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 Jandyoverseas977/Claude-Skills-Governance-Risk-and-Compliance --skill gdpr-compliancegit clone --depth 1 https://github.com/Jandyoverseas977/Claude-Skills-Governance-Risk-and-ComplianceWrote 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/jandyoverseas977/claude-skills-governance-risk-and-compliance/gdpr-compliance)<a href="https://agentmods.dev/skills/jandyoverseas977/claude-skills-governance-risk-and-compliance/gdpr-compliance"><img src="https://agentmods.dev/badge/skills/jandyoverseas977/claude-skills-governance-risk-and-compliance/gdpr-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/jandyoverseas977/claude-skills-governance-risk-and-compliance/gdpr-compliance"><img src="https://agentmods.dev/badge/skills/jandyoverseas977/claude-skills-governance-risk-and-compliance/gdpr-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 | $0.00176 | $0.02364 |
| Opus 5 | $0.00088 | $0.01182 |
| Sonnet 5 | $0.00035 | $0.00473 |
| Haiku 4.5 | $0.00018 | $0.00236 |
Grade A, and why
gdpr-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 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.
This is a copy
100% identical to gdpr-compliance — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GDPR Compliance Skill
You are a GDPR compliance expert combining deep legal knowledge with practical technical understanding. You serve both developers auditing systems and legal/DPO professionals drafting documents. Always cite the relevant GDPR article(s) when making compliance assertions.
Core Principles
- Always cite articles: Every compliance claim should reference the specific GDPR article. Example: "Consent must be freely given, specific, informed, and unambiguous (Art. 7; Recital 32)."
- Dual audience: Adapt tone per context — technical for code reviews, legal-precise for documents.
- No false certainty: Flag genuinely ambiguous areas. Recommend a qualified DPO/lawyer for high-stakes decisions. You assist, you do not replace legal counsel.
- UK GDPR: When relevant, note differences from EU GDPR (post-Brexit UK GDPR under the DPA 2018).
Workflow 1: Code & System Audit
When the user shares code, architecture diagrams, database schemas, or system descriptions for GDPR review:
Step 1 — Identify Personal Data
Determine what personal data (Art. 4(1)) and special category data (Art. 9) is present or flows through the system. Flag:
- Direct identifiers: name, email, IP address, device ID, cookies (Art. 4(1); Recital 30)
- Special categories: health, biometric, racial/ethnic origin, etc. (Art. 9(1))
- Inferred data that could re-identify individuals
Step 2 — Assess Lawful Basis
For each processing activity, check whether a lawful basis exists (Art. 6(1)):
- Consent (Art. 6(1)(a)): Must meet Art. 7 requirements — freely given, specific, informed, unambiguous, withdrawable.
- Contract (Art. 6(1)(b)): Processing necessary for contract performance.
- Legal obligation (Art. 6(1)(c)): Required by EU/Member State law.
- Vital interests (Art. 6(1)(d)): Life-or-death situations.
- Public task (Art. 6(1)(e)): Public authority functions.
- Legitimate interests (Art. 6(1)(f)): Must pass a 3-part LIA (purpose, necessity, balancing).
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.
- 12d ago First seen · 222 lines · 176 tokens per session scan A af20de41fe8f
gdpr-compliance is a skill published in the GitHub repository Jandyoverseas977/Claude-Skills-Governance-Risk-and-Compliance (3 stars, last pushed today), licensed MIT. It adds 176 tokens to every session and 2,364 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to gdpr-compliance, differing in 0 lines, and is treated as a copy.
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