td-simple-impute
Missing value imputation using TD_SimpleImputeFit
td-smoothing
Signal smoothing and noise reduction techniques
td-spectral-density
Power spectral density estimation for frequency content analysis
td-stationarity-test
Statistical tests for time series stationarity (ADF, KPSS, PP tests)
td-svm
Support Vector Machine for linear and non-linear classification
td-tfidf
Term Frequency-Inverse Document Frequency for text analysis
td-train-test-split
Data splitting for model validation using TD_TrainTestSplit
td-vector-distance
Vector distance calculations for similarity analysis
td-window
Signal windowing for spectral analysis and leakage reduction
control-sessions
Control active sessions by terminating problematic sessions, managing runaway queries, and handling blocking situations
manage-queues
Manage delayed request queues including workload, system, and utility queues to release blocked requests or abort unnecessary items
manage-workloads
**Autonomously create** filters, throttles, and classification rules to implement new workloads or manage workload lifecycle in response to changing operational needs
monitor-queries
Track query execution using real-time resources, analyze query bands, access query logs, and identify performance patterns across the Teradata system
monitor-resources
Monitor AMP processor load, system physical resources, and capacity using real-time resources to track system health and identify performance bottlenecks
monitor-sessions
Monitor active Teradata sessions using real-time resources, view SQL execution details, identify blocking issues, and optionally take control actions
monitor-workloads
Monitor workload definitions, distribution, and TASM statistics using real-time resources to understand classification effectiveness and workload performance
analyze-performance
Analyze system performance using throttle statistics, query logs, and resource metrics to identify bottlenecks and optimization opportunities
optimize-throttles
Analyze throttle behavior, recommend optimal configurations, and autonomously create/modify throttles to balance resource allocation and meet performance SLAs
tune-workloads
Analyze workload classification and **autonomously configure** classification rules, filters, and priorities to improve accuracy and meet business requirements
td-acf
Auto-correlation analysis for time series dependency and pattern detection
td-arima-forecast
ARIMA-based time series forecasting for trend and seasonal predictions
td-arima
ARIMA modeling for time series forecasting
td-arimaestimate
ARIMA parameter estimation for seasonal and non-seasonal AR, MA, ARMA, and ARIMA models
td-attribution
Marketing attribution modeling and analysis
td-change-point
Change point detection in time series for structural breaks
td-classification-evaluator
Classification model evaluation and metrics calculation
td-column-transformer
Advanced column transformation and feature engineering
td-convolution
Convolution operations for signal processing and filtering
td-correlation
Signal correlation analysis for similarity and delay detection
td-cross-validation
Time series specific cross-validation techniques for model validation
td-data-preparation
UAF-specific data preparation and validation for time series analysis
td-data-profiling
Comprehensive data profiling and quality assessment using Teradata ClearScape Analytics descriptive statistics functions
td-decision-forest
Decision forest ensemble classifier for robust predictions
td-decision-tree
Decision tree classifier for categorical prediction and rule extraction
td-detrend
Signal detrending for baseline correction and trend removal
td-dfft
Fourier transformation for frequency domain analysis
td-diff
Time series differencing for stationarity and trend removal
td-fft
Fast Fourier Transform for frequency domain analysis and spectral decomposition
td-filter
Digital filtering for noise reduction and signal enhancement
td-glm
Comprehensive Generalized Linear Model analytics for regression and classification
td-hierarchical-clustering
Hierarchical clustering for nested data grouping
td-ifft
Inverse Fast Fourier Transform for time domain reconstruction
td-kmeans
K-means clustering for customer segmentation and data grouping
td-linear-regression
Linear regression analysis for continuous target prediction
td-logistic-regression
Logistic regression for binary and multinomial classification
td-model-selection
Automated model selection and comparison for optimal forecasting
td-movavg-forecast
Moving average based forecasting for smoothed predictions
td-naive-bayes
Naive Bayes classifier for probabilistic classification
plantuml
Generate PlantUML diagrams from text descriptions and convert them to PNG/SVG images. Use when asked to "create a diagram", "generate PlantUML", "convert puml to image", "extract diagrams from markdown", or "prepare markdown for Confluence". Supports all PlantUML diagram types including UML (sequence, class, activity, state, component, deployment, use case, object, timing) and non-UML (ER diagrams, Gantt charts, JSON/YAML visualization, mindmaps, WBS, network diagrams, wireframes, and more).
frontend-design
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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