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 jabrena/plinth --skill 803-regulations-gdprgit clone --depth 1 https://github.com/jabrena/plinthWrote 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/jabrena/plinth/803-regulations-gdpr)<a href="https://agentmods.dev/skills/jabrena/plinth/803-regulations-gdpr"><img src="https://agentmods.dev/badge/skills/jabrena/plinth/803-regulations-gdpr/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/jabrena/plinth/803-regulations-gdpr"><img src="https://agentmods.dev/badge/skills/jabrena/plinth/803-regulations-gdpr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00090 | $0.02232 |
| Opus 5 | $0.00045 | $0.01116 |
| Sonnet 5 | $0.00018 | $0.00446 |
| Haiku 4.5 | $0.00009 | $0.00223 |
Grade A, and why
803-regulations-gdpr 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 7d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GDPR Regulation for Java Enterprise Personal Data Protection
Use this Skill to review Java enterprise applications, APIs, data pipelines, integrations, batch jobs, AI workflows, or operational tooling that collect, store, transform, expose, log, export, or delete personal data.
Apply this Skill to determine what engineering controls, evidence, and escalation paths are needed before the system is released, connected to production data, or used for personal-data processing.
This Skill is not legal advice. It helps Java engineers, architects, tech leads, platform teams, and reviewers identify when GDPR concerns may apply and how to translate data protection expectations into enterprise architecture controls such as personal-data inventories, minimization, purpose limitation, privacy by design, security of processing, data-subject rights workflows, retention and deletion, pseudonymization, transfer-review evidence, breach-response evidence, and privacy-safe logging.
The purpose of this Skill is to increase awareness of potential gaps in the system and create engineering evidence for qualified review. The response produced by this Skill does not represent legal advice, a legal opinion, or a final regulatory determination.
The main question is:
When does a Java enterprise system require GDPR-aware personal-data controls, and what should developers build differently?
External reference: GDPR Regulation (EU) 2016/679.
GDPR chapters summary reference: GDPR chapters summary.
Java engineering examples reference: GDPR engineering examples.
Questionnaire asset: GDPR engineering review questionnaire.
Report template asset: GDPR engineering review report template.
What ships with it
4 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.
- 7d ago First seen · 112 lines · 90 tokens per session scan A c3a0f5cdeabc
803-regulations-gdpr is a skill published in the GitHub repository jabrena/plinth (438 stars, last pushed today), licensed Apache-2.0. It adds 90 tokens to every session and 2,232 once invoked, about $0.0005 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 2026-09-03.
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