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zsrrica-pixelzsrrica-pixel/gdpr-compliance-plugin/skills/dpia/SKILL.md

dpia

Skill1 starsChanged 41 days agoMITView on GitHub

Conduct a Data Protection Impact Assessment (GDPR Art. 35) for a processing activity, product feature, or system. Use when the user asks whether a DPIA is needed or wants one drafted.

3 other projects use a version of this.

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  • Other versions3 projects use a version of this.

    Word for word · 0

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    None found.

    Wrote their own version · 3

    1. grcmana/grc-os★ 2same name
    2. grcmana/grcskills★ 2same name
    3. kaandgnsh/Claude-Blue★ 0same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository6 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When sources conflict (privacy notice vs.

    line 16

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Files
SKILL.md

DPIA

  1. Gather: purpose, data categories, data subjects, recipients, transfers outside the EEA, retention, technology used (especially AI/profiling). Ask for anything missing.
  2. Screening: check against the Art. 35(3) triggers and the EDPB's nine criteria (scoring, automated decisions, systematic monitoring, sensitive data, large scale, matching datasets, vulnerable subjects, new technology, blocking rights). Two or more criteria usually means a DPIA is required. State the verdict and why.
  3. Draft the DPIA with these sections: systematic description; necessity and proportionality (lawful basis, minimisation, retention); risk assessment (likelihood x severity per risk to data subjects); mitigation measures; residual risk; DPO advice; Art. 36 prior consultation if residual risk stays high.
  4. Mark any assumption clearly. This is a working draft for the controller or DPO to review, not legal advice.

Scale and conflicts

  • Rating scale: Likelihood and Severity each Low/Medium/High; level = the higher of the two unless both are Low. State that ratings are assumptions for the DPO to confirm.
  • Borderline screening that hinges on unknown facts (e.g. "large scale", uploaded content): recommend treating the DPIA as required until answered, and list the deciding questions.
  • When sources conflict (privacy notice vs. widget text vs. code), do not pick one: list each claim, its source, and mark it a transparency risk. Read relevant local source (backend function, widget) but cap the review to the data flow in question.
  • End with open questions for the controller; do not invent facts.

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