PromptEducation & Research
Plan a study session from supplied material
Create explanations and practice questions bounded by a learner's goal and provided sources.
✳Claude
By Dave AIDave AI original
MIT · FreeView prompt
Installable skillMIT
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.
instructions.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 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: ```markdown - [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 ```markdown - [Designing Data-Intensive Applications](https://dataintensive.net/) - Martin Kleppmann - Deep dive into distributed systems, storage, and processing ``` ### Course ```markdown - [CS229: Machine Learning](https://cs229.stanford.edu/) - Stanford - Andrew Ng's classic ML course covering fundamentals ``` ### Article ```markdown - [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--- 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: ```markdown - [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 ```markdown - [Designing Data-Intensive Applications](https://dataintensive.net/) - Martin Kleppmann - Deep dive into distributed systems, storage, and processing ``` ### Course ```markdown - [CS229: Machine Learning](https://cs229.stanford.edu/) - Stanford - Andrew Ng's classic ML course covering fundamentals ``` ### Article ```markdown - [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
COMPATIBILITY & REFERENCES
Platform guidance
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.
Resource notes updated 2026-10-27 · Original instructions by whanyu1212