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 JayRHa/AgentSkills --skill gdpr-data-mappergit clone --depth 1 https://github.com/JayRHa/AgentSkillsWrote 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/jayrha/agentskills/gdpr-data-mapper)<a href="https://agentmods.dev/skills/jayrha/agentskills/gdpr-data-mapper"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/gdpr-data-mapper/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/jayrha/agentskills/gdpr-data-mapper"><img src="https://agentmods.dev/badge/skills/jayrha/agentskills/gdpr-data-mapper.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 | $0.00127 | $0.01084 |
| Opus 5.5 | $0.00051 | $0.00434 |
| Sonnet 5.5 | $0.00025 | $0.00217 |
| Haiku 4.5 | $0.00013 | $0.00108 |
Grade A, and why
gdpr-data-mapper 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GDPR Data Mapper
Overview
Produce a clear, auditable map of personal-data processing and the core GDPR artifacts that depend on it. Output is a structured draft to be reviewed by a DPO or counsel — this skill does not give legal advice.
Keywords: GDPR, data mapping, RoPA, Article 30, record of processing, lawful basis, consent, legitimate interest, retention schedule, data subject rights, DSAR, data minimization, special category data, processor, controller, cross-border transfer, DPIA.
Workflow
- Inventory processing activities. List each distinct purpose for which personal data is used (e.g. "account management", "marketing emails", "fraud detection"). One activity per purpose.
- For each activity, capture the RoPA fields (see
templates/ropa-template.md): controller/processor role, purpose, data categories, data subjects, recipients, retention, transfers, and security measures. - Classify the data. Flag special category data (health, biometrics, religion, etc., Art. 9) and children's data — these need stronger justification. Apply data minimization: challenge every field ("why do we hold this?").
- Determine the lawful basis for each activity using the decision guide in
references/lawful-basis-guide.md. Exactly one of the six bases per purpose; document the reasoning. For legitimate interest, note that a balancing test (LIA) is required. - Set retention. Define a concrete retention period and trigger per data category (see
references/retention-and-rights.md). "Indefinite" is not acceptable. - Map data-subject rights readiness. For each activity, note how access, erasure, rectification, portability, restriction, and objection would be fulfilled — and any blockers (e.g. data in backups, third parties).
- Flag transfers and DPIA triggers. Note any transfers outside the EEA (and the safeguard: adequacy decision, SCCs) and whether the activity likely needs a DPIA (large-scale, special category, systematic monitoring).
- Summarize risks and gaps — missing basis, over-retention, undocumented processors, no DSAR path.
What ships with it
3 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.
- 1mo ago First seen · 69 lines · 127 tokens per session scan A 9859d85e7ab7
gdpr-data-mapper is a skill published in the GitHub repository JayRHa/AgentSkills (12 stars, last pushed 2mo ago), licensed MIT. It adds 127 tokens to every session and 1,084 once invoked, about $0.0005 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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