Agent skill · data analytics · aradotso
harvard-artifacts-etl-pipeline
Build ETL pipelines and analytics dashboards using the Harvard Art Museums API with Streamlit, SQL, and Plotly
Why this skill is useful
Adds executable scripts for building ETL pipelines, SQL database setup, and interactive visualizations that extend the AI's capabilities.
What it needs
Requires mysql-connector-python, pandas, plotly, python-dotenv, requests, streamlit installed locally. Requires harvard account access. About 5k tokens when loaded. Last updated 2026-08-05. 5 stars on the source repository.
What this skill does
Harvard Artifacts ETL Pipeline Skill by ara.so — Data Skills collection. This skill enables AI coding agents to help developers build end-to-end data engineering pipelines using the Harvard Art Museums API. The project demonstrates real-world ETL patterns, SQL database design, analytical queries, and interactive visualization using Streamlit. What This Project Does The Harvard Artifacts Collection application: Fetches artifact data from Harvard Art Museums API with pagination Transforms nested JSON into relational database tables Loads data into MySQL/TiDB Cloud databases Executes analytical SQL queries on artifact metadata, media, and colors Visualizes results through interactive Plotly charts in Streamlit Architecture: API → ETL → SQL → Analytics → Visualization Installation Configuration Environment Variables Create a .env file in the project root: Database Setup Key API Patterns Fetching Artifacts with Pagination ETL Pipeline Implementation Loading Data to SQL Streamlit Dashboard Implementation Common Analytical Queries Troubleshooting API Rate Limiting Database Connection Issues Handling Missing Data Running the Application This skill provides comprehensive guidance for building ETL pipelines with museum APIs, implementing SQL analytics, and creating interactive dashboards with Streamlit.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/harvard-artifacts-etl-pipeline