reporting

Generate HTML, PDF, and Markdown reports with tables and graphs.

Updated May 9, 2026

Search Tags:#data visualization #HTML #report generation #Markdown #PDF

Ready to run

npx skills add https://github.com/LeandroBenjaminL/lend-ai --skill reporting-leandrobenjaminl

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: reporting
Source: https://github.com/LeandroBenjaminL/lend-ai/tree/main/skills/reporting
Command: npx skills add https://github.com/LeandroBenjaminL/lend-ai --skill reporting-leandrobenjaminl

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, styler, matplotlib, seaborn, jinja2, reportlab, and includes scripts (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the generation of professional reports, saving time and ensuring consistency in your analysis presentations.

Core Features & Use Cases

Report Generation: Create HTML, PDF, and Markdown reports with tables, graphs, and conclusions.
Automation: Automate the production of periodic reports.
Format Flexibility: Export results to various formats for different audiences.
Use Case: Ideal for data analysts who need to present their findings in a format accessible to non-technical stakeholders.

Quick Start

Generate a report from the analysis data in 'analysis_data.csv' and export it as a PDF.

Frequently Asked Questions about reporting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate report generation in HTML, PDF, and Markdown formats?▼

Automate report generation by structuring analysis data with pandas and rendering it through jinja2, matplotlib, seaborn, and reportlab to produce HTML, PDF, and Markdown outputs with tables, graphs, and conclusions. It is designed for data analysis workflows to ensure consistency and save time.

What is the best way to convert data analysis results into a PDF report for non-technical stakeholders?▼

Converting data analysis results into a PDF report for non-technical stakeholders is done by using pandas and styler to format tables, matplotlib and seaborn for visualizations, and reportlab to render the final document. This approach tailors technical findings into an accessible format with automated conclusions.

Do I need pandas and jinja2 to generate Markdown reports from CSV data?▼

Yes, generating Markdown reports from CSV data requires pandas for data manipulation and jinja2 for templating, alongside styler, matplotlib, seaborn, and reportlab for formatting and rendering. These dependencies enable the automated inclusion of tables and graphs in the output.

Can I use matplotlib and seaborn graphs in automated HTML report generation?▼

Yes, you can use matplotlib and seaborn graphs in automated HTML report generation. The process integrates these visualization libraries with pandas dataframes and jinja2 templates to embed visual elements and tables directly into the final HTML output for technical and non-technical audiences.

How does automated report formatting handle tables and conclusions for periodic analysis?▼

Automated report formatting handles periodic analysis by applying pandas and styler to structure data tables, then uses jinja2 templates to append textual conclusions. This ensures consistent formatting across HTML, PDF, and Markdown outputs for recurring reporting workflows.