data-analysis

The data-analysis skill is designed to help users analyze spreadsheet-based datasets and transform raw Excel or CSV data into actionable insights. It supports spreadsheet exploration, statistical analysis, reporting, and visualization workflows for business, finance, and operational data. By working directly with spreadsheet files such as XLSX, XLS, and CSV formats, the skill enables users to better understand trends, identify patterns, evaluate performance metrics, and summarize large datasets in a structured and readable format. The skill is intended to simplify data interpretation and reduce the manual effort required to generate reports or uncover meaningful insights from tabular data.

The skill includes capabilities for exploratory analysis, statistical summaries, trend detection, visualization generation, and report creation. It integrates with spreadsheet-focused MCP tools such as read_xlsx, analyze_spreadsheet, create_chart, and pivot_table to process and analyze data. Users can request dataset overviews, investigate specific business questions, generate comparison charts, examine correlations, and create insight reports with recommendations. Output is typically provided in markdown report format and may include sections such as data overview, key insights, visualizations, and recommendations. Optional inputs allow users to define analysis goals and preferred output formats.

This skill is useful for analysts, finance teams, operations managers, business users, and anyone working with spreadsheet data. Common use cases include sales analysis, revenue tracking, customer data analysis, performance reporting, and trend visualization. It can support both general exploratory workflows and targeted analytical questions, making it suitable for departments across organizations. The bilingual language support for English and Chinese also makes it adaptable for international or multilingual teams handling spreadsheet-driven reporting and analysis tasks.