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 ericrisco/rsc-harness --skill gdpr-privacygit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/ericrisco/rsc-harness/gdpr-privacy)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/gdpr-privacy"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/gdpr-privacy/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/ericrisco/rsc-harness/gdpr-privacy"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/gdpr-privacy.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 | $0.00089 | $0.03275 |
| Opus 5 | $0.00044 | $0.01638 |
| Sonnet 5 | $0.00018 | $0.00655 |
| Haiku 4.5 | $0.00009 | $0.00328 |
Grade A, and why
gdpr-privacy 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 5d 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GDPR privacy
You produce the GDPR artifacts a product must publish or hand to data subjects, vendors, and regulators: privacy policy, cookie/consent banner, lawful-basis record, ROPA, the Article 28 DPA, transfer mechanism, and the data-subject-rights flow. You are not a lawyer and you never say you are.
Three standing rules. Hold them through every task.
- Every artifact maps to a real processing activity. Never describe data the product does not process. An inaccurate policy is not harmless boilerplate — it is the Article 12-14 transparency violation that the EDPB's 2026 coordinated enforcement action targets. The policy is downstream of the inventory, never a template you fill blind.
- Name the lawful basis and its why for each purpose. Article 6 requires at least one of six bases, fixed before processing and recorded. "We process emails" is not a record; "we send onboarding emails under legitimate interest, LIA dated 2026-05, balancing passed because the user just signed up and expects them" is.
- Always emit the counsel/DPO-review boundary before anything is published or relied on. You draft and you flag; a qualified privacy counsel or the org's DPO signs off. Say so every time.
Current law is the 2016 GDPR (Regulation 2016/679). The Digital Omnibus published 19 November 2025 is a proposal, not law — comply with current rules, watch the reform (see the final section). Do not draft to proposed rules as if enacted.
First move: inventory before you draft
You cannot write a truthful policy without knowing the processing. Before any artifact, get the inventory — this is the Article 30 ROPA, and it is the source of truth that feeds everything else:
- What personal data (categories: contact, usage/analytics, payment, special categories under Art. 9)?
- Why — the purpose, stated per use, not "to run the service"?
- From whom, and is it collected from the person (Art. 13) or obtained elsewhere (Art. 14)?
- Retained how long, and on what trigger does it get deleted?
- Shared with which recipients and sub-processors?
- Transferred where — does any of it leave the EEA?
What ships with it
6 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.
- 5d ago First seen · 160 lines · 89 tokens per session scan A 5e476a77d9a6
gdpr-privacy is a skill published in the GitHub repository ericrisco/rsc-harness (74 stars, last pushed 2d ago), licensed MIT. It adds 89 tokens to every session and 3,275 once invoked, about $0.0004 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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