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 boshi-xixixi/TraeSkill --skill gdpr-compliantgit clone --depth 1 https://github.com/boshi-xixixi/TraeSkillWrote 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/boshi-xixixi/traeskill/gdpr-compliant)<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/gdpr-compliant"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/gdpr-compliant/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/boshi-xixixi/traeskill/gdpr-compliant"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/gdpr-compliant.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 | $0.00139 | $0.02729 |
| Opus 5 | $0.00069 | $0.01365 |
| Sonnet 5 | $0.00028 | $0.00546 |
| Haiku 4.5 | $0.00014 | $0.00273 |
Grade A, and why
gdpr-compliant 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 9d 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 — 284 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GDPR Engineering Skill
Actionable GDPR reference for engineers, architects, DevOps, and tech leads. Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.
Golden Rule: Collect less. Store less. Expose less. Retain less.
For deep dives, read the reference files in references/:
references/data-rights.md— user rights endpoints, DSR workflow, RoPAreferences/security.md— encryption, hashing, secrets, anonymizationreferences/operations.md— cloud, CI/CD, incident response, architecture patterns
1. Core GDPR Principles (Article 5)
| Principle | Engineering obligation |
|---|---|
| Lawfulness, fairness, transparency | Document legal basis for every processing activity in the RoPA |
| Purpose limitation | Data collected for purpose A MUST NOT be reused for purpose B without a new legal basis |
| Data minimization | Collect only fields with a documented business need today |
| Accuracy | Provide update endpoints; propagate corrections to downstream stores |
| Storage limitation | Define TTL at schema design time — never after |
| Integrity & confidentiality | Encrypt at rest and in transit; restrict and audit access |
| Accountability | Maintain evidence of compliance; RoPA ready for DPA inspection at any time |
2. Privacy by Design & by Default
MUST
- Add
CreatedAt,RetentionExpiresAtto every table holding personal data at creation time. - Default all optional data collection to off. Users opt in; they never opt out of a default-on setting.
- Conduct a DPIA before building high-risk processing (biometrics, health data, large-scale profiling, systematic monitoring).
- Update the RoPA with every new feature that introduces a processing activity.
- Sign a DPA with every sub-processor before data flows to them.
MUST NOT
- Ship a new data collection feature without a documented legal basis.
- Enable analytics, tracking, or telemetry by default without explicit consent.
- Store personal data in a system not listed in the RoPA.
What ships with it
2 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.
- 9d ago First seen · 284 lines · 139 tokens per session scan A e1f33a817a1d
gdpr-compliant is a skill published in the GitHub repository boshi-xixixi/TraeSkill (263 stars, last pushed 4mo ago), licensed MIT. It adds 139 tokens to every session and 2,729 once invoked, about $0.0007 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.
Other skills, from other repositories
azure-health-data-services
Expert knowledge for Azure Health Data Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using FHIR/DICOM APIs, bulk import/export, de-identification…
nist-ai-rmf
AI risk assessment using NIST AI RMF 1.0 framework. Evaluate AI systems across 4 core functions (Govern, Map, Measure, Manage) for trustworthy and responsible AI deployment.
gdpr-audit
GDPR compliance audit of code, plans, schemas, or IaC. Produces a findings report with article citations, severity, confidence, and fixes; flags evidence gaps. Not a substitute for a DPO/lawyer.
iso-42001-ai-governance
AI governance readiness and gap assessment using ISO/IEC 42001:2023. Evaluate AI management-system practices for risk management, accountability, transparency, security, and continuous improvement.
<skill-name>
A template for defining a coding-agent skill, including its title, trigger situations, overview, workflow, common mistakes, and optional references.
akf-trust-metadata
The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA aud.