About this skill

Problem

Raw data often arrives as CSV, JSON, tables, or chat notes, which is too thin for a review-ready document. Engineers may need to turn metrics, trends, and workflows into a structured Markdown report that can be read in Typora, Markor, or exported to PDF. This skill covers the middle step from raw inputs to a chart-backed report, reducing manual HTML, Mermaid, and styling work.

How It Works And Limits

The skill loads a CSV/JSON source or built-in sample data, then builds a standardized report around the analysis goal. Key capabilities include:

Charts: renders bar, line, and scatter plots with matplotlib, embedded as base64 in Markdown to reduce external file dependencies.
Styling: uses a blue theme, metric cards, striped HTML tables, and a gradient summary block for report presentation.
Flow diagrams: includes Mermaid diagrams for data processing workflows, alongside tables and cards.
Configuration: uses config.yaml to set data_source, chart_type, x_column, y_column, title, and other report parameters.

It fits metric-driven tasks such as market research, sales analysis, competitor comparison, trend prediction, and food-industry analysis. It is better treated as a visualization report generator than a full data-cleaning, statistical-modeling, or business-explanation system, so changing fields, chart types, or output formats usually requires explicit configuration.