skills.rest
zazu-22
zazu-22COMMUNITY
Explore all skills by this author →
GitHub

notebook-creator

Create standardized Jupyter analysis notebooks with DuckDB connections and visualization standards.

Updated Aug 23, 2026
Search Tags:#visualization#jupyter#duckdb#notebook#notebook-template
One-click install
npx skills add https://github.com/zazu-22/ff_data_analytics --skill notebook-creator-zazu-22
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: notebook-creator
Source: https://github.com/zazu-22/ff_data_analytics/tree/main/.claude/_archive_skills/notebook-creator
Command: npx skills add https://github.com/zazu-22/ff_data_analytics --skill notebook-creator-zazu-22

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) and references (resource) components.

What problem does it solve?

This Skill creates analysis Jupyter notebooks for the Fantasy Football Analytics project, following established conventions for data access, transforms, visualizations, and documentation. It accelerates the production of analysis deliverables and ensures consistency.

Core Features & Use Cases

  • Notebook templates and structure for player evaluation, roster health, trades, market trends, and projection quality
  • Standardized DuckDB connection patterns and external Parquet data access
  • Visualization formatting and mart query examples to accelerate analysis
  • Notebook naming conventions and UX decisions to preserve reproducibility

Quick Start

Use the notebook-creator to generate a starter notebook, e.g., roster_health_analysis.ipynb, based on the provided assets/notebook_template.ipynb and standard structure.

Frequently Asked Questions about notebook-creator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a standardized Jupyter notebook for fantasy football analysis?▼

Create a standardized Jupyter notebook using the notebook-creator template, which enforces canonical structure including title, purpose, authorship, DuckDB connection setup with EXTERNAL_ROOT fallback, and visualization standards. This ensures reproducible analysis notebooks across player evaluation, roster health, trades, and market trends.

Can I use DuckDB and external Parquet data in my analysis notebooks?▼

Yes. The notebook-creator establishes standardized DuckDB connection patterns and external Parquet data access through a setup cell that uses EXTERNAL_ROOT and dev.duckdb fallback, enabling consistent data access across analysis notebooks.

What notebook structure and naming conventions does fantasy football analysis require?▼

The notebook-creator applies established conventions for notebook naming, structure, and UX decisions that preserve reproducibility. This includes canonical sections for title, purpose, authorship, objectives, imports, DuckDB setup, mart queries, and visualization formatting.

How do I ensure data freshness and consistency across analysis deliverables?▼

The notebook-creator includes a freshness banner that reports data recency and enforces common mart query standards and visualization formatting, ensuring consistency and transparency across all analysis notebooks.

What analysis types can I generate notebooks for using this tool?▼

Generate notebooks for player analysis, roster health, waiver/free agent analysis, trade analysis, market trends, and projection quality. The tool applies the same standardized structure and visualization conventions across all analysis types.

Related Skills

Explore More Data & Analytics Skills→
clawdataclawdata
24

duckdb

Query local DuckDB warehouses with SQL and ingest CSV, Parquet, and JSON files.

Official
Intermediate
brainbrewlabsbrainbrewlabs
7

reporting

Automates assembly of structured reports from analysis outputs and templates.

Official
Intermediate
alexismanuelalexismanuel

duckdb-data-explorer

Profile CSV, Parquet, and JSON datasets with DuckDB queries.

Community
Advanced
shalevaminshalevamin

jupyter-notebook

Generate structured Jupyter notebooks from templates using a Python helper script.

Community
Basic