ai-data-privacy
ai-data-privacy is a Privacy & regulatory compliance skill for AI agents, published by UnitOneAI in the SecuritySkills repository on GitHub. Skillspace rates ai-data-privacy D (67/100) and it passed the safety scan; the rating is based on static analysis only.
Reviews AI/ML systems for data privacy and governance risks including training data privacy, PII exposure in prompts and completions, data retention policies, model memorization risks, and regulatory compliance. Auto-invoked when reviewing systems that process personal data through LLMs, train or fine-tune models on user data, or deploy AI in regulated industries. Produces a structured assessment mapped to NIST AI RMF 1.0 and OWASP LLM02:2025 (Sensitive Information Disclosure).
- Grade
- D
- Quality
- 67 / 100
- Safety
- Passed
- GitHub stars
- 32
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 76 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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