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 LegalQuants/lq-skills --skill privacy-notice-eugit clone --depth 1 https://github.com/LegalQuants/lq-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/legalquants/lq-skills/privacy-notice-eu)<a href="https://agentmods.dev/skills/legalquants/lq-skills/privacy-notice-eu"><img src="https://agentmods.dev/badge/skills/legalquants/lq-skills/privacy-notice-eu/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/legalquants/lq-skills/privacy-notice-eu"><img src="https://agentmods.dev/badge/skills/legalquants/lq-skills/privacy-notice-eu.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 | $0.00166 | $0.06964 |
| Opus 5 | $0.00083 | $0.03482 |
| Sonnet 5 | $0.00033 | $0.01393 |
| Haiku 4.5 | $0.00017 | $0.00696 |
Grade A, and why
privacy-notice-eu 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 — 457 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pan-EU GDPR Privacy Notice Generator
Generate jurisdiction-aware, GDPR-compliant privacy notices as professional .docx documents.
Who this is for, and what kind of work this is
Operator. This skill is written for a privacy practitioner — an in-house data protection lead or DPO, or the privacy/commercial lawyer supporting them. It can be run by a non-lawyer (a founder or ops owner drafting a first notice), but then the output must be routed to qualified counsel before publication, not published on the skill's say-so. No special AI fluency is assumed beyond answering the intake questions in plain language.
Work shape. The work is bounded and document-centric: a single privacy notice assembled from a fixed template, the loaded jurisdiction reference, and the controller's intake — pattern-matched against the Art. 13/14 disclosure checklist, not open-ended advisory. The skill stays conservative inside that pattern and hands anything outside it back to counsel (see Confidence and what gets handed back below).
Status of the output. The notice itself is a client-facing document; the gap findings and assumptions this skill surfaces alongside it (e.g. "no DPA on file for processor X") are candid drafting observations — not legal advice, and not in themselves a privileged work product. Treat their storage and sharing per your firm's work-product and privilege policy.
Workflow Overview
1. SCOPE → Notice type, jurisdiction(s), template choice
2. INTAKE → Type-driven collection: controller info, data inventory, legal bases
3. DRAFT → Generate notice from template + type profile + collected info
4. VERIFY → Art. 13/14 compliance check + type-specific checks + AI Act check
5. DELIVER → .docx output via docx skill
Confidence and what gets handed back
A finished, formatted .docx reads as authoritative — which is the risk: a reviewing lawyer is tempted to ratify it rather than re-examine it. So the skill must make its own certainty visible and must NOT smooth contested points into confident prose. Tag every non-trivial legal position the notice relies on:
What ships with it
10 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.
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 · 457 lines · 166 tokens per session scan A b6c83e95bfcf
privacy-notice-eu is a skill published in the GitHub repository LegalQuants/lq-skills (54 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 166 tokens to every session and 6,964 once invoked, about $0.0008 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…