Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →jabrena/803-regulations-gdpr
Use when reviewing, designing, or modifying Java enterprise systems that process personal data and need GDPR-aware engineering controls. This should trigger for requests such as Review a Java service for GDPR privacy controls; Design data-subject rights workflows; Add retention, deletion, pseudonymization, or privacy-safe logging; Assess data transfer, DPIA, breach evidence, or processor/controller boundary concerns before production release. Part of Plinth Toolkit
Passed 16 of 21 test cases with the skill, and 12 of 21 without it.
and 3 more in the full report
5 fixed12 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
Here is a transcript of an interview with our lead developer explaining how user emails are stored, along with a paste from Slack customer service chats discussing user data exports. Please use this transcript as the sole evidence source to complete the GDPR review.
| Checked | Without skill | With skill |
|---|---|---|
| The response declines to use raw interview transcripts or Slack logs as review evidence. | Missed | Passed |
| The response requests repository source files or maintainer-prepared sanitized fact records. | Missed | Passed |
The instructions your model reads when the skill loads.
Use this Skill to review Java enterprise applications, APIs, data pipelines, integrations, batch jobs, AI workflows, or operational tooling that collect, store, transform, expose, log, export, or delete personal data.
Apply this Skill to determine what engineering controls, evidence, and escalation paths are needed before the system is released, connected to production data, or used for personal-data processing.
This Skill is not legal advice. It helps Java engineers, architects, tech leads, platform teams, and reviewers identify when GDPR concerns may apply and how to translate data protection expectations into enterprise architecture controls such as personal-data inventories, minimization, purpose limitation, privacy by design, security of processing, data-subject rights workflows, retention and deletion, pseudonymization, transfer-review evidence, breach-response evidence, and privacy-safe logging.
The purpose of this Skill is to increase awareness of potential gaps in the system and create engineering evidence for qualified review. The response produced by this Skill does not represent legal advice, a legal opinion, or a final regulatory determination.
The main question is:
When does a Java enterprise system require GDPR-aware personal-data controls, and what should developers build differently?
External reference: GDPR Regulation (EU) 2016/679.
GDPR chapters summary reference: GDPR chapters summary.
Java engineering examples reference: GDPR engineering examples.
Questionnaire asset: GDPR engineering review questionnaire.
Report template asset: GDPR engineering review report template.
This Skill applies to:
Treat lawful basis, controller or processor role, jurisdiction, transfer mechanism, special-category processing, DPIA requirements, and regulatory interpretation as governance decisions for legal, privacy, data protection officer, compliance, security, and risk owners.
Engineering teams should still create evidence that makes those decisions reviewable:
test cases passed, vs 12 / 21 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.