# harvard-artifacts-collection-data-engineering-analytics

Sets up an end-to-end data pipeline fetching Harvard Art Museums records, loading them into MySQL, and visualising trends in Streamlit.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1900 installs · ★ 5
- Author: reason-machines
- License: LicenseRef-Unknown · policy=link-only · description only; the file stays with the author
- Source: https://github.com/reason-machines/data-skills/tree/HEAD/skills/harvard-artifacts-collection-data-engineering-analytics/SKILL.md
- Updated: 2026-10-09
- HTML: https://affpapa.org/en/nevibecode/skills/harvard-artifacts-collection-data-engineering-analytics

## What it does

This skill guides the agent through an entire pipeline for museum artifact analytics. It extracts records from the Harvard Art Museums API, handling request pacing and multi-page responses. The transformation step unpacks nested JSON into relational tables covering object metadata, images, and color hex percentages.

Data lands in MySQL or TiDB Cloud across foreign-keyed tables. On top of the database, the project supplies over 20 SQL queries along with interactive charts built via Streamlit and Plotly.

The pipeline fails immediately if `HARVARD_API_KEY` or the database credentials in `.env` are omitted.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add reason-machines/data-skills --skill harvard-artifacts-collection-data-engineering-analytics -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/harvard-artifacts-collection-data-engineering-analytics/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/harvard-artifacts-collection-data-engineering-analytics/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add reason-machines/data-skills --skill harvard-artifacts-collection-data-engineering-analytics -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/harvard-artifacts-collection-data-engineering-analytics/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add reason-machines/data-skills --skill harvard-artifacts-collection-data-engineering-analytics -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/harvard-artifacts-collection-data-engineering-analytics/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install reason-machines/data-skills harvard-artifacts-collection-data-engineering-analytics
```

2. **Manually: put the files in place**
- File: `.github/skills/harvard-artifacts-collection-data-engineering-analytics/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add reason-machines/data-skills --skill harvard-artifacts-collection-data-engineering-analytics -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/reason-machines/data-skills --path skills/harvard-artifacts-collection-data-engineering-analytics
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/harvard-artifacts-collection-data-engineering-analytics/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add reason-machines/data-skills --skill harvard-artifacts-collection-data-engineering-analytics -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/reason-machines/data-skills/tree/HEAD/skills/harvard-artifacts-collection-data-engineering-analytics/SKILL.md

## When to use it
- extract museum artifacts from the Harvard API with rate limiting
- transform nested JSON into relational schemas for metadata, images, and colors
- launch a Streamlit dashboard with Plotly charts on top of MySQL or TiDB Cloud
- run analytical SQL queries across art collection datasets

## Example prompts
- Set up an ETL pipeline to load Harvard Art Museums records into MySQL.
- Create a Streamlit dashboard with Plotly charts for museum collection data.
- Generate SQL schema and queries to analyze Harvard artifact colors and metadata.

## Similar
- [indicator-setup](https://affpapa.org/en/nevibecode/skills/indicator-setup.md) — skill · 551 installs
- [geo-data-engineering](https://affpapa.org/en/nevibecode/skills/geo-data-engineering.md) — skill · ★ 35
- [data-engineering](https://affpapa.org/en/nevibecode/plugins/data-engineering.md) — plugin · ★ 41823
- [aws-data-analytics](https://affpapa.org/en/nevibecode/plugins/aws-data-analytics.md) — plugin · ★ 3299
- [indicator-dashboard](https://affpapa.org/en/nevibecode/skills/indicator-dashboard.md) — skill · 570 installs
- [google-analytics-data-api-basics](https://affpapa.org/en/nevibecode/skills/google-analytics-data-api-basics.md) — skill · 7364 installs

From the same set: [reason-machines/data-skills](https://affpapa.org/en/nevibecode/by/reason-machines/data-skills.md) — 74 cards

---
NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md