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.
npx skills add Aradotso/data-skills --skill harvard-artifacts-collection-data-engineeringgit clone --depth 1 https://github.com/Aradotso/data-skillsWrote 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.
[](https://agentmods.dev/skills/aradotso/data-skills/harvard-artifacts-collection-data-engineering)<a href="https://agentmods.dev/skills/aradotso/data-skills/harvard-artifacts-collection-data-engineering"><img src="https://agentmods.dev/badge/skills/aradotso/data-skills/harvard-artifacts-collection-data-engineering/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.
<a href="https://agentmods.dev/skills/aradotso/data-skills/harvard-artifacts-collection-data-engineering"><img src="https://agentmods.dev/badge/skills/aradotso/data-skills/harvard-artifacts-collection-data-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.03073 |
| Opus 5 | $0.00017 | $0.01537 |
| Sonnet 5 | $0.00007 | $0.00615 |
| Haiku 4.5 | $0.00003 | $0.00307 |
Grade A, and why
harvard-artifacts-collection-data-engineering 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 8d 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(self.base_url, params=params) 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.
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.
- 8d ago First seen · 471 lines · 35 tokens per session scan A 9687b929c781
harvard-artifacts-collection-data-engineering is a skill published in the GitHub repository Aradotso/data-skills (5 stars, last pushed 1mo ago), with no licence file. It adds 35 tokens to every session and 3,073 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.
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