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

$ Instalar

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


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

  1. 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
  2. Read the current resources.md file in that folder

  3. Add the resource in consistent format:

    - [Title](link) - Author/Source - Brief description of what it covers
    
  4. 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