td-data-preparation
UAF-specific data preparation and validation for time series analysis
UAF-specific data preparation and validation for time series analysis
Leonid Levin''s algorithmic complexity meets playful mutual ingression. Use for: BB(n) prediction markets, Kolmogorov complexity rewards, WEV extraction from proof inefficiencies, Nash equilibrium between exploration (LEVITY) and convergence (LEVIN).
Advanced parameter estimation and optimization for UAF models
Time series specific cross-validation techniques for model validation
Categorical variable encoding using TD_OneHotEncodingFit and Transform
Expert in Move smart contract development on Aptos. Covers modules, resources, abilities, generics, fungible assets, digital assets, testing, security, and advanced patterns.
Create beautiful data visualizations with mathematical elegance, color theory, and narrative design - the "Data is Beautiful" aesthetic.
Validate forecast quality by comparing MASE and sMAPE against benchmarks. Use when detecting model degradation. Trigger with 'validate forecast' or 'check forecast quality'.
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 best model', 'model selection'.
Scaffolds production-ready forecasting experiments with Nixtla libraries. Creates configuration files, experiment harnesses, multi-model comparisons, and cross-validation workflows for StatsForecast, MLForecast, and TimeGPT. Activates when user needs experiment setup, forecasting pipeline creation, model benchmarking, or multi-model comparison framework.
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 best model", "model selection".
Product strategy skill for defining positioning, ICP/JTBD, competitive analysis, moat hypotheses, pricing/packaging, GTM planning, and roadmap prioritization. Use for tasks like turning ideas into a strategy memo, writing OKRs, creating TAM/SAM/SOM, and making trade-off decisions.
Strategic AI council for product vision, innovation, and future planning
Guide revenue analysis using ChartMogul reports. Use when discussing MRR, ARR, churn, retention, cohorts, or subscription metrics. Helps select the right report and interpret results.
Forecast multiple time series in parallel using TimeGPT. Use when processing 10-100+ contracts efficiently. Trigger with 'batch forecast' or 'parallel forecasting'.
Calculate and interpret SaaS growth metrics including MRR, ARR, churn rate, LTV, CAC, NRR, and conversion rates. Use when user mentions metrics, asks about business health, wants to calculate KPIs, or needs help interpreting growth numbers. Provides health checks against industry benchmarks.
Provides expert design guidance for creating truthful, clear, beautiful data visualizations. Focuses on **DESIGN DECISIONS ONLY**—chart selection, color strategy, visual encoding, and validation. Assumes data is accurate and prepared. Auto-activates when user mentions: data viz, dashboard, chart type, visualization, infographic
Expert-level Looker BI, LookML, explores, dimensions, measures, dashboards, and data modeling
Master statistical analysis with hypothesis testing, A/B testing, regression, and statistical methods for data-driven decisions.
Generate comprehensive markdown benchmark reports from forecast accuracy metrics with model comparisons, statistical analysis, and regression detection. Use when analyzing baseline performance, comparing forecast models, or validating model quality. Trigger with 'generate benchmark report', 'analyze forecast metrics', or 'create performance summary'.
Calculate AI-readiness score (0-100%) for any project with project.faf file. Shows Podium tier (Trophy/Gold/Silver/Bronze), identifies strengths and gaps, provides improvement roadmap. Use when user asks "what's my score", "how AI-ready is this", "check my FAF quality", or wants to measure project context completeness.
Generate time series forecasts using TimeGPT, StatsForecast, and MLForecast. Use when forecasting, demand planning, or model comparison is needed. Trigger with 'forecast time series' or 'run Nixtla forecast'.
BI fundamentals with metric definition, KPI calculation, dimensional modeling, dashboard optimization, and data storytelling. 40+ metric examples and calculation patterns.
Generate production-ready Jupyter notebooks showcasing Nixtla forecasting workflows for statsforecast, mlforecast, and TimeGPT. Use when creating demos, building examples, or showcasing forecasting capabilities. Trigger with 'generate demo notebook', 'create Jupyter demo', or 'build forecasting example'.