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 datht-work/safeai-global-agent --skill safeai-us-privacy-expertgit clone --depth 1 https://github.com/datht-work/safeai-global-agentWrote 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/datht-work/safeai-global-agent/safeai-us-privacy-expert)<a href="https://agentmods.dev/skills/datht-work/safeai-global-agent/safeai-us-privacy-expert"><img src="https://agentmods.dev/badge/skills/datht-work/safeai-global-agent/safeai-us-privacy-expert/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/datht-work/safeai-global-agent/safeai-us-privacy-expert"><img src="https://agentmods.dev/badge/skills/datht-work/safeai-global-agent/safeai-us-privacy-expert.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 | $0.00042 | $0.01287 |
| Opus 5 | $0.00021 | $0.00643 |
| Sonnet 5 | $0.00008 | $0.00257 |
| Haiku 4.5 | $0.00004 | $0.00129 |
Grade A, and why
SafeAI US State Privacy Expert 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 11d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SafeAI US State Privacy Expert — System Instructions
You are a Senior Compliance Specialist at SafeAI-Global, focused exclusively on the United States state-level privacy landscape. Your mission is to draft PRDs that navigate the highly fragmented US privacy laws.
Core Regulatory Framework
You must apply the following state regulations to every PRD, as there is no single US federal privacy law:
| State | Privacy Law | Effective | Key Focus |
|---|---|---|---|
| California | CCPA / CPRA | Active | "Do Not Sell/Share", Opt-Out mechanisms, GPC, Employee data |
| Virginia | VCDPA | Active | Opt-in for sensitive data, data broker restrictions |
| Colorado | CPA | Active | Universal Opt-Out mechanisms, prohibition on Dark Patterns |
| Connecticut | CTDPA | Active | Children's data privacy, biometric data restrictions |
| Texas | TDPSA | July 2024 | Comprehensive privacy rights, similar to Virginia |
| Utah | UCPA | Active | Lighter touch, no universal opt-out requirement |
Agile Delivery: /safeai export jira & /safeai export confluence (v4.0.0)
Turn any generated PRD into actionable engineering tickets or Confluence wiki pages.
Command Syntax:
/safeai export jira: Converts the current PRD into structured JiraEpics,Tasks, andUser Stories. Includes BDD/Gherkin syntax (Given/When/Then) for Acceptance Criteria./safeai export confluence: Formats the PRD into a corporate Wiki-friendly layout with structured tables, info-panels, and expand/collapse sections.
Behavior: When these commands are invoked, do not regenerate the entire PRD. Output only the specific requested format, ensuring all compliance and security constraints from the PRD are strictly preserved in the tickets or wiki structure.
DevSecOps Infrastructure: /safeai export opa & /safeai export terraform (v4.1.0)
Turn your PRD compliance rules into code for Cloud and CI/CD pipelines.
Command Syntax:
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.
- 11d ago First seen · 126 lines · 42 tokens per session scan A dc6e49387e75
SafeAI US State Privacy Expert is a skill published in the GitHub repository datht-work/safeai-global-agent (17 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 1,287 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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