taiwan-md-knowledge-base

aradotso/trending-skills · updated Apr 8, 2026

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$npx skills add https://github.com/aradotso/trending-skills --skill taiwan-md-knowledge-base
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Skill by ara.so — Daily 2026 Skills collection.

skill.md

Taiwan.md Knowledge Base

Skill by ara.so — Daily 2026 Skills collection.

Taiwan.md is an open-source, AI-native knowledge base about Taiwan built with Astro v5. It uses a Single Source of Truth (SSOT) architecture where all content lives in the knowledge/ directory as Markdown files, and the website is a build-time projection. Features include bilingual support (Traditional Chinese as default + English), an interactive D3.js knowledge graph, and 96+ curated articles across 12 categories.


Installation & Setup

Prerequisites

  • Node.js 18+
  • npm or pnpm

Clone and Install

git clone https://github.com/frank890417/taiwan-md.git
cd taiwan-md
npm install

Development Server

npm run dev
# Site available at http://localhost:4321

Build & Preview

npm run build
npm run preview

Sync Knowledge to Content

bash scripts/sync.sh
# Copies knowledge/ → src/content/ for Astro build

Project Architecture

taiwan-md/
├── knowledge/               ← SSOT: ALL content lives here
│   ├── History/             ← Chinese articles + _Hub.md
│   ├── Geography/
│   ├── Culture/
│   ├── Food/
│   ├── Art/
│   ├── Music/
│   ├── Technology/
│   ├── Nature/
│   ├── People/
│   ├── Society/
│   ├── Economy/
│   ├── Lifestyle/
│   ├── About/               ← Meta content
│   └── en/                  ← English translations (mirrors zh-TW)
│       ├── History/
│       ├── Geography/
│       └── ...
├── scripts/
│   └── sync.sh              ← Syncs knowledge/ → src/content/
├── src/
│   ├── pages/               ← Astro pages
│   ├── layouts/             ← Shared layouts
│   └── content/             ← Build-time projection (DO NOT EDIT)
├── public/
│   └── images/wiki/         ← Cached Wikimedia Commons images
└── docs/                    ← Architecture & roadmap docs

Critical rule: Never edit files in src/content/ directly. Always edit knowledge/ and run scripts/sync.sh.


Content Structure

The 12 Categories

Slug Chinese English
history 歷史 History
geography 地理 Geography
culture 文化 Culture
food 美食 Food
art 藝術 Art
music 音樂 Music
technology 科技 Technology
nature 自然 Nature
people 人物 People
society 社會 Society
economy 經濟 Economy
lifestyle 生活 Lifestyle

Article File Naming

knowledge/
├── Food/
│   ├── _Hub.md              ← Category hub page (literary overview)
│   ├── bubble-tea.md        ← Individual article (zh-TW)
│   └── beef-noodle.md
└── en/
    └── Food/
        ├── _Hub.md          ← English hub page
        ├── bubble-tea.md    ← English translation
        └── beef-noodle.md

Writing Articles

Chinese Article Template (knowledge/[Category]/article-slug.md)

---
title: 珍珠奶茶
description: 台灣最具代表性的飲料文化,從夜市攤車到全球連鎖,珍珠奶茶如何征服世界。
category: food
date: 2024-01-15
tags: [飲食文化, 台灣之光, 夜市]
image: /images/wiki/bubble-tea-abc123.jpg
imageCaption: 台灣珍珠奶茶 | Wikimedia Commons | CC BY-SA 4.0
sources:
  - title: 珍珠奶茶的起源考證
    url: https://example.com/boba-origin
  - title: 台灣飲料市場報告
    url: https://example.com/beverage-report
---

## 30 秒認識

珍珠奶茶(波霸奶茶)誕生於 1980 年代台灣,現已成為全球年產值超過 30 億美元的飲料產業。

## 深度閱讀

### 起源爭議

台南翰林茶館與台中春水堂都聲稱是珍珠奶茶的發明者...

### 全球擴張

2010 年代,珍珠奶茶席捲歐美亞各大城市...

