add-resource
Add new learning resources (books, articles, courses, papers) to the appropriate resources.md file. Use when user mentions adding, saving, or tracking learning materials.
allowed_tools: Read, Edit, Glob
$ 설치
git clone https://github.com/whanyu1212/artifact-foundry /tmp/artifact-foundry && cp -r /tmp/artifact-foundry/.claude/skills/add-resource ~/.claude/skills/artifact-foundry// tip: Run this command in your terminal to install the skill
SKILL.md
name: add-resource description: Add new learning resources (books, articles, courses, papers) to the appropriate resources.md file. Use when user mentions adding, saving, or tracking learning materials. allowed-tools: Read, Edit, Glob
Add Resource
When the user wants to add a learning resource to their repository:
Instructions
-
Determine which topic folder the resource belongs to:
- foundations/ - Math, statistics, algorithms, systems
- data-analytics/ - EDA, visualization, SQL, data wrangling, business analytics
- machine-learning/ - Traditional ML, supervised/unsupervised learning
- deep-learning/ - Neural networks, transformers, CNNs, etc.
- ml-system-design/ - System design for ML applications
- ai-engineering/ - LLMs, agents, RAG, prompt engineering
- productionization/ - MLOps, deployment, monitoring
- software-engineering/ - Best practices, design patterns
- ai-productivity/ - AI-powered tools (ChatGPT, Claude, Cursor, Copilot, etc.)
- interview-prep/ - Interview-specific materials
-
Read the current resources.md file in that folder
-
Add the resource in consistent format:
- [Title](link) - Author/Source - Brief description of what it covers -
Organize entries:
- Group by type (Books, Articles, Courses, Papers, etc.) if multiple types exist
- Within each type, maintain alphabetical order by title
- If the file is empty, start with a simple list
Examples
Book
- [Designing Data-Intensive Applications](https://dataintensive.net/) - Martin Kleppmann - Deep dive into distributed systems, storage, and processing
Course
- [CS229: Machine Learning](https://cs229.stanford.edu/) - Stanford - Andrew Ng's classic ML course covering fundamentals
Article
- [Attention Is All You Need](https://arxiv.org/abs/1706.03762) - Vaswani et al. - Original transformer architecture paper
Edge Cases
- If unclear which folder: Ask the user or suggest the most relevant one
- If resource fits multiple topics: Add to primary topic and note cross-reference
- If resources.md doesn't exist yet: Create it with proper header
Repository

whanyu1212
Author
whanyu1212/artifact-foundry/.claude/skills/add-resource
2
Stars
0
Forks
Updated1d ago
Added6d ago