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 vaquarkhan/compliance-agent-skills --skill us-state-privacy-lawsgit clone --depth 1 https://github.com/vaquarkhan/compliance-agent-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/vaquarkhan/compliance-agent-skills/us-state-privacy-laws)<a href="https://agentmods.dev/skills/vaquarkhan/compliance-agent-skills/us-state-privacy-laws"><img src="https://agentmods.dev/badge/skills/vaquarkhan/compliance-agent-skills/us-state-privacy-laws/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/vaquarkhan/compliance-agent-skills/us-state-privacy-laws"><img src="https://agentmods.dev/badge/skills/vaquarkhan/compliance-agent-skills/us-state-privacy-laws.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 | $0.00189 | $0.02080 |
| Opus 5.5 | $0.00076 | $0.00832 |
| Sonnet 5.5 | $0.00038 | $0.00416 |
| Haiku 4.5 | $0.00019 | $0.00208 |
Grade A, and why
us-state-privacy-laws 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
US State Privacy Laws
Overview
After California CPRA, comprehensive state privacy laws form a patchwork of consumer rights, controller/processor roles, and assessment requirements. This skill operationalizes multi-state compliance for organizations processing US residents' personal data—including agent prompts, MCP logs, and LLM vendor chains.
| State | Law | Effective | Notable scope threshold |
|---|---|---|---|
| Virginia | VCDPA Va. Code §59.1-575 | 2023 | 100k consumers or 25k + 50% revenue from PI sale |
| Colorado | CPA C.R.S. §6-1-1301 | 2023 | 100k consumers or 25k + revenue from PI sale |
| Connecticut | CTDPA | 2023 | Similar to VCDPA |
| Utah | UCPA | 2023 | 100k consumers or 25k + 50% revenue from sale |
| Texas | TDPSA | 2024 | Broad—no revenue threshold; SBO threshold |
| Oregon | OCPA | 2024 | 100k consumers or 25k + 25% revenue from sale |
| Montana | MCDPA | 2024 | 50k consumers |
| Iowa | ICDPA | 2024 | 100k consumers |
| Delaware | DPDPA | 2025 | 35k consumers or 10k + 20% revenue from sale |
| New Jersey | NJDPA | 2025 | 100k consumers or 25k + revenue from sale |
Harmonized rights (most states): access, delete, correct, portability, opt-out of targeted advertising, sale, and profiling for significant decisions; sensitive data consent; DPIA/assessment for high-risk processing (varies by state).
Reference: references/us-state-privacy-matrix.md
When to Use
Use this skill when:
- Operating nationally and need state-by-state gap analysis beyond California
- Building unified US privacy program (single notice, multi-state DSAR, GPC/opt-out)
- Agent/LLM systems process state residents' PI in prompts, embeddings, or analytics
- Data protection assessments required (Colorado, Virginia, Connecticut, etc.)
- Universal opt-out (Global Privacy Control, state-specific links) implementation review
- Vendor contracts for LLM/MCP need processor terms aligned to VCDPA/CPA
- Texas TDPSA small business exemption or SBO analysis
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 · 154 lines · 189 tokens per session scan A f3629cbd24df
us-state-privacy-laws is a skill published in the GitHub repository vaquarkhan/compliance-agent-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 189 tokens to every session and 2,080 once invoked, about $0.0008 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 2026-08-31.
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