyzes multi-contract correlations and generates hedge recommendations. Use when managing a portfolio of correlated assets and needing to mitigate risk. Trigger with "analyze correlations", "suggest hedge", "...
Generate benchmarking pipelines to compare forecasting models and summarize accuracy/speed trade-offs. Use when evaluating TimeGPT vs StatsForecast/MLForecast/NeuralForecast on a dataset. Trigger with "benchmar...
Automatically selects the best forecasting model between StatsForecast and TimeGPT based on time series data characteristics. Use when unsure which model performs best. Trigger with "auto-select model", "choose...
Scaffolds production-ready forecasting experiments with Nixtla libraries. Creates configuration files, experiment harnesses, multi-model comparisons, and cross-validation workflows for StatsForecast, MLForecast...
Transform PRD documents into actionable implementation tasks with TodoWrite integration. Use when planning development work, converting requirements to tasks, or creating implementation roadmaps. Trigger with '...
Analyze causal impact of events on time series forecasts using TimeGPT. Use when quantifying promotion or disaster effects. Trigger with 'event impact analysis' or 'causal analysis'.
Forecasts orderbook depth and spreads to optimize trade execution timing. Use when needing to estimate market liquidity for large orders. Trigger with 'forecast liquidity', 'predict orderbook', 'estimate depth'...
Transforms forecasting experiments into production-ready inference pipelines with Airflow, Prefect, or cron orchestration. Generates ETL tasks, monitoring, error handling, and deployment configs. Activates when...
Fine-tunes TimeGPT on custom datasets to improve forecasting accuracy. Use when TimeGPT's zero-shot performance is insufficient or domain-specific accuracy is needed. Trigger with "finetune TimeGPT", "train Tim...
Detects anomalies in time series data using TimeGPT. Identifies outliers, level shifts, and trend breaks without model training. Use when identifying anomalies, outliers, or unusual patterns in time series. Tri...
Generate comprehensive pytest test suites from PRD functional requirements with fixtures, parameterization, and coverage tracking. Use when creating tests for new plugins, validating PRD requirements, or scaffo...
Generate production-ready Jupyter notebooks showcasing Nixtla forecasting workflows for statsforecast, mlforecast, and TimeGPT. Use when creating demos, building examples, or showcasing forecasting capabilities...
Quantifies prediction uncertainty using conformal prediction. Use when risk assessment, scenario planning, or decision-making under uncertainty is required. Trigger with "quantify uncertainty", "generate predic...
Analyze forecast uncertainty using conformal prediction. Use when risk assessment or scenario planning is required. Trigger with 'quantify uncertainty' or 'prediction intervals'.
Performs rigorous time series cross-validation using expanding and sliding windows. Use when needing to evaluate the performance of time series models on unseen data. Trigger with cross validate time series, ev...
Transform data sources to Nixtla schema (unique_id, ds, y) with column inference. Use when preparing data for forecasting. Trigger with 'map to Nixtla schema' or 'transform data'.
Automatically selects the best forecasting model between StatsForecast and TimeGPT based on time series data characteristics. Use when unsure which model performs best. Trigger with 'auto-select model', 'choose...
Detects anomalies in time series data using TimeGPT. Identifies outliers, level shifts, and trend breaks without model training. Use when identifying anomalies, outliers, or unusual patterns in time series. Tri...
Guides TimeGPT lab environment setup including Python dependencies, API key configuration, smoke testing, experiment workflows, and optional CI/CD integration. Inspects environment docs and scripts to provide s...
Analyzes Polymarket prediction market contracts and forecasts price movements using TimeGPT. Activates when analyzing prediction markets, forecasting contract outcomes, or evaluating market sentiment. Triggers...
Quantifies the impact of exogenous events on contract prices using TimeGPT and CausalImpact. Triggers on "event impact analysis", "model event effects", "quantify event impact", or "causal analysis".
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.