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
1---2name: add-resource3description: Add new learning resources (books, articles, courses, papers) to the appropriate resources.md file. Use when user mentions adding, saving, or tracking learning materials.4---56# Add Resource78When the user wants to add a learning resource to their repository:910## Instructions11121. Determine which topic folder the resource belongs to:13 - foundations/ - Math, statistics, algorithms, systems14 - data-analytics/ - EDA, visualization, SQL, data wrangling, business analytics15 - machine-learning/ - Traditional ML, supervised/unsupervised learning16 - deep-learning/ - Neural networks, transformers, CNNs, etc.17 - ml-system-design/ - System design for ML applications18 - ai-engineering/ - LLMs, agents, RAG, prompt engineering19 - productionization/ - MLOps, deployment, monitoring20 - software-engineering/ - Best practices, design patterns21 - ai-productivity/ - AI-powered tools (ChatGPT, Claude, Cursor, Copilot, etc.)22 - interview-prep/ - Interview-specific materials23242. Read the current resources.md file in that folder25263. Add the resource in consistent format:27 ```markdown28 - [Title](link) - Author/Source - Brief description of what it covers29 ```30314. Organize entries:32 - Group by type (Books, Articles, Courses, Papers, etc.) if multiple types exist33 - Within each type, maintain alphabetical order by title34 - If the file is empty, start with a simple list3536## Examples3738### Book39```markdown40- [Designing Data-Intensive Applications](https://dataintensive.net/) - Martin Kleppmann - Deep dive into distributed systems, storage, and processing41```4243### Course44```markdown45- [CS229: Machine Learning](https://cs229.stanford.edu/) - Stanford - Andrew Ng's classic ML course covering fundamentals46```4748### Article49```markdown50- [Attention Is All You Need](https://arxiv.org/abs/1706.03762) - Vaswani et al. - Original transformer architecture paper51```5253## Edge Cases5455- If unclear which folder: Ask the user or suggest the most relevant one56- If resource fits multiple topics: Add to primary topic and note cross-reference57- If resources.md doesn't exist yet: Create it with proper header
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