nexus-tutorial

A skill for creating runnable Jupyter Notebook tutorials and AI-engineering walkthroughs. Jupyter Notebooks combine explanatory text with code cells that readers can run.

In plain words
What is it for?
Use it to produce a shareable .ipynb notebook, a Makefile, reproducible Python setup instructions, validated environment variables, and copy-ready examples.
Why use it?
It sets a repeatable structure for tutorials, including setup, pinned dependencies, configuration checks, and documented failure cases.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/aayushostwal/nexus/tutorial
Any agent
npx skills add aayushostwal/nexus --skill tutorial
Clone the repo
git clone --depth 1 https://github.com/aayushostwal/nexus

Made for: Claude Code, Codex.

Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,376 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00064 $0.01376
Opus 5 $0.00032 $0.00688
Sonnet 5 $0.00013 $0.00275
Haiku 4.5 $0.00006 $0.00138

Measured 2d ago against content hash 1bc56890c63d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

nexus-tutorial scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/tutorial/SKILL.md · 132 lines

How it starts

The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 type hints on all function signatures
  • Comments explain why — not what (bad: # create list, good: # dedup before sending to avoid API double-charge)
  • One concept per cell; max ~30 lines per cell — split into functions if longer
  • Never hardcode credentials; always use settings.api_key from the Pydantic config

Step 5 — Explanatory Narrative

Between every pair of code cells, add a Markdown cell that:

  1. States the "why" behind the implementation choice (e.g., "We use a ReAct loop here because it lets the agent decide when to call tools vs. answer directly")
  2. Describes the expected output when the cell runs
  3. Lists one or two common errors with their fixes (e.g., "RateLimitError → add time.sleep(1) between calls")

Read the full file on GitHub · 132 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 132 lines · 64 tokens per session scan A 1bc56890c63d

Subscribe to this mod's changes

nexus-tutorial is a skill published in the GitHub repository aayushostwal/nexus (18 stars, last pushed 22d ago), licensed MIT. It adds 64 tokens to every session and 1,376 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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