hv-analysis

Analyze products, companies, concepts, or people using a dual-axis framework and render Markdown to PDF via WeasyPrint.

4|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/macrochen/hv-analysis --skill hv-analysis-macrochen
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: hv-analysis
Source: https://github.com/macrochen/hv-analysis/tree/main
Command: npx skills add https://github.com/macrochen/hv-analysis --skill hv-analysis-macrochen

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires weasyprint, markdown, and includes scripts (resource) components.

What problem does it solve?

横纵分析法深度研究Skill 解决系统性、可重复地对产品/公司/概念/人物进行深入研究并输出专业PDF报告的需求。

Core Features & Use Cases

  • 提供完整的纵向叙事与横向比较框架,帮助用户从历史演变与当前定位看清对比关系。
  • 具有内置生成排版精美PDF报告的工作流,输出可直接分发的文稿。
  • 支持可选资源(scripts/references/assets/)来满足定制化分析与引用需求。
  • 兼容自带脚本 md_to_pdf.py,将 Markdown 渲染为 PDF,并实现一体化工作流。

Quick Start

请以横纵分析法对目标对象进行完整研究,并输出排版精美的PDF研究报告。

Frequently Asked Questions about hv-analysis

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

FAQPage Schema
What is horizontal and vertical analysis for competitive research?

WeasyPrint is used to render Markdown content into a polished, distribution-ready PDF report, integrating the research workflow from drafting to final document output seamlessly.

How do I generate a PDF research report from Markdown analysis?

Use the built-in md_to_pdf.py script to convert Markdown content into a polished PDF report via WeasyPrint, completing the research workflow from analysis to distribution-ready document.

Can I use this dual-axis framework to analyze both companies and concepts?

Yes, the horizontal and vertical analysis framework supports deep research on products, companies, concepts, and people by applying longitudinal storytelling and cross-sectional competitive benchmarking to any target.

Do I need to install WeasyPrint and markdown dependencies to output PDF reports?

Yes, installing WeasyPrint and markdown dependencies is required to execute the md_to_pdf.py script and render Markdown research content into a formatted PDF report.

What is the best way to structure a competitive analysis with diachronic and synchronic perspectives?

The best approach is a dual-axis framework combining diachronic longitudinal storytelling with synchronic cross-sectional benchmarking to map historical evolution against current competitive positioning.