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 BagelHole/DevOps-Security-Agent-Skills --skill gdpr-compliancegit clone --depth 1 https://github.com/BagelHole/DevOps-Security-Agent-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/bagelhole/devops-security-agent-skills/gdpr-compliance)<a href="https://agentmods.dev/skills/bagelhole/devops-security-agent-skills/gdpr-compliance"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/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/bagelhole/devops-security-agent-skills/gdpr-compliance"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/gdpr-compliance.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 | $0.00031 | $0.04349 |
| Opus 5 | $0.00015 | $0.02174 |
| Sonnet 5 | $0.00006 | $0.00870 |
| Haiku 4.5 | $0.00003 | $0.00435 |
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 10d 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 — 561 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GDPR Compliance
Implement General Data Protection Regulation requirements for organizations that process personal data of EU/EEA residents, covering lawful processing, data subject rights, and technical safeguards.
When to Use
- Processing personal data of EU/EEA residents in any capacity
- Building consent management and preference centers
- Implementing Data Subject Access Request (DSAR) workflows
- Conducting Data Protection Impact Assessments (DPIAs)
- Setting up data processing agreements with third-party processors
- Designing systems with privacy by design and by default principles
Key Principles and Legal Bases
gdpr_principles:
article_5:
lawfulness_fairness_transparency:
description: "Process data lawfully, fairly, and transparently"
implementation:
- Document legal basis for every processing activity
- Provide clear privacy notices
- No hidden or deceptive data collection
purpose_limitation:
description: "Collect for specified, explicit, and legitimate purposes"
implementation:
- Define purpose before collection
- Do not repurpose data without new legal basis
- Document all processing purposes in ROPA
data_minimization:
description: "Adequate, relevant, and limited to what is necessary"
implementation:
- Collect only required fields
- Review data models for unnecessary fields
- Remove optional fields that are not used
accuracy:
description: "Accurate and kept up to date"
implementation:
- Provide self-service profile editing
- Implement data validation at point of entry
- Schedule regular data quality reviews
storage_limitation:
description: "Kept no longer than necessary"
implementation:
- Define retention periods per data category
- Automate deletion when retention expires
- Document retention schedule
integrity_and_confidentiality:
description: "Appropriate security measures"
implementation:
- Encryption at rest and in transit
- Access controls and audit logging
- Pseudonymization where appropriate
accountability:
description: "Demonstrate compliance"
implementation:
- Maintain Records of Processing Activities
- Conduct DPIAs for high-risk processing
- Appoint DPO if required
legal_bases:
article_6:
consent: "Freely given, specific, informed, unambiguous"
contract: "Necessary for performance of a contract"
legal_obligation: "Required by EU or member state law"
vital_interests: "Protect life of data subject or another person"
public_interest: "Task carried out in public interest"
legitimate_interest: "Legitimate interest not overridden by data subject rights"
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.
- 10d ago First seen · 561 lines · 31 tokens per session scan A 9e4e44f70a2d
gdpr-compliance is a skill published in the GitHub repository BagelHole/DevOps-Security-Agent-Skills (1,071 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 4,349 once invoked, about $0.0002 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.
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