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 Kin9Zeus/senior-engineer-skills --skill privacy-compliancegit clone --depth 1 https://github.com/Kin9Zeus/senior-engineer-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/kin9zeus/senior-engineer-skills/privacy-compliance)<a href="https://agentmods.dev/skills/kin9zeus/senior-engineer-skills/privacy-compliance"><img src="https://agentmods.dev/badge/skills/kin9zeus/senior-engineer-skills/privacy-compliance/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/kin9zeus/senior-engineer-skills/privacy-compliance"><img src="https://agentmods.dev/badge/skills/kin9zeus/senior-engineer-skills/privacy-compliance.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 | $0.00179 | $0.03428 |
| Opus 5 | $0.00089 | $0.01714 |
| Sonnet 5 | $0.00036 | $0.00686 |
| Haiku 4.5 | $0.00018 | $0.00343 |
Grade A, and why
privacy-compliance 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 — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Privacy and Compliance Engineering
Almost every product processes personal data — an email address is personal data. The engineering obligations that follow are concrete, buildable, and far cheaper to build in than to retrofit.
Scope note. This skill produces the technical controls and a policy drafted from real data flows. It is not legal advice. For a regulated sector, a high-risk processing activity, or a live regulatory enquiry, the recommendation is to have a qualified privacy lawyer review the output. Say this plainly to the user; do not let it stop you from building the controls, which are the same either way.
The order of work
Every artefact depends on the one above it. Drafting a privacy policy before the inventory means describing a system you have not read.
1. DATA INVENTORY → what is actually collected, from the code
2. POLICY → a document generated from that inventory
3. CONSENT → a mechanism that genuinely gates the scripts
4. RIGHTS PIPELINE → export and deletion, automated end to end
5. GOVERNANCE → DPAs, retention, breach plan, ongoing review
1. Build the data inventory from the code
Never from a form, an interview, or a template. From the schema, the routes and the third-party integrations. What a team believes it collects and what it collects are routinely different.
# Personal data in the schema
grep -rEni '(email|phone|address|birth|dob|ssn|passport|ip_?addr|location|lat|lng|gender|name)' \
--include='*.prisma' --include='*.sql' --include='models*.py' --include='schema.rb' . | head -40
# Every third party that receives data — SDKs, tags, pixels, fonts, embeds
grep -rhoE 'googletagmanager|google-analytics|gtag\(|connect\.facebook\.net|hotjar|segment|mixpanel|posthog|intercom|clarity\.ms|sentry\.io|stripe|paypal|fonts\.googleapis|recaptcha|youtube\.com/embed|player\.vimeo|cdn\.jsdelivr' \
. --exclude-dir={node_modules,.git,dist} | sort -u
# Where data enters
grep -rEn 'req\.body|request\.form|@RequestBody|params\.permit' --exclude-dir=node_modules . | head -30
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/cookie-consent.md 10 KB
- references/data-inventory.md 9.0 KB
- references/governance.md 8.3 KB
- references/rights-pipeline.md 11 KB
- templates/cookie-policy.md 4.6 KB
- templates/deletion-request-flow.md 11 KB
- templates/privacy-policy.es.md 20 KB
- templates/privacy-policy.md 18 KB
- templates/subprocessors.md 3.9 KB
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 · 300 lines · 179 tokens per session scan A 6a106b818bc8
privacy-compliance is a skill published in the GitHub repository Kin9Zeus/senior-engineer-skills (3 stars, last pushed 18d ago), licensed MIT. It adds 179 tokens to every session and 3,428 once invoked, about $0.0009 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 2026-08-31.
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