harvard-artifacts-etl-analytics

harvard-artifacts-etl-analytics is a skill for Claude Code, Codex from Aradotso/data-skills. It costs 30 tokens per session (2,793 once invoked), scanned A, original, no licence file.

A data workflow for collecting Harvard Art Museums API data, transforming it with Python and SQL, and showing results in Streamlit dashboards.

In plain words
What is it for?
Building ETL pipelines—processes that extract, transform, and load data—and analytics dashboards for Harvard Art Museums data.
Why use it?
It helps turn museum API data into stored, analysable information and visual reports.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Building ETL pipelines—processes that extract, transform, and load data—and analytics dashboards for Harvard Art Museums data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aradotso/data-skills/harvard-artifacts-etl-analytics
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.

Any agent
npx skills add Aradotso/data-skills --skill harvard-artifacts-etl-analytics
Clone the repo
git clone --depth 1 https://github.com/Aradotso/data-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for harvard-artifacts-etl-analytics

README.md
[![agentmods](https://agentmods.dev/badge/skills/aradotso/data-skills/harvard-artifacts-etl-analytics/github.svg)](https://agentmods.dev/skills/aradotso/data-skills/harvard-artifacts-etl-analytics)
Your own site
<a href="https://agentmods.dev/skills/aradotso/data-skills/harvard-artifacts-etl-analytics"><img src="https://agentmods.dev/badge/skills/aradotso/data-skills/harvard-artifacts-etl-analytics/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for harvard-artifacts-etl-analytics

Your own site · 80×15
<a href="https://agentmods.dev/skills/aradotso/data-skills/harvard-artifacts-etl-analytics"><img src="https://agentmods.dev/badge/skills/aradotso/data-skills/harvard-artifacts-etl-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,793 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown 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 5.1 $0.00030 $0.02793
Opus 5 $0.00015 $0.01396
Sonnet 5 $0.00006 $0.00559
Haiku 4.5 $0.00003 $0.00279

Measured 10d ago against content hash 76e15186abc6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

harvard-artifacts-etl-analytics scanned grade A with 1 finding 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 10d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

response = requests.get(url, params=params)
skills/harvard-artifacts-etl-analytics/SKILL.md · 449 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

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. 10d ago First seen · 449 lines · 30 tokens per session scan A 76e15186abc6

Subscribe to this mod's changes

harvard-artifacts-etl-analytics is a skill published in the GitHub repository Aradotso/data-skills (5 stars, last pushed 1mo ago), with no licence file. It adds 30 tokens to every session and 2,793 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

agent-platform-rag-engine-management

Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…

google/skills · 85 tokens

agent-platform-model-registry

Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.

google/skills · 60 tokens

foundry-config-setup

Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.

microsoft/agent-framework · 65 tokens

google-cloud-solution-agentic-analytics-spark-knowledge-catalog

Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…

google/skills · 138 tokens

training-check

Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.

wanshuiyin/Auto-claude-code-research-in-sleep · 35 tokens

nemo-automodel-launcher-config

Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.

NVIDIA/skills · 30 tokens