skill CX Codex

harvard-art-museums-data-engineering-pipeline — Claude Code skill

Q: How do I install harvard-art-museums-data-engineering-pipeline in Claude Code?

Run `npx skills add reason-machines/data-skills --skill harvard-art-museums-data-engineering-pipeline -a claude-code`. The skill lands at `~/.claude/skills/harvard-art-museums-data-engineering-pipeline/SKILL.md`.

A skill for building an ETL pipeline on Harvard Art Museums API data: JSON into normalized SQL tables, analytical queries, and a Streamlit dashboard.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓

npx skills add reason-machines/data-skills --skill harvard-art-museums-data-engineering-pipeline -a claude-code

Open on GitHub

What harvard-art-museums-data-engineering-pipeline does

The skill walks through the whole chain, from a Harvard Art Museums API request to an interactive dashboard. Records are pulled page by page with rate limiting in mind, then the nested JSON is split into normalized tables: object metadata, images, and colors each get their own table, joined by objectid. The schema is created during the load step.

Code samples are Python. requests handles fetching, pandas does the reshaping, mysql-connector-python writes to the database, and plotly plus streamlit cover the visuals. Analytics rest on a set of ready-made SQL queries against the loaded tables.

You need a Harvard Art Museums API key and a MySQL or TiDB Cloud database before anything runs. Credentials live in .env: HARVARD_API_KEY, DB_HOST, DB_PORT, DB_USER, DB_PASSWORD, DB_NAME. Leave that file empty and both the fetch and the load fail. The dashboard starts with streamlit run app.py and serves at http://localhost:8501.

What it helps with

pull objects from the Harvard Art Museums API across pages
flatten nested JSON into normalized SQL tables
design a relational schema with foreign keys for a collection
write analytical SQL queries over the collected data
put together a Streamlit dashboard with Plotly charts

Example prompts for the agent

Build an ETL pipeline that pulls objects from the Harvard Art Museums API into MySQL
Set up a normalized schema for object metadata, images, and colors
Create a Streamlit dashboard with Plotly charts for the collection data

How to install harvard-art-museums-data-engineering-pipeline

1Skills CLI (Vercel)

npx skills add reason-machines/data-skills --skill harvard-art-museums-data-engineering-pipeline -a claude-code

2Manually: put the files in place

~/.claude/skills/harvard-art-museums-data-engineering-pipeline/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/harvard-art-museums-data-engineering-pipeline/

1Skills CLI (Vercel)

npx skills add reason-machines/data-skills --skill harvard-art-museums-data-engineering-pipeline -a codex

2Manually: put the files in place

.agents/skills/harvard-art-museums-data-engineering-pipeline/SKILL.md

For all projects use ~/.agents/skills/

1Skills CLI (Vercel)

npx skills add reason-machines/data-skills --skill harvard-art-museums-data-engineering-pipeline -a cursor

2Manually: put the files in place

.cursor/skills/harvard-art-museums-data-engineering-pipeline/SKILL.md

Cursor also reads .agents/skills/ and .claude/skills/

1GitHub CLI

gh skill install reason-machines/data-skills harvard-art-museums-data-engineering-pipeline

2Manually: put the files in place

.github/skills/harvard-art-museums-data-engineering-pipeline/SKILL.md

1Skills CLI (Vercel)

npx skills add reason-machines/data-skills --skill harvard-art-museums-data-engineering-pipeline -a gemini-cli

2Platform CLI

gemini skills install https://github.com/reason-machines/data-skills --path skills/harvard-art-museums-data-engineering-pipeline

Manually: put the files in place

.devin/skills/harvard-art-museums-data-engineering-pipeline/SKILL.md

The legacy .windsurf/skills/ path still works

Skills CLI (Vercel)

npx skills add reason-machines/data-skills --skill harvard-art-museums-data-engineering-pipeline -a opencode

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about harvard-art-museums-data-engineering-pipeline

How do I install harvard-art-museums-data-engineering-pipeline in Claude Code?

Run npx skills add reason-machines/data-skills --skill harvard-art-museums-data-engineering-pipeline -a claude-code. The skill lands at ~/.claude/skills/harvard-art-museums-data-engineering-pipeline/SKILL.md.

What does harvard-art-museums-data-engineering-pipeline do?

It guides you through an end-to-end pipeline: fetching from the Harvard Art Museums API, reshaping JSON into normalized tables, loading SQL, and a Streamlit dashboard with Plotly charts.

What do I need before running it?

A Harvard Art Museums API key and a MySQL or TiDB Cloud database. The key and connection settings go into .env.

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