← ClaudeAtlas

nexus-tutoriallisted

Use for creating executable Jupyter tutorials and AI engineering walkthroughs with runnable cells. Trigger on requests for step-by-step guides, notebook-based teaching, or shareable code-first learning content. Prioritize reproducibility, clarity, and copy-paste-ready outputs. When in doubt, use this skill.
aayushostwal/nexus · ★ 10 · AI & Automation · score 76
Install: claude install-skill aayushostwal/nexus
# Tutorial Generation Protocol Produce complete, executable Jupyter Notebooks that work on the first run. --- ## Compatibility - Language: Python 3.10+ - Output: `.ipynb` file + `Makefile` - Style: PEP 8, GitHub-renderable Markdown, clean saved outputs --- ## Workflow ### Step 1 — Reproducibility Block Begin every notebook with: 1. Shell commands cell: `python -m venv .venv && source .venv/bin/activate` 2. `pip install` cell with all required libraries (pin versions: `langchain==0.2.0`) 3. Kernel check instructions as a Markdown cell 4. `Makefile` with `make jupyter` target and Python version pin (e.g. `.python-version` file) ### Step 2 — Production-Ready Configuration 1. Create a Pydantic `BaseSettings` class to validate all environment variables on startup 2. Load secrets with `python-dotenv`; raise an explicit `ValueError` with a helpful message if a key is missing 3. Document every production failure mode: missing keys, rate limits, model errors, network timeouts ### Step 3 — Structural Outline Create Markdown cells with headers H1–H3: - **H1 — Title:** What the tutorial builds in one sentence - **H2 — Objective:** One paragraph "what you will build and why" - **H2 — Prerequisites:** List exact API keys, GPU requirements, or account setup steps - **H2 — Architecture Diagram:** Mermaid diagram showing end-to-end system flow ### Step 4 — Code Implementation Rules for every code cell: - Self-contained or explicitly references previously defined variables - Python ty