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 ThomasMoreAI/legal-skills-open --skill healthcare-ai-privacygit clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-openWrote 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/thomasmoreai/legal-skills-open/healthcare-ai-privacy)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/healthcare-ai-privacy"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/healthcare-ai-privacy/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/thomasmoreai/legal-skills-open/healthcare-ai-privacy"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/healthcare-ai-privacy.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 | $0.00080 | $0.03421 |
| Opus 5.5 | $0.00032 | $0.01368 |
| Sonnet 5.5 | $0.00016 | $0.00684 |
| Haiku 4.5 | $0.00008 | $0.00342 |
Grade A, and why
healthcare-ai-privacy scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Healthcare AI Privacy — HIPAA and AI Act Intersection
Overview
Artificial intelligence in healthcare introduces privacy challenges that sit at the intersection of established health privacy law (HIPAA, HITECH) and emerging AI regulation (EU AI Act, FDA regulatory framework, proposed state AI laws). Clinical decision support (CDS) systems, diagnostic AI, and predictive analytics operate on protected health information, creating obligations under HIPAA while simultaneously falling within the scope of AI-specific regulation when deployed in high-risk clinical contexts. This skill addresses the complete privacy lifecycle of healthcare AI — from training data acquisition through model deployment and patient interaction — ensuring compliance with both health privacy and AI governance frameworks.
Regulatory Landscape
Overlapping Regulatory Frameworks
| Framework | Applicability to Healthcare AI | Key Requirements |
|---|---|---|
| HIPAA Privacy Rule (45 CFR §164) | AI systems processing PHI at covered entities or BAs | Authorization or TPO exception for PHI use; minimum necessary; individual rights |
| HIPAA Security Rule (45 CFR §164.312) | ePHI used in AI training, inference, and storage | Access controls, audit trails, encryption, integrity controls |
| EU AI Act (Regulation 2024/1689) | AI systems deployed in EU healthcare or processing EU patient data | High-risk classification for medical devices; conformity assessment; transparency |
| FDA Regulatory Framework | AI/ML-based Software as a Medical Device (SaMD) | 510(k), De Novo, or PMA pathway; GMLP (Good Machine Learning Practice); total product lifecycle approach |
| FTC Act §5 | AI making health-related decisions affecting consumers | Unfair or deceptive practices; Health Breach Notification Rule for non-HIPAA entities |
| State AI Laws | Emerging state legislation (Colorado AI Act SB24-205, Illinois AI Video Interview Act) | Algorithmic impact assessments; notice and opt-out for automated decisions |
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.
- 1mo ago First seen · 223 lines · 80 tokens per session scan A d641b0a3931f
healthcare-ai-privacy is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (95 stars, last pushed 15d ago), licensed Apache-2.0. It adds 80 tokens to every session and 3,421 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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