Skill UI

Enables Claude to analyze historical time series patterns, select the best forecasting model, and predict future values with confidence intervals for sales, traffic, or other time-dependent metrics.

An advanced skill for Scrum Masters that uses Python scripts to analyze raw sprint data exported from tools like Jira. It provides comprehensive insights including Monte Carlo velocity forecasting, a multi-dimensional team health score (0-100), and tracking of action items and recurring themes from retrospectives. Ideal for process improvement, sprint planning, and stakeholder reporting.

Guides multi-location retailers through demand forecasting, safety stock calculation, replenishment planning, promotional lift estimation, and ABC/XYZ segmentation, blending statistical best practices with ML-ready feature engineering to balance service levels and inventory costs.

Aeon is a scikit-learn compatible toolkit for time series machine learning, covering classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search, and feature extraction on temporal data.

Access over 800,000 economic time series from FRED's API, covering GDP, employment, inflation, interest rates, regional metrics, and more; ideal for macroeconomic analysis, financial research, policymaking, and forecasting workflows.

This skill provides zero-shot time series forecasting using Google's TimesFM foundation model. It forecasts any univariate time series (like sales, sensor data, or weather) without requiring custom model training. The model delivers point forecasts along with calibrated prediction intervals (quantiles), offering a robust and probabilistic view of future trends. It is ideal for rapid, reliable forecasting across diverse time-based datasets.

This tool assists Chief Revenue Officers in building predictable revenue engines. It provides frameworks for revenue forecasting, quota setting, sales modeling, and churn analysis. Key features include NRR and GRR tracking, pricing strategy optimization, and sales capacity planning. Ideal for B2B companies scaling from $1M to $100M ARR.

Guides configuration and optimization of Odoo Sales and CRM, covering pipeline stages, quotation templates, pricelists, sales teams, lead assignment, and forecasting to standardize workflows and boost closure rates.

This advanced agent deeply simulates the cognitive structure, strategic mindset, and analytical frameworks of Bill Gates. It moves beyond simple imitation, allowing users to analyze complex problems through the lens of systemic thinking, platform economics, and long-term strategic planning—reflecting his career from founding Microsoft to global philanthropy. Ideal for business strategy, technology forecasting, and high-level problem decomposition.

A comprehensive framework for optimizing inventory levels and planning replenishment in multi-location retail environments. It covers advanced demand forecasting techniques (e.g., Holt-Winters, ML models), calculating safety stock based on variability, estimating promotional uplift, and generating actionable purchase orders while minimizing stockouts and excess inventory. Ideal for professionals managing complex SKU portfolios across various supply chain systems.

Scikit-learn compatible Python toolkit for time series machine learning: classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search and distance metrics for univariate and multivariate temporal data.

Utilize Google's TimesFM foundation model for zero-shot univariate time series forecasting without training custom models. Supports sales, sensor, and weather data with point forecasts and prediction intervals. Includes mandatory system checks for RAM and GPU before inference to prevent crashes.