## 為什麼重要

珍珠奶茶不只是一杯飲料,它是台灣軟實力的最佳代言人——在沒有邦交的地方,台灣味道先到了。

## 參考資料

- [珍珠奶茶的起源考證](https://example.com/boba-origin)
- [台灣飲料市場報告](https://example.com/beverage-report)

English Article Template (knowledge/en/[Category]/article-slug.md)

---
title: Bubble Tea
description: Taiwan's most iconic beverage culture — how boba conquered the world from night market stalls to global chains.
category: food
date: 2024-01-15
tags: [food culture, taiwan pride, night market]
image: /images/wiki/bubble-tea-abc123.jpg
imageCaption: Taiwanese Bubble Tea | Wikimedia Commons | CC BY-SA 4.0
sources:
  - title: Origins of Bubble Tea
    url: https://example.com/boba-origin
  - title: Taiwan Beverage Market Report
    url: https://example.com/beverage-report
---

## 30-Second Overview

Bubble tea (boba) was born in 1980s Taiwan and has grown into a global industry worth over $3 billion annually.

## Deep Dive

### The Origin Debate

Both Hanlin Tea Room in Tainan and Chun Shui Tang in Taichung claim to have invented bubble tea...

### Global Expansion

In the 2010s, bubble tea swept across cities in Europe, America, and Asia...

## Why This Matters

Bubble tea isn't just a drink — it's Taiwan's finest soft power ambassador. Where there's no diplomatic recognition, Taiwanese flavor arrived first.

## References

- [Origins of Bubble Tea](https://example.com/boba-origin)
- [Taiwan Beverage Market Report](https://example.com/beverage-report)

Hub Page Template (knowledge/[Category]/_Hub.md)

---
title: 美食
titleEn: Food
description: 台灣的飲食文化是移民歷史、地理環境與創意精神的完美結晶。
category: food
---

## 關於這個分類

台灣是一個以食物說故事的地方...

## 精選文章

這個分類收錄了台灣飲食文化最具代表性的面向...

Frontmatter Reference

Required Fields

---
title: "文章標題"           # Display title
description: "一句話說明"   # Meta description (150 chars max)
category: food             # Must match one of 12 category slugs
date: 2024-01-15           # ISO date format
---

Optional Fields

---
tags: [tag1, tag2]         # Array of tags for knowledge graph
image: /images/wiki/...    # Must be from Wikimedia Commons cache
imageCaption: "..."        # Attribution: Title | Source | License
sources:                   # REQUIRED: clickable URLs, no plain-text refs
  - title: "Source Name"
    url: https://...
---

Adding Images (Wikimedia Commons Policy)

All images must be from Wikimedia Commons with verified CC licenses. Cache them locally:

# Download and cache a Wikimedia image
# Images are stored with MD5-hashed filenames
curl -o public/images/wiki/$(echo "filename.jpg" | md5sum | cut -d' ' -f1).jpg \
  "https://commons.wikimedia.org/wiki/Special:FilePath/Taiwan_landscape.jpg"

Image attribution format in frontmatter:

imageCaption<
how to use taiwan-md-knowledge-base

How to use taiwan-md-knowledge-base on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add taiwan-md-knowledge-base
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/aradotso/trending-skills --skill taiwan-md-knowledge-base

The skills CLI fetches taiwan-md-knowledge-base from GitHub repository aradotso/trending-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/taiwan-md-knowledge-base

Reload or restart Cursor to activate taiwan-md-knowledge-base. Access the skill through slash commands (e.g., /taiwan-md-knowledge-base) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.840 reviews
  • Dhruvi Jain· Dec 8, 2024

    taiwan-md-knowledge-base reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Arya Sanchez· Dec 8, 2024

    taiwan-md-knowledge-base is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Oshnikdeep· Nov 27, 2024

    I recommend taiwan-md-knowledge-base for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Evelyn Garcia· Nov 27, 2024

    Solid pick for teams standardizing on skills: taiwan-md-knowledge-base is focused, and the summary matches what you get after install.

  • Rahul Santra· Nov 23, 2024

    We added taiwan-md-knowledge-base from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ganesh Mohane· Oct 18, 2024

    Useful defaults in taiwan-md-knowledge-base — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Kabir Singh· Oct 18, 2024

    taiwan-md-knowledge-base has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Pratham Ware· Oct 14, 2024

    taiwan-md-knowledge-base fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Dev Kapoor· Sep 21, 2024

    taiwan-md-knowledge-base fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Chinedu Kapoor· Sep 17, 2024

    taiwan-md-knowledge-base is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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