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 StanfordSpezi/SpeziVibe --skill digital-health-compliance-planninggit clone --depth 1 https://github.com/StanfordSpezi/SpeziVibeWrote 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/stanfordspezi/spezivibe/digital-health-compliance-planning)<a href="https://agentmods.dev/skills/stanfordspezi/spezivibe/digital-health-compliance-planning"><img src="https://agentmods.dev/badge/skills/stanfordspezi/spezivibe/digital-health-compliance-planning/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/stanfordspezi/spezivibe/digital-health-compliance-planning"><img src="https://agentmods.dev/badge/skills/stanfordspezi/spezivibe/digital-health-compliance-planning.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 | $0.00039 | $0.01096 |
| Opus 5 | $0.00019 | $0.00548 |
| Sonnet 5 | $0.00008 | $0.00219 |
| Haiku 4.5 | $0.00004 | $0.00110 |
Grade A, and why
digital-health-compliance-planning 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 12d 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compliance Planner
Plan privacy, research, regulatory, and governance requirements for a digital health product in a framework-agnostic way.
When to Use
Use this skill when you need to:
- assess whether a product handles regulated health or research data
- prepare for HIPAA, IRB, FDA, GDPR, or institutional review conversations
- define consent, retention, export, deletion, and audit expectations
- identify compliance work that should shape product scope early
Working Style
Do not jump straight to controls. First understand:
- product purpose
- who the users are
- whether the product is clinical care, research, wellness, operations, or education
- what data is collected, derived, shared, or exported
- which regions, institutions, and partners are involved
Then produce a concise compliance planning brief with assumptions, risks, open questions, and recommended next steps.
Core Questions
Ask about:
- intended use and claims
- user groups such as patients, participants, clinicians, coordinators, or caregivers
- data types collected, inferred, uploaded, or connected from external systems
- whether the product supports research, quality improvement, or direct care
- data storage, processing, and sharing locations
- third-party vendors and subprocessors
- admin access, audit needs, and incident response expectations
- export, deletion, correction, and retention requirements
Compliance Areas To Review
HIPAA and Institutional Privacy
Check whether the product likely handles protected health information or institution-controlled data.
Review:
- what identifiers are present
- who is a covered entity or business associate
- minimum necessary access expectations
- workforce, admin, and support access boundaries
- logging, monitoring, and breach response needs
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.
- 12d ago First seen · 166 lines · 39 tokens per session scan A 9a6f9bd07f78
digital-health-compliance-planning is a skill published in the GitHub repository StanfordSpezi/SpeziVibe (24 stars, last pushed 4d ago), licensed MIT. It adds 39 tokens to every session and 1,096 once invoked, about $0.0002 per session on Opus 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 2026-08-30.
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