Agent Skills Hub

financial-statements

Generate financial statements (P&L, balance sheet, cash flow) with period-over-period comparisons, variance analysis, and GAAP compliance checks.

Data Analysis Helper

A versatile data analysis assistant for loading datasets, performing statistical calculations, visualizing trends, and generating professional summary reports.

variance-analysis

Decompose financial variances into drivers with narrative explanations and waterfall analysis. Optimize budget vs. actual reporting, P&L commentary, and forecast reconciliation.

sql-pro

Expert SQL agent for modern database systems, query optimization, HTAP environments, and data architecture patterns. Optimize performance, schema design, and analytical workloads effectively.

article-analysis

Analyze and summarize web content like articles, newsletters, and blog posts into structured markdown reports. Perfect for content consumption, knowledge management, and research.

geospatial-analysis

Analyze geospatial data using GeoPandas with proper coordinate projections for accurate distance, filtering, and spatial relationship calculations.

seaborn

Statistical visualization library for Python. Create publication-quality graphics like box plots, heatmaps, and violin plots with pandas integration and automatic statistical estimation.

analytics-interpretation

Analyze GA4 and GSC performance data with automated benchmarks, status indicators, and actionable content optimization insights.

loading-insurance-data

Load, validate, and preprocess weekly insurance policy CSV data with intelligent period detection and standardization.

changelog

Automated runtime observability changelog for Claude Code development sessions, tracking file changes, test results, and git commits.

meteorology-driver-classification

Classify and group meteorological and environmental variables into specific driver categories for consistent attribution analysis and environmental modeling.

scikit-learn

Classical machine learning with scikit-learn. Use for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building robust ML pipelines in Python.